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WO2024233203A1 - Method and apparatus for providing on demand paint mixing components from a remote location - Google Patents

Method and apparatus for providing on demand paint mixing components from a remote location Download PDF

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Publication number
WO2024233203A1
WO2024233203A1 PCT/US2024/027134 US2024027134W WO2024233203A1 WO 2024233203 A1 WO2024233203 A1 WO 2024233203A1 US 2024027134 W US2024027134 W US 2024027134W WO 2024233203 A1 WO2024233203 A1 WO 2024233203A1
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WO
WIPO (PCT)
Prior art keywords
coating
vehicle
data
remote
color
Prior art date
Application number
PCT/US2024/027134
Other languages
French (fr)
Inventor
Ryan Keith WOOLFENDEN
Original Assignee
Ppg Industries Ohio, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ppg Industries Ohio, Inc. filed Critical Ppg Industries Ohio, Inc.
Publication of WO2024233203A1 publication Critical patent/WO2024233203A1/en

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Definitions

  • the present disclosure relates to devices, computer-implemented methods, and systems for efficiently providing paint/coating matching and mixing from a different location than where the paint/coating is applied to an asset.
  • Coatings can protect a coated material from corrosion, such as rust. Coatings can also provide an aesthetic function by providing a particular color and/or texture to an object.
  • a computerized method of receiving on-demand coatings delivered from a remote location includes displaying a user interface on a digital display of a digital device being accessed by a user at a geographic location.
  • the method further includes receiving, through the user interface, user input that creates a record for a vehicle to be refinished, wherein the record identifies details concerning the vehicle.
  • the method further includes receiving from a digital color measurement device spectrophotometric data and image data corresponding to the vehicle.
  • the method further includes displaying a representation of the vehicle in the form of a plurality of selectable vehicle parts to be refinished, and receiving user input at the user interface to select a vehicle part.
  • the method further includes sending to a remote mixing server in a different geographic location a requested order to mix an amount of coating that reflects a quantity of coating calculated for the selected a vehicle pail a coating color of the coating being based on an identified color match identified based on the spectrophotometric data.
  • a computerized method of providing on-demand coatings to a remote location based on vehicle and location specific data specified at the remote location includes sending display instructions for display of a user interface to a remote client computer system being accessed by a user at a geographic location.
  • the method further includes receiving from the client computer system user input that creates a record for a vehicle to be refinished, wherein the record identifies the vehicle by a year, make, and model.
  • the method further includes receiving from the client computer system digital color measurement device spectrophotometric data and image data corresponding to the vehicle to be refinished.
  • the method further includes based on the spectrophotometric data, identifying a color match corresponding to the vehicle to be refinished.
  • the method further includes sending display instructions of the vehicle in the form of a plurality of selectable vehicle parts to be refinished, and receiving user selection of a vehicle part through the user interface.
  • the method further includes, in response to the selection of the vehicle part, instructing a mixing device to mix a requested order comprising the color match and a quantity of coating calculated for the selected vehicle part.
  • Figure 1 A illustrates a schematic diagram of a paint streaming system, in accordance with the present disclosure
  • Figure IB illustrates a schematic diagram of a user system, in accordance with the present disclosure
  • Figure 2A illustrates a diagram of a user interface prior to selecting of a part of an asset that is to be refinished, in accordance with the present disclosure
  • Figure 2B illustrates a diagram of the user interface after selecting of a part of an asset that is to be refinished, in accordance with the present disclosure
  • Figure 2C illustrates a diagram of an alternative example of the user interface prior to selecting of a part of an asset that is to be refinished, in accordance with the present disclosure
  • Figure 2D illustrates a diagram of the alternative example of the user interface after selecting of a part of an asset that is to be refinished, in accordance with the present disclosure
  • Figure 3 illustrates a diagram of the user interface when finalizing a mix order, in accordance with the present disclosure
  • Figure 4 illustrates a flow diagram of a client method, in accordance with the present disclosure.
  • FIG. 5 illustrates a flow diagram of a server method, in accordance with the present disclosure.
  • Paint Streaming or Mixing as a Service is a service which allows entities to accurately and efficiently mix and deliver coatings and sundries to customers on demand. This service saves time, improves accuracy, eliminates waste, and reduces costly overhead, in favor of an on-demand model in which anyone can be a customer, and offers added sustainability benefits via a closed-loop product and packaging waste management process.
  • FIG. 1 depicts a schematic diagram of a paint streaming system 100 that includes a user system 110, a remote mixing server 140, and a server 180, each of which can be connected via a network 150.
  • the user system 110 includes a computing device 116 and/or a portable device 114 on which is executed a method of communicating a paint request to a remote mixing server 140.
  • the user system 110 may further include a router 120, which can be wireless and/or wired, but, without loss of generality
  • FIG. 1 A illustrates a non-limiting example of a wireless router 120 (c.g., a WIFI router or a router using BLUETOOTH or Near Field Communication (NFC) technology).
  • a wireless router 120 c.g., a WIFI router or a router using BLUETOOTH or Near Field Communication (NFC) technology.
  • the system 110 can be an internet of things (loT), for example.
  • the user system 110 may further include a user scale 130 and a sensor box 132. Additionally, the user system 110 may include an asset 102 (e.g., an automobile that is to be repaired and/or repainted or partially repainted) and a spectrophotometer 112.
  • asset 102 e.g., an automobile that is to be repaired and/or repainted or partially repainted
  • the sensor box 132 includes a physical enclosure enclosing the sensor box 132. Placing the components of the sensor box 132 within the physical enclosure allows the components to operate within an environment where painting spray may otherwise interfere with the electronics.
  • the user scale 130 can be a separate device that can be external to the sensor box 132. This separation allows the user scale 130 to be retrofit with the sensor box 132 such that the user scale 130 gains potentially new features provided by the sensor box 132.
  • the sensor box 132 may include a local communication interface 134 configured to receive a physical connector from the user scale 130.
  • the local communication interface 134 which may include a serial port, but one will appreciate that any number of different types of local communication interfaces 134 may be used.
  • the local communication interface 134 may comprise a universal serial bus (USB), a parallel port, a SPT port, or any other type of physical port.
  • USB universal serial bus
  • SPI port serial port
  • any number and combination of these ports or similar ports may be used according to the present disclosure .
  • the user scale 130 may be either an analog scale or a digital scale, or a combination thereof. Further in various examples, the user scale 130 lacks a hardware network interface, such that the user scale 130 is not equipped with hardware and/or software to communicate over a network connection. As such, in some examples, the user scale 130 is able to communicate with the remote server 180 through the sensor box 132.
  • the sensor box 132 also may include a network communication interface 136 configured to communicate with an internet gateway.
  • the network communication interface 136 is depicted as an Ethernet port, but may comprise another data/connection port, including, e.g., any connection capable of network communications, such as but not limited to, a WIFI network interface or a BLUETOOTH network interface.
  • the internet gateway may include a router, a modem, or any other conventional network gateway device.
  • the sensor box 132 may communicate with the wireless router 120 or with the network 150 through an internet gateway.
  • the sensor box 132 includes a sensor 138.
  • the sensor 138 is shown with dashed lines to indicate that the sensor may be visible on the sensor box 132 or that it may be integrated within the physical enclosure of the sensor box 132.
  • the sensor 138 may comprise a climate sensor such as a temperature sensor, a humidity sensor, a pressure sensor, an altimeter, a locationdetection antenna (e.g., a GPS radio), and/or any other sensor capable of providing climate data describing an aspect of a physical environment around the user system 110.
  • the sensor 138 includes a plurality of sensors of including some sensors of different types.
  • the sensor 138 comprises an interchangeable hardware slot that can be configured to receive a plurality of different sensor types. Accordingly, the sensor 138 can be modular such that different sensors and different types of sensors can be added or removed from the sensor box 132.
  • various layers of the coating may be sensitive to the local environment conditions. For example, to avoid a clear coat having a cloudy appearance, a certain ratio of solvent to solute may be required, which ratio depends on local temperature and humidity.
  • a recipe for a given layer may change depending on the local conditions. The local conditions are measured by the sensor box 132 at the location of the user system 110 because that is the location at which the coatings will be applied to the asset 102, which dictates the desired recipe for the layers. Thus, in some examples, geographic information for a user may be pertinent to a recipe mixed a remote location.
  • a user geographic location may be located at least 20 km from a remote mixing location.
  • the user geographic location may have a temperature, humidity, barometric pressure, etc. that is different by a predetermined about from the remote location where a recipe is mixed.
  • the sensor box 132 may include a processor configured to process data received from the user scale 130 and the sensor 138.
  • the sensor box 132 further includes a first computer- readable media having stored thereon executable instructions that when executed by the processor configure the sensor box 132 to perform various acts.
  • the sensor box 132 receives, through the local communication interface 134, a mass variable from the user scale 130.
  • the mass variable provides a mass of a coating mixture resting on the user scale 130.
  • the sensor box 132 also receives, from the sensor 138, a sensor variable.
  • the sensor variable provides data describing an aspect of a physical environment around the coating mixture.
  • the sensor variable may comprise an ambient temperature, a humidity level, an atmospheric pressure, an altitude, a geographic location (from the location-detection antenna or from an IP address localization), and/or any other data pertinent to the physical environment around the coating mixture. Accordingly, the sensor variable may provide a humidity reading from the physical environment around the coating mixture and a temperature reading from the physical environment around the coating mixture.
  • the remote mixing server 140 includes a computing device 146, a computer readable memory storage 144, and a distributor scale 142.
  • the server 180 includes a processor 184, a computer readable memory storage 182, and a matching engine 186.
  • the user system 110, the remote mixing server 140, and the server 180 communicate with each other via the network 150.
  • the remote mixing server 140 receives information regarding a layer composition to be applied to the asset 102 and mixes/generates the layer composition in a specified quantity.
  • the server 180 can be a cloud-based system, for example, and the server 180 determines the recipes for the layer composition (e.g., which colorants and quantities thereof to add to a paint to match a color of the asset 102).
  • the server 180 can use distributed computing or can use localized computing, such as being localized, c.g., at the remote mixing server 140.
  • the server 180 can be pail of, or hosts a cloud-based service.
  • the server 180 may host subscription services for the user system 110.
