APPLICATIONS OF IOT IN MAINTENANCE

MANAGEMENT
 INTRODUCTION

Internet of Things (IOT):

The Internet of Things is the concept of connecting any device (so long as it has an
on/off switch) to the Internet and to other connected devices. The IoT is a giant network
of connected things and people – all of which collect and share data about the way they
are used and about the environment around them.
That includes an extraordinary number of objects of all shapes and sizes – from smart
microwaves, which automatically cook your food for the right length of time, to self-
driving cars, whose complex sensors detect objects in their path, to wearable fitness
devices that measure your heart rate and the number of steps you’ve taken that day,
then use that information to suggest exercise plans tailored to you.

Devices and objects with built in sensors are connected to an Internet of Things
platform, which integrates data from the different devices and applies analytics to share
the most valuable information with applications built to address specific needs.
These powerful IoT platforms can pinpoint exactly what information is useful and what
can safely be ignored. This information can be used to detect patterns, make
recommendations, and detect possible problems before they occur.

Maintenance Management:
Maintenance is a set of organised activities that are carried out in order to keep an item
in its best operational condition with minimum cost acquired.Activities of maintenance
function could be either repair or replacement activities, which are necessary for an item
to reach its acceptable productivity condition and these activities, should be carried out
with a minimum possible cost.
Maintenance management is all about maintaining the resources of the company so
that production proceeds effectively and that no money is wasted on inefficiency. There
are many software programs that assist with this process, and there are a few
objectives that a maintenance manager should seek to accomplish. These objectives
are to control costs, to schedule work properly and efficiently, and to ensure that the
company complies with all regulations.
Maintenance management is very important in a company. In fact, it partially determines
the long-term success of the company because poorly maintained resources can bring
operations to a halt, and could cause the company to lose money.
For maintenance implications, the IoT uses sensors and connected devices across the
industry to easily track key performance indicators (KPIs) and control machines. We’re
left with access to accurate, real-time data to make the smartest maintenance
decisions.
Furthermore, the IoT has the power to completely transform the industry through
proactive maintenance strategies. For instance, with the help of IoT sensors and data
gathering, maintenance managers are able to better predict when a breakdown will
occur based on historic records and past service requests. A more proactive
maintenance strategy means less equipment downtime, fewer emergency work order
requests and better budget planning.
IOT IN MAINTENANCE MANAGEMENT :

IoT/CPS technologies can enable the design and devel- opment of advanced monitoring
strategies and thus maintenance policies by adding additional monitoring capabilities to
industrial machines and equipment providing in such a way the following functionalities:

● Integration of secondary processes within the main control: IoT based

technologies can be deployed in order to provide more data about machine and
equipment during their operation. Such information can be used to model the
machine/equipment behavior for the sake of failures/breakdowns detection;
● Modernization of low-tech production systems: IoT based tech- nologies can
be deployed in low-tech production processes, i.e. produc- tion processes that
are not natively ready for industry 4.0, and make them industry 4.0 compatible.
 ● IT/OT Integration: IoT technologies can easily provide data to all the layers of
the automation pyramid enabling a true cross-layer integration.
● Maintenance engagement: IoT technologies can enable a better engagement of
the maintenance department in the health of the overall production system.

IOT IN TOTAL PRODUCTIVE MAINTENANCE

APPAREL INDUSTRY

IOT based Preventive Maintenance Strategies

Managers can depend on sensors to track certain KPIs and gather the best hard data
like average technician response times, average length of downtime or technician
efficiency into their preventive maintenance schedule with the help of the IoT. Try
embedding sensors on devices to track abnormal conditions. From there, generate
alerts when unscheduled downtime is approaching to implement an easy preventive
maintenance schedule.

● Identifying bottlenecks in the operations:With the real-time data about the

location and the quantity of the inventory items, manufacturers can reveal
bottlenecks in the manufacturing process and pinpoint machines with lower
utilization rates. For instance, if part of the inventory tends to pile up in front of a
machine, a manufacturer assumes that the machine is underutilized and needs
to be seen to.

● Lead time optimization:By providing inventory managers with the data about
the amount of available inventory and machine learning-driven demand
forecasts, solutions based on IIoT allow manufacturers to reduce lead times.
Here is an example: a RFID-based inventory management solution allowed Zara
to take a garment from design through the manufacturing process to a smart
warehouse in just 10 days.Factory visibility: IoT network connect what’s
happening on the factory floor to enterprise-based systems and decision makers.
IoT provides production line information to decision makers and improve factory
efficiency. The benefits of visibility will extend beyond the enterprise to a wide
range of suppliers and third party providers of services, consumables and capital
goods.
 ● Automation:Once machinery and systems are connected within the plant,
manufacturers can use this information to automate workflows to maintain and
optimize production systems without human intervention. The software can
automatically adjust the machinery if it detects that a measurement has deviated
from acceptable ranges.
● Energy management:In many industries, energy is frequently the second
largest operating cost. But many companies lack cost effective measurement
systems and modelling tools and/or performance and management tools to
optimize energy use in individual production operations, much less in real-time
across multiple operations, facilities, or an entire supply chain.

IOT-Predictive Maintenance
Manufacturers that implement IoT and predictive maintenance garner a number of
benefits, depending upon need and application. Benefits may include:

● Reduced unscheduled downtime: Avoid costly equipment failures and

unscheduled down time. Proactively address issues before they become
problems that significantly impact operations.
● Increased quality: Improve products and processes through machine-learning
and detect maintenance issues early to increase customer satisfaction.
● Decreased costs: Lower maintenance costs and extend equipment life.
● Greater efficiency and output: Increase process efficiency, asset utilization,
and production output.

Examples of IoT-enabled predictive maintenance

For a great example of how IoT-enabled predictive maintenance can transform
business, let’s look at a steel manufacturer with multiple plants in India. Each plant has
multiple arc furnaces that use water cooling panels for temperature control. However,
leakages in the panels were causing safety issues as well as production losses. To
resolve this issue, the manufacturer worked with Happiest Minds (a Microsoft partner) to
build an Azure-based IoT solution that remotely monitors the panels, detects anomalies,
and performs root-cause analysis. The implementation of predictive maintenance has
prevented failures and production delays throughout the plants while helping ensure
employee safety.

In another example, aircraft engine manufacturer Rolls-Royce implemented predictive

maintenance on the Azure IoT platform to help their customers reduce costly flight
delays caused by engine maintenance issues. Each of their 13,000 engines in operation
worldwide has thousands of sensors that monitor engine components and deliver
insights around fuel efficiency, engine performance, and operational efficiencies. These
insights enable Rolls-Royce to anticipate maintenance needs and avoid costly,
unscheduled delays.

USE OF IOT IN PREDICTIVE MAINTENANCE IN DIFFERENT

INDUSTRIES

WIND - TURBINE

The RCA (Root Cause Analysis) of the situation gave an insight on the operational limit
of the turbine system which led to such