  • a user at the user system 110 can log in to a subscription service hosted by the server 180 by providing login credentials through a user interface.
  • the subscription service includes an option for a remote paint distributor that is operating a remote mixing server to both deliver the requested order and to retrieve from the user any waste or packaging upon completion of refinishing the vehicle to be repaired.
  • both the user system 110 includes a user scale 130 and the remote mixing server 140 includes a distributor scale 142 because some coating compositions are generated using the user scale 130 of the user system 110 and other coating compositions are generated using the distributor scale 142 of the remote mixing server 140.
  • compositions e.g., the paint layer
  • volatile coating compositions are generated by the user system 110. This example can be efficient because volatile coating compositions require relatively few ingredients/constituents, whereas inventories of many colorants may be used to match the many possible paint colors of various assets.
  • the coating compositions may be generated and supplied by the remote mixing server 140.
  • the user scale 130 may be no longer needed in the user system 110 and therefore the user scale 130 may be omitted.
  • the asset 102 has been coated with a target coating.
  • an undercoat has been applied to the asset 102 as well.
  • the owner of the asset 102 may want the shop to paint the wrecked areas of the asset 102 with the same coating as the other areas to maintain consistency across the asset 102. To do so, the shop will be tasked with identifying that target coating.
  • the user system 110 generates spectrometric data of the target coating (e.g., using the spectrophotometer 112 or using a camera on the portable device 114).
  • the spectrometric data may be gathered by a camera, a spectrometer, such as spectrophotometer, or any other device capable of scanning the target coating on the asset 102 and providing characterization data relating to attributes of the target coating.
  • the spectrometric data can comprise spectrophotometric data, spectrocolorimetric data, data acquired via image processing, and/or any other similar data.
  • the server 180 can process the spectrometric data through a probabilistic colorant analysis.
  • the probabilistic colorant analysis identifies a set of colorants that are likely present in the coating and associates with each colorant a probability that the colorant is present in the target coating. Based on these results, a formulation for a best fit coating may be identified
  • test coating Sometimes a spray out or “test coating” is generated for the identified formulation and spectrocolorimetric data can be taken of the “test coating” to confirm it matches the target coating on the asset 102. If not, the identified formulation can be tweaked. Often the probabilistic colorant analysis can be sufficient to generate a color match and corresponding recipe without the additional step of generating a “test coating.”
  • colorants include absorption and scattering pigments, effect pigments, and/or any other related coating or coating component.
  • the disclosed server 180 can analytically identify potential colorants within the target coating.
  • potential colorants are colorants that are identified by a probabilistic colorant analysis as likely being in the target coating.
  • the potential colorants are fed into a formulation or analysis engine that can be seeded with colorants that have already been identified as having a high probability of being present within the target coating.
  • Any number of potential formulations may be identified by the server 180. Often, the potential formulations can be ranked based on how closely they correspond, align, or match with the target coating. In response to identifying the potential formulations, a skilled user is able to review the coatings in a user interface and make a selection regarding which coating the user thinks most closely aligns with the target coating.
  • a selected potential formulation can be referred to as a “test coating.” That is, the test coating can be a coating that can be a selected potential formulation. If a spray out is needed to verify the coating color for a given formulation, then the given formulation may be applied to another asset, for example, at the remote facility. This other asset can be a test surface used for application purposes to gauge how the given formulation can be applied and cured. Once the test coating cures, it can be analyzed using the techniques mentioned earlier, e.g., using a spectrophotometer such as spectrophotometer 1 12. In any event, the test coating can then be compared against the target coating of the asset 102 to determine whether a true alignment exists between those two coatings. If the test coating is not satisfactorily aligned with the target coating, then an adjustment to the coating attributes of the test coating can be performed in an attempt to bring the test coating into a matched state relative to the target coating.
  • a spectrophotometer such as spectrophotometer 1 12.
  • the server 180 identifies a best fit match to a target coating.
  • the server 180 receives color data from a spectrophotometer 112 and identifies therefrom a best fit match.
  • the server 180 can then generate rendering data and formulation data, which can be transmitted to the user system and distributor, for example.
  • the computing device 116 and/or the portable device 114 can visually display a selected number of coatings that potentially match with the target coating. A user can review these so-called “best fit coatings” and can select one for further testing and analysis, such as by applying it to an asset and then obtaining coating attributes for the applied coating.
  • the server 180 may include a processor 184 and a matching engine 186.
  • the server 180 may include a computer-readable hardware storage device, such as storage 182.
  • the storage 182 includes instructions that are executable by a processor 184 to configure the server 180 to perform any number of operations, such as the methods discussed below.
  • the computer server 180 also includes or has access to a matching engine 186.
  • the server 180 can be also able to communicate with remote devices via the network 150 (e.g., the Internet).
  • the spectrophotometer 112 can be used to identify coating attributes (e.g., colorimeter data and/or reflectance characteristics, which can then be used to infer color attributes) for both the target coating and the new coating applied to the asset 102.
  • the coating attributes can include color formula component information, which can be inferred based on the reflectance data obtained by the spectrophotometer 112.
  • a mapping or prediction process can be available to correlate reflectance with known color formula information.
  • the color formula component information can include various information on pigments (e.g., XIRALLIC, gonioapparent pigment, metallic flake, mica, pearlescent pigments, and the like), multiple coating layer information (e.g., tricoat, XIRALLIC), various physical or raw data measured for each coating sub-component, such as spectral, colorimetric, or other data for various tints, base coats, and effect pigments, including such data as measured from various combinations of such sub- components.
  • the coating attributes can include predicted spectral or colorimetric data for given formulas where actual measurements have not yet been performed.
  • the coating attributes can include raw physical measurements and/or predicted measurements, such as spectral, and/or other colorimetric measurements including but not limited to CIELab (i.e., L*a*b*) values, spectrophotometer reads, RGB, and gamma- RGB values, and/or XYZ tristimulus data, etc. for each coating, and each coating subcomponent.
  • CIELab i.e., L*a*b*
  • the coating attributes include data detailing a mixture of raw physical measurements for a number of coatings and coating sub-components, and predicted physical measurements for other coatings or coating sub-components based on measurements taken from adjacent colors, such as colors in the same color space, but perhaps differing by a sub-component (e.g., different base), or differing by slight changes in hue, chroma, or toner ratio.
  • the coating attributes can also include barcode, VIN, or QR code data.
  • the coating information may include information relating to how a coating can be applied to an asset.
  • the information can include which tools are used, how the coating can be cured, under what environmental conditions the coating can be applied and allowed to cure, and so on.
  • the coating information may include environmental data detailing the environmental conditions that exist when a coating is applied and allowed to cure.
  • environment data can include temperature, atmospheric pressure, elevation, humidity, time of day, season of the year, and so forth.
  • the storage 182 may store secondary indicia associated with each color and color formulation.
  • the storage 182 can store barcode, QR code, and/or VIN (vehicle identification number) data associated with each color record, which may enable an end user to scan the corresponding code on the asset itself, and then enable the user to pull the record for the original color as stored by the storage 182. Pulling the full record for the original color can indicate components/ingredients/layers, and other parameters known regarding the original coating application.
  • the storage 182 may also serve as a central repository for the most recent updates of a coating manufacturer's colors, color names, and related physical data, such as formula, spectral, colorimetric, RGB, CIELAB (i.e., L*a*b*), and/or XYZ tristimulus data and related conversion data, as well as image data, for each color and corresponding color sub-component used to make a particular coating.
  • the storage 182 may also, for example, coordinate with a database of an asset (e.g., auto) manufacturers (which may or may not be the coating manufacturer).
  • This coordination can ensure the cloud color manager can be able to regularly obtain similar formula, spectral, colorimetric, RGB, CIELAB (i.e., L*a*b*), and/or XYZ tristimulus values (and related conversions) for each color used to coat the assets by the asset manufacturer as they are applied each year.
  • the secondary and physical data corresponding to each color can be used to retrieve color matches as described more fully herein.
  • "primary color data" refers to the color name or color code used to identify a particular coating, namely human readable labels that an end user might use to identify a color or color profile, such as Midnight Blue.
  • second color data refers to inherent physical characteristic data and machine-readable data other than express color name or color code, such as barcode, QR code, or physical characteristic data associated with a particular coating.
  • Physical characteristic data can include spectral reflectance data, colorimeter data, CIELAB values, RGB values, and so forth.
  • the color data can be obtained using the spectrophotometer 112 and/or an imaging device, such as a camera on the portable device 114, which may be a tablet computer or smartphone, for example.
  • the server 180 receives the color data (or indicia/information representing the color data).
  • the server 180 can use a matching engine 186 to perform a number of analyses of the image, spectral, and/or colorimetric data received to identify relevant, closest color matches among colors stored in storage 182.
  • matching engine 186 can identify that barcode information received in color data identifies a particular color from a particular make, model, and year of an automobile, and further identify from information in the storage 182 which particular undercoat(s) and pigment effects were used in the formula for that particular color record.
  • matching engine 186 can determine that the original coating identified in the color data is not one created by a known paint manufacturer stored in the storage 182, but that several other colors that have similar secondary color data by comparison of physical characteristics, such as similar spectral, CIELab, and/or XYZ tristimulus value matches. Matching engine 186 can then gather those color records that match or otherwise fit within an acceptable range of deviation from the actual measurement (e.g., by computing a z-score of the measured color relative to a group of colors with similar physical measurements), and provide that as a response for further user input. The server 180 can then send a response back to the user system 110 and/or remote mixing server 140 in the form of a color match message. For example, rendering data and color data of the potential color match(es) can be sent to the user system 110 to be reviewed by a user, and formulation data of the potential color match(s) can be sent to the remote mixing server 140.
  • rendering data and color data of the potential color match(es) can be sent to the user system 110 to
  • the server 180 can generate rendering data that represent how the asset 102 would appear with a potential formulation applied to the asset 102.
  • the generated rendering data can instruct the computing device 116 and/or the portable device 114 to render an image of the asset 102 (or a generic version of the asset 102) with the entire asset 102 coated using the potential formulation or with just the damaged/repaired portion of the asset 102 coated using the potential formulation.
  • a user can select the potential formulation for comparison to select the best option.
  • FIGs. 2A-2D illustrate a user interface 300 that can be displayed on a display of the computing device 116 and/or the portable device 114.
  • a user of the user system 110 interacts with the user interface 300 to enter information for a desired coating composition.
  • the user can enter details for the vehicle data 310 including, e.g., year, make, and model information 312 and a vehicle identification number 314. This information can be used to identify sizes of various panels.
  • the user can interact with the user interface 300 to enter and/or edit information for location data 320 including, e.g., historical and preference data 322 and sensor data 324 for the sensor box 132.
  • the historical and preference data 322 can represent user preferences. For example, a user may prefer to request 20% more than a recommended quantity of the coating composition to provide a safety margin that ensures adequate material to complete a repainting/repair job. Such a preference can be stored and associated with the user as a default. Using the user interface 300, the user can edit this preference if a different safety margin is desired for a current job.
  • the user can enter information for the measured data 330 including, e.g., spectrophotometric data 332 acquired using the spectrophotometer and/or image data 334 (e.g., acquired using a camera of the portable device 114).
  • information for the measured data 330 including, e.g., spectrophotometric data 332 acquired using the spectrophotometer and/or image data 334 (e.g., acquired using a camera of the portable device 114).
  • the user interface 300 can also include a graphical user interface (GUI) 340 for receiving user input selecting a part of the asset 102 being repaired.
  • GUI graphical user interface
  • an asset 102 can be represented in a representation of the asset using an exploded view of the body panels, doors, and bumpers: none of the sections arc selected by a user.
  • a user can, c.g., hover a mouse cursor over a given part and click to select the given part.
  • FIG. 2B a driverside door panel has been selected. If a given part is not visible in the GUI 346, a user can rotate the rendering of the asset 102 until the desired part becomes visible.
  • FIGs. 2C and 2D the respective parts of the asset 102 are illustrated such that the pails are simultaneously visible in the GUI 340. In FIG. 2C, no parts have been selected, and, in FIG. 2D, a driver-side door panel has been selected.
  • FIG. 3 illustrates an example of the user interface 300 when finalizing an order.
  • the GUI 370 shows a rendering of the coated asset.
  • N potential formulations are identified (i.e., #1 potential formulation 372, #2 potential formulation 374, ... #N potential formulation 376).
  • a user can select which of these potential formulations they want to visualize, and the GUI 370 will display a rendering of the asset with the selected portion rendered to look like the selected potential formulation.
  • the user interface 300 can display information 341 of the selected formulations, including, e.g., the colorants 342 and their respective quantities 344. Additionally or alternatively, the formulation information 341 can include an estimate of a quantity of the coating composition required to coat the selected part and an estimate of the cost.
  • the user interface 300 can display finishing materials information 350 including, e.g., recommended amounts of consumables, such as tape, sealant, adhesives, and/or abrasives for the repainting/repair job.
  • These recommended consumables may include coating components 352 (e.g., examples of coating components may include an over coat, an under coat, a primer coat, or a clear coat) abrasives 354 (e.g., sandpaper), and masking tape.
  • the user interface 300 can display other instructions 360 including, e.g., waste management instructions 362 and application instructions 364. For example, expense and waste can be reduced by using reusable containers to transport and hold the coating composition and the coating components 352.
  • the waste management instructions 362 can direct the user how to handle and return the reusable containers to a distributor.
  • the application instructions 364 can direct a user regarding the proper conditions for applying coating composition and desirable environmental condition for curing the coating composition, for example.
  • FIG. 4 shows a flow diagram of a client method 400. Method 400 can be performed using a user system 110 to request delivery of a coating composition.
  • a user interface 300 can be displayed on a digital device (e.g., the computing device 116 or the portable device 114).
  • the digital device receives user inputs through the user interface 300, and the digital device creates therefrom a record for an asset (e.g., a vehicle) to be refinished.
  • the received data can include the vehicle data 310 and can include location data 320 (e.g., preference data 322).
  • color data can be received to indicate a color of the asset 102.
  • the color data may be measured using the spectrophotometer 112, and/or the color data may be acquired using an imaging device, such as a camera of the portable device 114.
  • the color data may include the measured data 330.
  • the received data on the digital device including the color data and the user inputs, are transmitted to a matching engine (e.g., the matching engine 186 on the server 180). Based on the color data (and possibly the user inputs) the matching engine determines a proposed color match.
  • the proposed color match can be based on the measured data, vehicle data, location information, age of the vehicle and/or other information.
  • the matching engine 186 may implement machine learning algorithms to determine the color match. While “a proposed color match” is described here, it should be appreciated that in some examples multiple proposed color matches may be generated. Thus, as used herein, “a proposed color match” should not be interpreted as limiting to only a single proposed color match.
  • the user interface 300 displays the color match(es).
  • N potential formulations that are identified as #1 potential formulation 372, #2 potential formulation 374, ... #N potential formulation 376).
  • the user interface 300 may also display three- dimensional rendering of the proposed color match(es).
  • step 450 the user uses the user interface 300 to select a proposed color match.
  • step 460 the user uses the user interface 300 to select a part of the asset 102 to be repainted/refinished. Using the selection of a part to be refinished and using the vehicle data 310, a surface area can be calculated for the part to be refinished. Based on this surface area, a quantity of coating composition can be determined. Additionally or alternatively, a look-up-table may directly provide the quantity of coating composition for the part to be refinished based on the vehicle data 310 without calculating the surface area to be refinished. The desired quantity of the coating composition can be adjusted up or down, depending on the user’s preferences (e.g., safety margin).
  • a mix order can be sent to the remote mixing server 140 for a coating composition corresponding to a selected proposed color match and the desired quantity.
  • the mix order may include various other items, such as consumable materials, that are used in the refinishing job.
  • FIG. 5 illustrates a server method 500 that can be performed by the remote mixing server 140 and/or the server 180.
  • the remote mixing server 140 and the server 180 may be collocated.
  • the server 180 may be a cloud-based application.
  • the server 180 may perform the steps of method 500, and, then once the order is finalized, the server 180 can send the mix order to the distributor for mixing of the coating composition.
  • a server 180 sends display instructions to a client (e.g., the user system 110) requesting user input.
  • the requested user input can include the vehicle data 310, for example, which can be entered by the user interacting with the user interface 300.
  • step 520 the requested user input can be received at the server 180 from the client, and a record can be created/ received by the server 180.
  • step 530 the server 180 receives from the client color data (e.g., the measured data 330).
  • the server 180 determines a proposed color match or a plurality of proposed color matches based on the received color data from the client.
  • the proposed color match(es) is/are sent to the client together with optional rendering data.
  • the rendering data can be generated at the server 180, and in other examples the rendering data can be generated at user system 110 based on the information of the proposed color match(es).
  • the server 180 awaits a selection from the client of one of the proposed color match(es). Note that in other examples, the server 180 may simply determine a color match without providing the user an opportunity to select a proposed color match.
  • the server 180 may implement machine learning algorithms to determine the color match.
  • the server 180 optionally receives information indicating the selected one of the proposed color match(cs).
  • the server 180 receives information indicating the selected part of the asset 102 that is to be refinished.
  • step 560 the server 180 receives from the client a mix order and communicates the mix order to the remote mixing server 140, which fulfills the mix order.
  • a computerized method of receiving on-demand coatings delivered from a remote location includes displaying a user interface on a digital display of a digital device being accessed by a user at a geographic location.
  • the method includes receiving, through the user interface, user input that creates a record for a vehicle to be refinished, wherein the record identifies details concerning the vehicle.
  • the method includes receiving from a digital color measurement device spectrophotometric data and image data corresponding to the vehicle.
  • the method includes displaying a representation of the vehicle in the form of a plurality of selectable vehicle parts to be refinished, and receiving user input at the user interface to select a vehicle part.
  • the method includes, sending to a remote mixing server in a different geographic location a requested order to mix an amount that reflects a quantity of coating calculated for the selected a vehicle part a coating color of the coating being based on an identified color match identified based on the spectrophotometric data.
  • the method includes receiving a message from the remote mixing server that confirms mixing of the requested order, and delivery details. Additionally or alternatively, the method includes causing, via the digital device, the quantity of the coating to be mixed based on the selected selectable part. Furthermore, in an additional or alternative configuration, the method includes identifying, via the digital device, from the calculated quantity, an amount of additional finishing materials to include with the coating to be mixed; wherein the finishing materials include an outer layer or clear coat and corresponding amount thereof that is calculated based on data taken from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished. Still further, in an additional or alternative configuration, the method includes the additional finishing materials further comprise tape, sealant, adhesives, or abrasives.
  • the method includes displaying application instructions.
  • the method includes displaying application instructions.
  • the method can further includes receiving climate data from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished.
  • the method includes storing the requested order in a cloud server that is remote from the geographic location of the user and the geographic location of the remote mixing server.
  • the method includes providing login credentials through the user interface; wherein the login credentials are associated with a subscription service.
  • the method includes the subscription service includes an option for a remote paint distributor that is operating the remote mixing server to both deliver the requested order and to retrieve from the user any waste or packaging upon completion of refinishing the vehicle to be repaired.
  • the method includes displaying a plurality of proposed color matches on the digital display, wherein the proposed color matches enable comparison through the digital display of the image data against the plurality of proposed color matches, and wherein the coating color of the coating being based on user selection in the user interface of one of the proposed color matches.
  • the method includes the coating color of the coating is based on the remote mixing server using the spectrophotometric data selecting a coating color.
  • a digital device includes a storage storing executable instructions; a display configured to display a user interface; and a processor configured to execute the executable instructions, wherein executing the executable instructions on the processor causes the digital device to perform method according to any of the preceding methods.
  • Still further or additional configurations can include, at a remote server computer, a computerized method of providing on-demand coatings to a remote location based on vehicle and location specific data specified at the remote location is disclosed.
  • the method includes sending display instructions for display of a user interface to a remote client computer system being accessed by a user at a geographic location.
  • the method includes receiving from the client computer system user input that creates a record for a vehicle to be refinished, wherein the record identifies the vehicle by a year, make, and model.
  • the method includes receiving from the client computer system digital color measurement device spectrophotometric data and image data corresponding to the vehicle to be refinished.
  • the method includes based on the spectrophotometric data, identifying a color match corresponding to the vehicle to be refinished.
  • the method includes sending display instructions of the vehicle in the form of a plurality of selectable vehicle pails to be refinished, and receiving user selection of a vehicle part through the user interface; and in response to the selection of the vehicle part, instructing a mixing device to mix a requested order comprising the color match and a quantity of coating calculated for the selected vehicle part.
  • the method of a computerized method of providing on-demand coatings to a remote location based on vehicle and location specific data specified at the remote location includes sending a message to the remote client computer that confirms mixing of the requested order, and delivery details.
  • the method of a computerized method of providing on-demand coatings to a remote location based on vehicle and location specific data specified at the remote location includes causing the quantity of the coating to be mixed based on the selected selectable part.
  • the method of a computerized method of providing on- demand coatings to a remote location based on vehicle and location specific data specified at the remote location, or any associated methods includes identifying from the calculated quantity, an amount of additional finishing materials to include with the coating to be mixed; wherein the finishing materials include an outer layer or clear coat and corresponding amount thereof that is calculated based on data taken from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished.
  • the method providing the additional finishing materials further comprising tape, sealant, adhesives, or abrasives.
  • the method further includes sending application instructions to the remote client computer system.
  • the methods includes receiving climate data from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished.
  • the method can include storing the requested order in a cloud server that is remote from the geographic location of the user and the geographic location of the remote server computer.
  • the method can include sending a plurality of proposed color matches to the remote client computer system for display at the remote client computer system, and wherein the coating color of the coating being based on user selection of one of the proposed color matches.
  • the methods includes the coating color of the coating being based on the remote mixing server using the spectrophotometric data selecting a coating color.
  • present disclosure may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like.
  • present disclosure may also be practiced in distributed computing environments where local and remote processing devices perform tasks and are linked (either by hardwired links, wireless links, or by a combination of hardwired or wireless links) through a communications network.
  • program modules may be located in both local and remote memory storage devices.
  • the present disclosure may comprise or utilize a special-purpose or general-purpose computer system that includes computer hardware, such as, for example, a processor and system memory, as discussed in greater detail below.
  • the scope of the present disclosure also includes physical and other computer-readable media for carrying or storing computer-executable instructions and/or data structures.
  • Such computer-readable media can be any available media that can be accessed by a general-purpose or special-purpose computer system.
  • Computer-readable media that store computer-executable instructions and/or data structures are computer storage media.
  • Computer-readable media that carry computer-executable instructions and/or data structures are transmission media.
  • the present disclosure can comprise two distinctly different kinds of computer-readable media: computer storage media and transmission media.
  • Computer storage media are physical storage media that store computer-executable instructions and/or data structures.
  • Physical storage media include computer hardware, such as RAM, ROM, EEPROM, solid state drives (“SSDs”), flash memory, phase-change memory (“PCM”), optical disk storage, magnetic disk storage or other magnetic storage devices, or any other hardware storage device(s) which can be used to store program code in the form of computerexecutable instructions or data structures, which can be accessed and executed by a general- purpose or special-purpose computer system to implement the disclosed functionality of the present disclosure.
  • Transmission media can include a network and/or data links which can be used to carry program code in the form of computer-executable instructions or data structures, and which can be accessed by a general-purpose or special-purpose computer system.
  • a “network” is defined as data links that enable the transport of electronic data between computer systems and/or modules and/or other electronic devices.
  • program code in the form of computer-executable instructions or data structures can be transferred automatically from transmission media to computer storage media (or vice versa).
  • program code in the form of computer-executable instructions or data structures received over a network or data link can be buffered in RAM within a network interface module ,and then eventually transferred to computer system RAM and/or to less volatile computer storage media at a computer system.
  • computer storage media can be included in computer system components that also (or even primarily) utilize transmission media.
  • Computer-executable instructions comprise, for example, instructions and data which, when executed at a processor, cause a general-purpose computer system, special-purpose computer system, or special-purpose processing device to perform a certain function or group of functions.
  • Computer-executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, or even source code.
  • CMOS complementary metal-oxide-semiconductor
  • present disclosure may be practiced in network computing environments with many types of computer system configurations, including, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, tablets, pagers, routers, switches, and the like.
  • the present disclosure may also be practiced in distributed system environments where local and remote computer systems, which are linked (either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links) through a network, both perform tasks.
  • a computer system may include a plurality of constituent computer systems.
  • program modules may be located in both local and remote memory storage devices.
  • Cloud computing environments may be distributed, although this is not required. When distributed, cloud computing environments may be distributed internationally within an organization and/or have components possessed across multiple organizations.
  • cloud computing is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services). The definition of “cloud computing” is not limited to any of the other numerous advantages that can be obtained from such a model when properly deployed.
  • a cloud-computing model can be composed of various characteristics, such as on- demand self-service, broad network access, resource pooling, rapid elasticity, measured service, and so forth.
  • a cloud-computing model may also come in the form of various service models such as, for example, Software as a Service (“SaaS”), Platform as a Service (“PaaS”), and Infrastructure as a Service (“laaS”).
  • SaaS Software as a Service
  • PaaS Platform as a Service
  • laaS Infrastructure as a Service
  • the cloud-computing model may also be deployed using different deployment models such as private cloud, community cloud, public cloud, hybrid cloud, and so forth.
  • a cloud-computing environment may comprise a system that includes a host that is capable of running virtual machines.
  • virtual machines emulate an operational computing system, supporting an operating system and perhaps other applications as well.
  • Each host may include a hypervisor that emulates virtual resources for the virtual machines using physical resources that are abstracted from view of the virtual machines.
  • the hypervisor also provides proper isolation between the virtual machines.
  • the hypervisor provides the illusion that the virtual machine is interfacing with a physical resource, even though the virtual machine interfaces with the appearance (e.g., a virtual resource) of a physical resource. Examples of physical resources including processing capacity, memory, disk space, network bandwidth, media drives, and so forth.

Abstract

Obtaining on-demand coatings delivered from a remote location based on vehicle data includes displaying a user interface on a digital display of a digital device being accessed by a user at a geographic location. User input is received that creates a record for a vehicle to be refinished. Spectrophotometric data and image data corresponding to the vehicle is received from a digital color measurement device. A representation of the vehicle in the form of selectable vehicle parts is displayed. A requested order is sent to a remote mixing server in a different geographic location to mix a user selected color match in an amount that reflects a quantity of coating calculated for a selected vehicle part.

Description

METHOD AND APPARATUS FOR PROVIDING ON DEMAND PAINT MIXING COMPONENTS FROM A REMOTE LOCATION
[0001] The present invention claims the benefit of priority to US Provisional Application No. 63/500,468, filed on May 5, 2023, the entire content of which is incorporated herein by reference.
BACKGROUND
1. Technical Field
[0002] The present disclosure relates to devices, computer-implemented methods, and systems for efficiently providing paint/coating matching and mixing from a different location than where the paint/coating is applied to an asset.
2. Background
[0003] Modern coatings provide several beneficial functions in industry and society. Coatings can protect a coated material from corrosion, such as rust. Coatings can also provide an aesthetic function by providing a particular color and/or texture to an object.
[0004] It is often desirable to identify a target coating composition. For instance, it might be desirable to identify a target coating composition on an asset, such as an automobile, that has sustained damage. However, due to the nature of complex mixtures within coatings, it is sometimes difficult to formulate, identify, and/or search for acceptable matching formulations and/or pigmentations. Even in the case where a suitable match can be identified, frequently the coating on the asset will have aged or denatured in such a way that recoating the damaged portion with the original coating still creates a mismatch in color upon later inspection.
[0005] The process of determining the paint color; matching the paint color and determining the formulation thereof, storing an inventory of pigments, effect pigments, coating components, etc.; and mixing an appropriate quantity of the matching paint can present challenges at each step of the process. This can be especially true for smaller repair and body shops which do not quickly turn over inventory of pigments and coating components. Further, the capital expenditure for sophisticated scales and mixing equipment might not be justified by a small repair shop. [0006] Thus, there are many opportunities for improving efficiency of determining, matching, mixing, and storing paint colors. These opportunities for improvements extend beyond economic and labor improvements and include improvements with respect to environmental costs of waste mitigation.
[0007] The subject matter claimed herein is not limited to examples that solve any disadvantages or that operate only in environments such as those described above. Rather, this background is only provided to illustrate one exemplary technology area where some examples described herein may be practiced.
BRIEF SUMMARY OF THE PRESENT DISCLOSURE
[0008] A computerized method of receiving on-demand coatings delivered from a remote location is disclosed. The method includes displaying a user interface on a digital display of a digital device being accessed by a user at a geographic location. The method further includes receiving, through the user interface, user input that creates a record for a vehicle to be refinished, wherein the record identifies details concerning the vehicle. The method further includes receiving from a digital color measurement device spectrophotometric data and image data corresponding to the vehicle. The method further includes displaying a representation of the vehicle in the form of a plurality of selectable vehicle parts to be refinished, and receiving user input at the user interface to select a vehicle part. The method further includes sending to a remote mixing server in a different geographic location a requested order to mix an amount of coating that reflects a quantity of coating calculated for the selected a vehicle pail a coating color of the coating being based on an identified color match identified based on the spectrophotometric data.
[0009] A computerized method of providing on-demand coatings to a remote location based on vehicle and location specific data specified at the remote location is disclosed. The method includes sending display instructions for display of a user interface to a remote client computer system being accessed by a user at a geographic location. The method further includes receiving from the client computer system user input that creates a record for a vehicle to be refinished, wherein the record identifies the vehicle by a year, make, and model. The method further includes receiving from the client computer system digital color measurement device spectrophotometric data and image data corresponding to the vehicle to be refinished. The method further includes based on the spectrophotometric data, identifying a color match corresponding to the vehicle to be refinished. The method further includes sending display instructions of the vehicle in the form of a plurality of selectable vehicle parts to be refinished, and receiving user selection of a vehicle part through the user interface. The method further includes, in response to the selection of the vehicle part, instructing a mixing device to mix a requested order comprising the color match and a quantity of coating calculated for the selected vehicle part.
BRIEF DESCRIPTION OF THE DRAWINGS rooioi To describe the manner in which the above-recited and other advantages and features can be obtained, a more particular description of the subject matter briefly described above will be rendered by reference to specific examples which are illustrated in the appended drawings. Understanding that these drawings depict only typical examples and are not therefore to be considered to be limiting in scope, examples will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:
[0011] Figure 1 A illustrates a schematic diagram of a paint streaming system, in accordance with the present disclosure;
[0012] Figure IB illustrates a schematic diagram of a user system, in accordance with the present disclosure;
[0013] Figure 2A illustrates a diagram of a user interface prior to selecting of a part of an asset that is to be refinished, in accordance with the present disclosure;
[0014] Figure 2B illustrates a diagram of the user interface after selecting of a part of an asset that is to be refinished, in accordance with the present disclosure;
[0015] Figure 2C illustrates a diagram of an alternative example of the user interface prior to selecting of a part of an asset that is to be refinished, in accordance with the present disclosure; [0016] Figure 2D illustrates a diagram of the alternative example of the user interface after selecting of a part of an asset that is to be refinished, in accordance with the present disclosure;
[0017] Figure 3 illustrates a diagram of the user interface when finalizing a mix order, in accordance with the present disclosure;
[0018] Figure 4 illustrates a flow diagram of a client method, in accordance with the present disclosure; and
[0019] Figure 5 illustrates a flow diagram of a server method, in accordance with the present disclosure. DETAILED DESCRIPTION
[0020] Paint Streaming or Mixing as a Service is a service which allows entities to accurately and efficiently mix and deliver coatings and sundries to customers on demand. This service saves time, improves accuracy, eliminates waste, and reduces costly overhead, in favor of an on-demand model in which anyone can be a customer, and offers added sustainability benefits via a closed-loop product and packaging waste management process.
[0021] Turning now to the figures, FIG. 1 depicts a schematic diagram of a paint streaming system 100 that includes a user system 110, a remote mixing server 140, and a server 180, each of which can be connected via a network 150. As shown in FIGs. 1A and IB, the user system 110 includes a computing device 116 and/or a portable device 114 on which is executed a method of communicating a paint request to a remote mixing server 140. The user system 110 may further include a router 120, which can be wireless and/or wired, but, without loss of generality, FIG. 1 A illustrates a non-limiting example of a wireless router 120 (c.g., a WIFI router or a router using BLUETOOTH or Near Field Communication (NFC) technology). The system 110 can be an internet of things (loT), for example. The user system 110 may further include a user scale 130 and a sensor box 132. Additionally, the user system 110 may include an asset 102 (e.g., an automobile that is to be repaired and/or repainted or partially repainted) and a spectrophotometer 112.
[0022] The sensor box 132 includes a physical enclosure enclosing the sensor box 132. Placing the components of the sensor box 132 within the physical enclosure allows the components to operate within an environment where painting spray may otherwise interfere with the electronics. In the non-limiting example depicted in FIGs. 1A and IB, the user scale 130 can be a separate device that can be external to the sensor box 132. This separation allows the user scale 130 to be retrofit with the sensor box 132 such that the user scale 130 gains potentially new features provided by the sensor box 132.
[0023] The sensor box 132 may include a local communication interface 134 configured to receive a physical connector from the user scale 130. In the depicted example, the local communication interface 134, which may include a serial port, but one will appreciate that any number of different types of local communication interfaces 134 may be used. For example, the local communication interface 134 may comprise a universal serial bus (USB), a parallel port, a SPT port, or any other type of physical port. Although the disclosure refers to “a serial port”, “a USB” “a parallel port”, “ SPI port”, etc. it should be appreciated that any number and combination of these ports or similar ports may be used according to the present disclosure .
[0024] In various examples, the user scale 130 may be either an analog scale or a digital scale, or a combination thereof. Further in various examples, the user scale 130 lacks a hardware network interface, such that the user scale 130 is not equipped with hardware and/or software to communicate over a network connection. As such, in some examples, the user scale 130 is able to communicate with the remote server 180 through the sensor box 132.
[0025] The sensor box 132 also may include a network communication interface 136 configured to communicate with an internet gateway. The network communication interface 136 is depicted as an Ethernet port, but may comprise another data/connection port, including, e.g., any connection capable of network communications, such as but not limited to, a WIFI network interface or a BLUETOOTH network interface. The internet gateway may include a router, a modem, or any other conventional network gateway device. The sensor box 132 may communicate with the wireless router 120 or with the network 150 through an internet gateway.
[0026] The sensor box 132 includes a sensor 138. The sensor 138 is shown with dashed lines to indicate that the sensor may be visible on the sensor box 132 or that it may be integrated within the physical enclosure of the sensor box 132. The sensor 138 may comprise a climate sensor such as a temperature sensor, a humidity sensor, a pressure sensor, an altimeter, a locationdetection antenna (e.g., a GPS radio), and/or any other sensor capable of providing climate data describing an aspect of a physical environment around the user system 110. Thus, while the sensor 138 is singular, it should be appreciated that in some examples, the sensor 138 includes a plurality of sensors of including some sensors of different types. Additionally, in some examples, the sensor 138 comprises an interchangeable hardware slot that can be configured to receive a plurality of different sensor types. Accordingly, the sensor 138 can be modular such that different sensors and different types of sensors can be added or removed from the sensor box 132.
[0027] In a coating, various layers of the coating (e.g., the paint layer, the under (base) coat layer, the over (clear) coat layer, or the sealing layer) may be sensitive to the local environment conditions. For example, to avoid a clear coat having a cloudy appearance, a certain ratio of solvent to solute may be required, which ratio depends on local temperature and humidity. As another example, a recipe for a given layer may change depending on the local conditions. The local conditions are measured by the sensor box 132 at the location of the user system 110 because that is the location at which the coatings will be applied to the asset 102, which dictates the desired recipe for the layers. Thus, in some examples, geographic information for a user may be pertinent to a recipe mixed a remote location. For example, a user geographic location may be located at least 20 km from a remote mixing location. Alternatively or additionally, the user geographic location may have a temperature, humidity, barometric pressure, etc. that is different by a predetermined about from the remote location where a recipe is mixed.
[0028] The sensor box 132 may include a processor configured to process data received from the user scale 130 and the sensor 138. The sensor box 132 further includes a first computer- readable media having stored thereon executable instructions that when executed by the processor configure the sensor box 132 to perform various acts. For example, the sensor box 132 receives, through the local communication interface 134, a mass variable from the user scale 130. The mass variable provides a mass of a coating mixture resting on the user scale 130. The sensor box 132 also receives, from the sensor 138, a sensor variable. The sensor variable provides data describing an aspect of a physical environment around the coating mixture. For example, the sensor variable may comprise an ambient temperature, a humidity level, an atmospheric pressure, an altitude, a geographic location (from the location-detection antenna or from an IP address localization), and/or any other data pertinent to the physical environment around the coating mixture. Accordingly, the sensor variable may provide a humidity reading from the physical environment around the coating mixture and a temperature reading from the physical environment around the coating mixture.
[0029] Returning to FIG. 1A, the remote mixing server 140 includes a computing device 146, a computer readable memory storage 144, and a distributor scale 142. The server 180 includes a processor 184, a computer readable memory storage 182, and a matching engine 186. The user system 110, the remote mixing server 140, and the server 180 communicate with each other via the network 150. The remote mixing server 140 receives information regarding a layer composition to be applied to the asset 102 and mixes/generates the layer composition in a specified quantity. The server 180 can be a cloud-based system, for example, and the server 180 determines the recipes for the layer composition (e.g., which colorants and quantities thereof to add to a paint to match a color of the asset 102). The server 180 can use distributed computing or can use localized computing, such as being localized, c.g., at the remote mixing server 140.
[0030] In some examples, the server 180 can be pail of, or hosts a cloud-based service. In some examples, the server 180 may host subscription services for the user system 110. A user at the user system 110 can log in to a subscription service hosted by the server 180 by providing login credentials through a user interface. In some examples, the subscription service includes an option for a remote paint distributor that is operating a remote mixing server to both deliver the requested order and to retrieve from the user any waste or packaging upon completion of refinishing the vehicle to be repaired.
[0031] In the non-limiting example, illustrated in FIG. 1A both the user system 110 includes a user scale 130 and the remote mixing server 140 includes a distributor scale 142 because some coating compositions are generated using the user scale 130 of the user system 110 and other coating compositions are generated using the distributor scale 142 of the remote mixing server 140. According to one example, compositions (e.g., the paint layer) are generated at the remote mixing server 140 and volatile coating compositions are generated by the user system 110. This example can be efficient because volatile coating compositions require relatively few ingredients/constituents, whereas inventories of many colorants may be used to match the many possible paint colors of various assets.
[0032] According to another example, the coating compositions may be generated and supplied by the remote mixing server 140. In this case, the user scale 130 may be no longer needed in the user system 110 and therefore the user scale 130 may be omitted.
[0033] According to one non-limiting example, the asset 102 has been coated with a target coating. In some cases, an undercoat has been applied to the asset 102 as well. In any event, it is often desirable to identify that target coating, or to identify a best-fit match for the coating (aka best potential match). For example, it may be the case that the asset 102 was involved in an accident and taken to an autobody shop, which may be a “remote facility” corresponding to the user system 110. The owner of the asset 102 may want the shop to paint the wrecked areas of the asset 102 with the same coating as the other areas to maintain consistency across the asset 102. To do so, the shop will be tasked with identifying that target coating.
[0034] The user system 110 generates spectrometric data of the target coating (e.g., using the spectrophotometer 112 or using a camera on the portable device 114). The spectrometric data may be gathered by a camera, a spectrometer, such as spectrophotometer, or any other device capable of scanning the target coating on the asset 102 and providing characterization data relating to attributes of the target coating. The spectrometric data can comprise spectrophotometric data, spectrocolorimetric data, data acquired via image processing, and/or any other similar data. The server 180 can process the spectrometric data through a probabilistic colorant analysis. The probabilistic colorant analysis identifies a set of colorants that are likely present in the coating and associates with each colorant a probability that the colorant is present in the target coating. Based on these results, a formulation for a best fit coating may be identified
[0035] Sometimes a spray out or “test coating” is generated for the identified formulation and spectrocolorimetric data can be taken of the “test coating” to confirm it matches the target coating on the asset 102. If not, the identified formulation can be tweaked. Often the probabilistic colorant analysis can be sufficient to generate a color match and corresponding recipe without the additional step of generating a “test coating.”
[0036] As used herein, colorants include absorption and scattering pigments, effect pigments, and/or any other related coating or coating component.
[0037] In this sense, the disclosed server 180 can analytically identify potential colorants within the target coating. As used herein, “potential colorants” are colorants that are identified by a probabilistic colorant analysis as likely being in the target coating. The potential colorants are fed into a formulation or analysis engine that can be seeded with colorants that have already been identified as having a high probability of being present within the target coating.
[0038] Any number of potential formulations may be identified by the server 180. Often, the potential formulations can be ranked based on how closely they correspond, align, or match with the target coating. In response to identifying the potential formulations, a skilled user is able to review the coatings in a user interface and make a selection regarding which coating the user thinks most closely aligns with the target coating.
[0039] A selected potential formulation can be referred to as a “test coating.” That is, the test coating can be a coating that can be a selected potential formulation. If a spray out is needed to verify the coating color for a given formulation, then the given formulation may be applied to another asset, for example, at the remote facility. This other asset can be a test surface used for application purposes to gauge how the given formulation can be applied and cured. Once the test coating cures, it can be analyzed using the techniques mentioned earlier, e.g., using a spectrophotometer such as spectrophotometer 1 12. In any event, the test coating can then be compared against the target coating of the asset 102 to determine whether a true alignment exists between those two coatings. If the test coating is not satisfactorily aligned with the target coating, then an adjustment to the coating attributes of the test coating can be performed in an attempt to bring the test coating into a matched state relative to the target coating.
[0040] The server 180 identifies a best fit match to a target coating. According to one nonlimiting example, the server 180 receives color data from a spectrophotometer 112 and identifies therefrom a best fit match. The server 180 can then generate rendering data and formulation data, which can be transmitted to the user system and distributor, for example. The computing device 116 and/or the portable device 114 can visually display a selected number of coatings that potentially match with the target coating. A user can review these so-called “best fit coatings” and can select one for further testing and analysis, such as by applying it to an asset and then obtaining coating attributes for the applied coating.
[0041] The server 180 may include a processor 184 and a matching engine 186. The server 180 may include a computer-readable hardware storage device, such as storage 182. The storage 182 includes instructions that are executable by a processor 184 to configure the server 180 to perform any number of operations, such as the methods discussed below. In some cases, the computer server 180 also includes or has access to a matching engine 186. The server 180 can be also able to communicate with remote devices via the network 150 (e.g., the Internet).
[0042] The spectrophotometer 112 can be used to identify coating attributes (e.g., colorimeter data and/or reflectance characteristics, which can then be used to infer color attributes) for both the target coating and the new coating applied to the asset 102. As an example, the coating attributes can include color formula component information, which can be inferred based on the reflectance data obtained by the spectrophotometer 112. A mapping or prediction process can be available to correlate reflectance with known color formula information. The color formula component information can include various information on pigments (e.g., XIRALLIC, gonioapparent pigment, metallic flake, mica, pearlescent pigments, and the like), multiple coating layer information (e.g., tricoat, XIRALLIC), various physical or raw data measured for each coating sub-component, such as spectral, colorimetric, or other data for various tints, base coats, and effect pigments, including such data as measured from various combinations of such sub- components. The coating attributes can include predicted spectral or colorimetric data for given formulas where actual measurements have not yet been performed.
[0043] As indicated above, the coating attributes can include raw physical measurements and/or predicted measurements, such as spectral, and/or other colorimetric measurements including but not limited to CIELab (i.e., L*a*b*) values, spectrophotometer reads, RGB, and gamma- RGB values, and/or XYZ tristimulus data, etc. for each coating, and each coating subcomponent. In some cases, the coating attributes include data detailing a mixture of raw physical measurements for a number of coatings and coating sub-components, and predicted physical measurements for other coatings or coating sub-components based on measurements taken from adjacent colors, such as colors in the same color space, but perhaps differing by a sub-component (e.g., different base), or differing by slight changes in hue, chroma, or toner ratio. In some cases, the coating attributes can also include barcode, VIN, or QR code data.
[0044] The coating information may include information relating to how a coating can be applied to an asset. For instance, the information can include which tools are used, how the coating can be cured, under what environmental conditions the coating can be applied and allowed to cure, and so on. That is, the coating information may include environmental data detailing the environmental conditions that exist when a coating is applied and allowed to cure. Such environment data can include temperature, atmospheric pressure, elevation, humidity, time of day, season of the year, and so forth.
[0045] The storage 182 may store secondary indicia associated with each color and color formulation. For example, the storage 182 can store barcode, QR code, and/or VIN (vehicle identification number) data associated with each color record, which may enable an end user to scan the corresponding code on the asset itself, and then enable the user to pull the record for the original color as stored by the storage 182. Pulling the full record for the original color can indicate components/ingredients/layers, and other parameters known regarding the original coating application. The storage 182 may also serve as a central repository for the most recent updates of a coating manufacturer's colors, color names, and related physical data, such as formula, spectral, colorimetric, RGB, CIELAB (i.e., L*a*b*), and/or XYZ tristimulus data and related conversion data, as well as image data, for each color and corresponding color sub-component used to make a particular coating. [0046] The storage 182 may also, for example, coordinate with a database of an asset (e.g., auto) manufacturers (which may or may not be the coating manufacturer). This coordination can ensure the cloud color manager can be able to regularly obtain similar formula, spectral, colorimetric, RGB, CIELAB (i.e., L*a*b*), and/or XYZ tristimulus values (and related conversions) for each color used to coat the assets by the asset manufacturer as they are applied each year. The secondary and physical data corresponding to each color can be used to retrieve color matches as described more fully herein. For purposes of this specification and claims, "primary color data" refers to the color name or color code used to identify a particular coating, namely human readable labels that an end user might use to identify a color or color profile, such as Midnight Blue. Meanwhile, "secondary color data" refers to inherent physical characteristic data and machine-readable data other than express color name or color code, such as barcode, QR code, or physical characteristic data associated with a particular coating. Physical characteristic data can include spectral reflectance data, colorimeter data, CIELAB values, RGB values, and so forth.
[0047] As shown in FIG. 1 A, the color data can be obtained using the spectrophotometer 112 and/or an imaging device, such as a camera on the portable device 114, which may be a tablet computer or smartphone, for example. The server 180 receives the color data (or indicia/information representing the color data). The server 180 can use a matching engine 186 to perform a number of analyses of the image, spectral, and/or colorimetric data received to identify relevant, closest color matches among colors stored in storage 182. For example, matching engine 186 can identify that barcode information received in color data identifies a particular color from a particular make, model, and year of an automobile, and further identify from information in the storage 182 which particular undercoat(s) and pigment effects were used in the formula for that particular color record.
[0048] Similarly, matching engine 186 can determine that the original coating identified in the color data is not one created by a known paint manufacturer stored in the storage 182, but that several other colors that have similar secondary color data by comparison of physical characteristics, such as similar spectral, CIELab, and/or XYZ tristimulus value matches. Matching engine 186 can then gather those color records that match or otherwise fit within an acceptable range of deviation from the actual measurement (e.g., by computing a z-score of the measured color relative to a group of colors with similar physical measurements), and provide that as a response for further user input. The server 180 can then send a response back to the user system 110 and/or remote mixing server 140 in the form of a color match message. For example, rendering data and color data of the potential color match(es) can be sent to the user system 110 to be reviewed by a user, and formulation data of the potential color match(s) can be sent to the remote mixing server 140.
[0049] The server 180 can generate rendering data that represent how the asset 102 would appear with a potential formulation applied to the asset 102. For example, the generated rendering data can instruct the computing device 116 and/or the portable device 114 to render an image of the asset 102 (or a generic version of the asset 102) with the entire asset 102 coated using the potential formulation or with just the damaged/repaired portion of the asset 102 coated using the potential formulation. A user can select the potential formulation for comparison to select the best option.
[0050] FIGs. 2A-2D illustrate a user interface 300 that can be displayed on a display of the computing device 116 and/or the portable device 114. A user of the user system 110 interacts with the user interface 300 to enter information for a desired coating composition. For example, the user can enter details for the vehicle data 310 including, e.g., year, make, and model information 312 and a vehicle identification number 314. This information can be used to identify sizes of various panels.
[0051] The user can interact with the user interface 300 to enter and/or edit information for location data 320 including, e.g., historical and preference data 322 and sensor data 324 for the sensor box 132. The historical and preference data 322 can represent user preferences. For example, a user may prefer to request 20% more than a recommended quantity of the coating composition to provide a safety margin that ensures adequate material to complete a repainting/repair job. Such a preference can be stored and associated with the user as a default. Using the user interface 300, the user can edit this preference if a different safety margin is desired for a current job.
[0052] Additionally, the user can enter information for the measured data 330 including, e.g., spectrophotometric data 332 acquired using the spectrophotometer and/or image data 334 (e.g., acquired using a camera of the portable device 114).
[0053] The user interface 300 can also include a graphical user interface (GUI) 340 for receiving user input selecting a part of the asset 102 being repaired. For example, in FIG. 2A, an asset 102 can be represented in a representation of the asset using an exploded view of the body panels, doors, and bumpers: none of the sections arc selected by a user. A user can, c.g., hover a mouse cursor over a given part and click to select the given part. For example, in FIG. 2B, a driverside door panel has been selected. If a given part is not visible in the GUI 346, a user can rotate the rendering of the asset 102 until the desired part becomes visible. In FIGs. 2C and 2D, the respective parts of the asset 102 are illustrated such that the pails are simultaneously visible in the GUI 340. In FIG. 2C, no parts have been selected, and, in FIG. 2D, a driver-side door panel has been selected.
[0054] FIG. 3 illustrates an example of the user interface 300 when finalizing an order. The GUI 370 shows a rendering of the coated asset. In this example, N potential formulations are identified (i.e., #1 potential formulation 372, #2 potential formulation 374, ... #N potential formulation 376). A user can select which of these potential formulations they want to visualize, and the GUI 370 will display a rendering of the asset with the selected portion rendered to look like the selected potential formulation.
[0055] The user interface 300 can display information 341 of the selected formulations, including, e.g., the colorants 342 and their respective quantities 344. Additionally or alternatively, the formulation information 341 can include an estimate of a quantity of the coating composition required to coat the selected part and an estimate of the cost.
[0056] The user interface 300 can display finishing materials information 350 including, e.g., recommended amounts of consumables, such as tape, sealant, adhesives, and/or abrasives for the repainting/repair job. These recommended consumables may include coating components 352 (e.g., examples of coating components may include an over coat, an under coat, a primer coat, or a clear coat) abrasives 354 (e.g., sandpaper), and masking tape.
[0057] The user interface 300 can display other instructions 360 including, e.g., waste management instructions 362 and application instructions 364. For example, expense and waste can be reduced by using reusable containers to transport and hold the coating composition and the coating components 352. The waste management instructions 362 can direct the user how to handle and return the reusable containers to a distributor. The application instructions 364 can direct a user regarding the proper conditions for applying coating composition and desirable environmental condition for curing the coating composition, for example. [0058] FIG. 4 shows a flow diagram of a client method 400. Method 400 can be performed using a user system 110 to request delivery of a coating composition. In step 410, a user interface 300 can be displayed on a digital device (e.g., the computing device 116 or the portable device 114).
[0059] In step 420, the digital device receives user inputs through the user interface 300, and the digital device creates therefrom a record for an asset (e.g., a vehicle) to be refinished. The received data can include the vehicle data 310 and can include location data 320 (e.g., preference data 322).
[0060] In step 430, color data can be received to indicate a color of the asset 102. For example, the color data may be measured using the spectrophotometer 112, and/or the color data may be acquired using an imaging device, such as a camera of the portable device 114. The color data may include the measured data 330.
[0061] The received data on the digital device, including the color data and the user inputs, are transmitted to a matching engine (e.g., the matching engine 186 on the server 180). Based on the color data (and possibly the user inputs) the matching engine determines a proposed color match. The proposed color match can be based on the measured data, vehicle data, location information, age of the vehicle and/or other information. In some examples, the matching engine 186 may implement machine learning algorithms to determine the color match. While “a proposed color match” is described here, it should be appreciated that in some examples multiple proposed color matches may be generated. Thus, as used herein, “a proposed color match” should not be interpreted as limiting to only a single proposed color match.
[0062] In optional step 440, the user interface 300 displays the color match(es). In some example, N potential formulations that are identified as #1 potential formulation 372, #2 potential formulation 374, ... #N potential formulation 376). The user interface 300 may also display three- dimensional rendering of the proposed color match(es).
[0063] In optional step 450, the user uses the user interface 300 to select a proposed color match.
[0064] In step 460, the user uses the user interface 300 to select a part of the asset 102 to be repainted/refinished. Using the selection of a part to be refinished and using the vehicle data 310, a surface area can be calculated for the part to be refinished. Based on this surface area, a quantity of coating composition can be determined. Additionally or alternatively, a look-up-table may directly provide the quantity of coating composition for the part to be refinished based on the vehicle data 310 without calculating the surface area to be refinished. The desired quantity of the coating composition can be adjusted up or down, depending on the user’s preferences (e.g., safety margin).
[0065] In step 470, a mix order can be sent to the remote mixing server 140 for a coating composition corresponding to a selected proposed color match and the desired quantity. The mix order may include various other items, such as consumable materials, that are used in the refinishing job.
[0066] FIG. 5 illustrates a server method 500 that can be performed by the remote mixing server 140 and/or the server 180. The remote mixing server 140 and the server 180 may be collocated. Alternatively, the server 180 may be a cloud-based application. The server 180 may perform the steps of method 500, and, then once the order is finalized, the server 180 can send the mix order to the distributor for mixing of the coating composition.
[0067] In step 510, a server 180 sends display instructions to a client (e.g., the user system 110) requesting user input. The requested user input can include the vehicle data 310, for example, which can be entered by the user interacting with the user interface 300.
[0068] In step 520, the requested user input can be received at the server 180 from the client, and a record can be created/ received by the server 180.
[0069] In step 530, the server 180 receives from the client color data (e.g., the measured data 330).
[0070] In step 540, the server 180 determines a proposed color match or a plurality of proposed color matches based on the received color data from the client. Optionally, the proposed color match(es) is/are sent to the client together with optional rendering data. In certain examples the rendering data can be generated at the server 180, and in other examples the rendering data can be generated at user system 110 based on the information of the proposed color match(es). After sending the proposed color match(es), the server 180 awaits a selection from the client of one of the proposed color match(es). Note that in other examples, the server 180 may simply determine a color match without providing the user an opportunity to select a proposed color match. This can be based on the measured data, vehicle data, location information, age of the vehicle and/or other information. In some examples, the server 180 may implement machine learning algorithms to determine the color match. [0071] In step 550, the server 180 optionally receives information indicating the selected one of the proposed color match(cs). The server 180 receives information indicating the selected part of the asset 102 that is to be refinished.
[0072] In step 560, the server 180 receives from the client a mix order and communicates the mix order to the remote mixing server 140, which fulfills the mix order.
[0073] While the present disclosure provides descriptions of various specific elements and configurations for the purpose of illustrating various aspects of the present disclosure and/or its potential applications, it is understood that variations and modifications will occur to those skilled in the art. Accordingly, the present disclosure herein should be understood to be at least as broad as claimed and not as more narrowly defined by particular illustrative aspects provided herein.
[0074] One will appreciate, therefore, that the present disclosure can be described in terms of various configurations. For example, in at least one configuration a computerized method of receiving on-demand coatings delivered from a remote location includes displaying a user interface on a digital display of a digital device being accessed by a user at a geographic location. The method includes receiving, through the user interface, user input that creates a record for a vehicle to be refinished, wherein the record identifies details concerning the vehicle. The method includes receiving from a digital color measurement device spectrophotometric data and image data corresponding to the vehicle. The method includes displaying a representation of the vehicle in the form of a plurality of selectable vehicle parts to be refinished, and receiving user input at the user interface to select a vehicle part. The method includes, sending to a remote mixing server in a different geographic location a requested order to mix an amount that reflects a quantity of coating calculated for the selected a vehicle part a coating color of the coating being based on an identified color match identified based on the spectrophotometric data.
[0075] In an additional or alternative configuration, the method includes receiving a message from the remote mixing server that confirms mixing of the requested order, and delivery details. Additionally or alternatively, the method includes causing, via the digital device, the quantity of the coating to be mixed based on the selected selectable part. Furthermore, in an additional or alternative configuration, the method includes identifying, via the digital device, from the calculated quantity, an amount of additional finishing materials to include with the coating to be mixed; wherein the finishing materials include an outer layer or clear coat and corresponding amount thereof that is calculated based on data taken from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished. Still further, in an additional or alternative configuration, the method includes the additional finishing materials further comprise tape, sealant, adhesives, or abrasives.
[0076] According to another configuration of the present disclosures, the method includes displaying application instructions. In an additional or alternative configuration,
[0077] the method can further includes receiving climate data from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished. In still another or alternative configuration, the method includes storing the requested order in a cloud server that is remote from the geographic location of the user and the geographic location of the remote mixing server. According to another or alternative configuration, the method includes providing login credentials through the user interface; wherein the login credentials are associated with a subscription service.
[0078]
In a still further configuration, the method includes the subscription service includes an option for a remote paint distributor that is operating the remote mixing server to both deliver the requested order and to retrieve from the user any waste or packaging upon completion of refinishing the vehicle to be repaired. According to another example of the present disclosures, the method includes displaying a plurality of proposed color matches on the digital display, wherein the proposed color matches enable comparison through the digital display of the image data against the plurality of proposed color matches, and wherein the coating color of the coating being based on user selection in the user interface of one of the proposed color matches. In an additional or alternative configuration, the method includes the coating color of the coating is based on the remote mixing server using the spectrophotometric data selecting a coating color. According to another example of the present disclosures, a digital device, includes a storage storing executable instructions; a display configured to display a user interface; and a processor configured to execute the executable instructions, wherein executing the executable instructions on the processor causes the digital device to perform method according to any of the preceding methods.
[0079] Still further or additional configurations can include, at a remote server computer, a computerized method of providing on-demand coatings to a remote location based on vehicle and location specific data specified at the remote location is disclosed. The method includes sending display instructions for display of a user interface to a remote client computer system being accessed by a user at a geographic location. The method includes receiving from the client computer system user input that creates a record for a vehicle to be refinished, wherein the record identifies the vehicle by a year, make, and model. The method includes receiving from the client computer system digital color measurement device spectrophotometric data and image data corresponding to the vehicle to be refinished. The method includes based on the spectrophotometric data, identifying a color match corresponding to the vehicle to be refinished. The method includes sending display instructions of the vehicle in the form of a plurality of selectable vehicle pails to be refinished, and receiving user selection of a vehicle part through the user interface; and in response to the selection of the vehicle part, instructing a mixing device to mix a requested order comprising the color match and a quantity of coating calculated for the selected vehicle part.
[0080] In an additional or alternative configuration, the method of a computerized method of providing on-demand coatings to a remote location based on vehicle and location specific data specified at the remote location includes sending a message to the remote client computer that confirms mixing of the requested order, and delivery details. In an additional or alternative configuration, the method of a computerized method of providing on-demand coatings to a remote location based on vehicle and location specific data specified at the remote location includes causing the quantity of the coating to be mixed based on the selected selectable part. According to another or alternative configuration, the method of a computerized method of providing on- demand coatings to a remote location based on vehicle and location specific data specified at the remote location, or any associated methods includes identifying from the calculated quantity, an amount of additional finishing materials to include with the coating to be mixed; wherein the finishing materials include an outer layer or clear coat and corresponding amount thereof that is calculated based on data taken from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished.
[0081] In additional or alternative configurations, the method providing the additional finishing materials further comprising tape, sealant, adhesives, or abrasives. In additional or alternative configurations, the method further includes sending application instructions to the remote client computer system. Furthermore, in additional or alternative configurations, the methods includes receiving climate data from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished. [0082] Yet still further, in another configuration, the method can include storing the requested order in a cloud server that is remote from the geographic location of the user and the geographic location of the remote server computer. In additional or alternative configurations, the method can include sending a plurality of proposed color matches to the remote client computer system for display at the remote client computer system, and wherein the coating color of the coating being based on user selection of one of the proposed color matches. Furthermore, in additional or alternative configurations, the methods includes the coating color of the coating being based on the remote mixing server using the spectrophotometric data selecting a coating color.
[0083] The following discussion is intended to provide a brief, general description of a suitable computing environment in which the present disclosure may be implemented. Although not required, the present disclosure will be described in the general context of computer-executable instructions, such as program modules, being executed by computers in network environments. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Computer-executable instructions, associated data structures, and program modules represent examples of the program code means for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps.
[0084] Those skilled in the art will appreciate that the present disclosure may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. The present disclosure may also be practiced in distributed computing environments where local and remote processing devices perform tasks and are linked (either by hardwired links, wireless links, or by a combination of hardwired or wireless links) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.
[0085] The present disclosure may comprise or utilize a special-purpose or general-purpose computer system that includes computer hardware, such as, for example, a processor and system memory, as discussed in greater detail below. The scope of the present disclosure also includes physical and other computer-readable media for carrying or storing computer-executable instructions and/or data structures. Such computer-readable media can be any available media that can be accessed by a general-purpose or special-purpose computer system. Computer-readable media that store computer-executable instructions and/or data structures are computer storage media. Computer-readable media that carry computer-executable instructions and/or data structures are transmission media. Thus, by way of example, and not limitation, the present disclosure can comprise two distinctly different kinds of computer-readable media: computer storage media and transmission media.
[0086] Computer storage media are physical storage media that store computer-executable instructions and/or data structures. Physical storage media include computer hardware, such as RAM, ROM, EEPROM, solid state drives (“SSDs”), flash memory, phase-change memory (“PCM”), optical disk storage, magnetic disk storage or other magnetic storage devices, or any other hardware storage device(s) which can be used to store program code in the form of computerexecutable instructions or data structures, which can be accessed and executed by a general- purpose or special-purpose computer system to implement the disclosed functionality of the present disclosure.
[0087] Transmission media can include a network and/or data links which can be used to carry program code in the form of computer-executable instructions or data structures, and which can be accessed by a general-purpose or special-purpose computer system. A “network” is defined as data links that enable the transport of electronic data between computer systems and/or modules and/or other electronic devices. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer system, the computer system may view the connection as transmission media. Combinations of the above should also be included within the scope of computer-readable media.
[0088] Further, upon reaching various computer system components, program code in the form of computer-executable instructions or data structures can be transferred automatically from transmission media to computer storage media (or vice versa). For example, computer-executable instructions or data structures received over a network or data link can be buffered in RAM within a network interface module ,and then eventually transferred to computer system RAM and/or to less volatile computer storage media at a computer system. Thus, it should be understood that computer storage media can be included in computer system components that also (or even primarily) utilize transmission media.
[0089] Computer-executable instructions comprise, for example, instructions and data which, when executed at a processor, cause a general-purpose computer system, special-purpose computer system, or special-purpose processing device to perform a certain function or group of functions. Computer-executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, or even source code.
[0090] Those skilled in the ail will appreciate that the present disclosure may be practiced in network computing environments with many types of computer system configurations, including, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, tablets, pagers, routers, switches, and the like. The present disclosure may also be practiced in distributed system environments where local and remote computer systems, which are linked (either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links) through a network, both perform tasks. As such, in a distributed system environment, a computer system may include a plurality of constituent computer systems. In a distributed system environment, program modules may be located in both local and remote memory storage devices.
[0091] Those skilled in the art will also appreciate that the present disclosure may be practiced in a cloud-computing environment. Cloud computing environments may be distributed, although this is not required. When distributed, cloud computing environments may be distributed internationally within an organization and/or have components possessed across multiple organizations. In this description and the following claims, “cloud computing” is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services). The definition of “cloud computing” is not limited to any of the other numerous advantages that can be obtained from such a model when properly deployed.
[0092] A cloud-computing model can be composed of various characteristics, such as on- demand self-service, broad network access, resource pooling, rapid elasticity, measured service, and so forth. A cloud-computing model may also come in the form of various service models such as, for example, Software as a Service (“SaaS”), Platform as a Service (“PaaS”), and Infrastructure as a Service (“laaS”). The cloud-computing model may also be deployed using different deployment models such as private cloud, community cloud, public cloud, hybrid cloud, and so forth.
[0093] A cloud-computing environment, or cloud-computing platform, may comprise a system that includes a host that is capable of running virtual machines. During operation, virtual machines emulate an operational computing system, supporting an operating system and perhaps other applications as well. Each host may include a hypervisor that emulates virtual resources for the virtual machines using physical resources that are abstracted from view of the virtual machines. The hypervisor also provides proper isolation between the virtual machines. Thus, from the perspective of any given virtual machine, the hypervisor provides the illusion that the virtual machine is interfacing with a physical resource, even though the virtual machine interfaces with the appearance (e.g., a virtual resource) of a physical resource. Examples of physical resources including processing capacity, memory, disk space, network bandwidth, media drives, and so forth.
[0094] The present disclosure may be embodied in other specific forms without departing from its spirit or essential characteristics. The described examples are to be considered in all respects only as illustrative and not restrictive. The scope of the present disclosure is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.

Claims (24)

CLAIMS Wc claim:
1. A computerized method of receiving on-demand coatings delivered from a remote location, comprising: displaying a user interface on a digital display of a digital device being accessed by a user at a geographic location; receiving, through the user interface, user input that creates a record for a vehicle to be refinished, wherein the record identifies details concerning the vehicle; receiving from a digital color measurement device spectrophotometric data and image data corresponding to the vehicle; displaying a representation of the vehicle in the form of a plurality of selectable vehicle parts to be refinished, and receiving user input at the user interface to select a vehicle part; and sending to a remote mixing server in a different geographic location a requested order to mix an amount of coating that reflects a quantity of coating calculated for the selected a vehicle part a coating color of the coating being based on an identified color match identified based on the spectrophotometric data.
2. The method as recited in claim 1, further comprising: receiving a message from the remote mixing server that confirms mixing of the requested order, and delivery details.
3. The method as recited in any of the preceding claims, further comprising: causing, via the digital device, the quantity of the coating to be mixed based on the selected selectable part.
4. The method as recited in claim 3, further comprising: identifying, via the digital device, from the calculated quantity, an amount of additional finishing materials to include with the coating to be mixed; wherein the finishing materials include an outer layer or clear coat and corresponding amount thereof that is calculated based on data taken from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be rcfinishcd.
5. The method as recited in claim 4, wherein: the additional finishing materials further comprise tape, sealant, adhesives, or abrasives.
6. The method as recited in any of the preceding claims 4 through 5, further comprising: displaying application instructions.
7. The method as recited in any of the preceding claims, further comprising: receiving climate data from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished; and wherein mixing an amount of coating is performed based on the climate data.
8. The method as recited in any of the preceding claims, further comprising: further comprising storing the requested order in a cloud server that is remote from the geographic location of the user and the geographic location of the remote mixing server.
9. The method as recited in any of the preceding claims, further comprising: providing login credentials through the user interface; wherein the login credentials are associated with a subscription service.
10. The method as recited in claim 9, further comprising: wherein the subscription service includes an option for a remote paint distributor that is operating the remote mixing server to both deliver the requested order and to retrieve from the user any waste or packaging upon completion of refinishing the vehicle to be repaired.
1 1 . The method as recited in any of the preceding claims, further comprising displaying a plurality of proposed color matches on the digital display, wherein the proposed color matches enable comparison through the digital display of the image data against the plurality of proposed color matches, and wherein the coating color of the coating being based on user selection in the user interface of one of the proposed color matches.
12. The method as recited in any of the preceding claims, wherein the coating color of the coating is based on the remote mixing server using the spectrophotometric data to select a coating color.
13. The method as recited in claim 1, further comprising: coating the selected vehicle part with the coating at the geographic location.
14. A digital device, comprising: a storage storing executable instructions; a display configured to display a user interface; and a processor configured to execute the executable instructions, wherein executing the executable instructions on the processor causes the digital device to perform method according to any of the preceding claims.
15. At a remote server computer, a computerized method of providing on-demand coatings to a remote location based on vehicle and location specific data specified at the remote location, comprising: sending display instructions for display of a user interface to a remote client computer system being accessed by a user at a geographic location; receiving from the client computer system user input that creates a record for a vehicle to be refinished, wherein the record identifies the vehicle by a year, make, and model; receiving from the client computer system digital color measurement device spectrophotometric data and image data corresponding to the vehicle to be refinished; based on the spectrophotometric data, identifying a color match corresponding to the vehicle to be refinished; sending display instructions of the vehicle in the form of a plurality of selectable vehicle parts to be refinished, and receiving user selection of a vehicle part through the user interface; and in response to the selection of the vehicle part, instructing a mixing device to mix a requested order comprising the color match and a quantity of coating calculated for the selected vehicle part.
16. The method as recited in claim 15, further comprising: sending a message to the remote client computer that confirms mixing of the requested order, and delivery details.
17. The method as recited in any of the preceding claims 15 through 16, further comprising:
Causing the quantity of the coating to be mixed based on the selected selectable part.
18. The method as recited in claim 17, further comprising:
Identifying from the calculated quantity, an amount of additional finishing materials to include with the coating to be mixed; wherein the finishing materials include an outer layer or clear coat and corresponding amount thereof that is calculated based on data taken from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished.
19. The method as recited in claim 18, wherein: the additional finishing materials further comprise tape, sealant, adhesives, or abrasives.
20. The method as recited in any of the preceding claims 18-19, further comprising: sending application instructions to the remote client computer system.
21. The method as recited in any of the preceding claims 15 through 20, further comprising: receiving climate data from a climate sensor, wherein the climate data comprises data taken from a location where the vehicle is to be refinished and wherein mixing the requested order is performed based on the climate data.
22. The method as recited in any of the preceding claims 15 through 21, further comprising: further comprising storing the requested order in a cloud server that is remote from the geographic location of the user and the geographic location of the remote server computer.
23. The method as recited in any of the preceding claims 15 through 22, further comprising sending a plurality of proposed color matches to the remote client computer system for display at the remote client computer system, and wherein the coating color of the coating being based on user selection of one of the proposed color matches.
24. The method as recited in any of the preceding claims 15 through 23, wherein the coating color of the coating is based on the remote mixing server using the spectrophotometric data selecting a coating color.
PCT/US2024/027134 2023-05-05 2024-05-01 Method and apparatus for providing on demand paint mixing components from a remote location WO2024233203A1 (en)

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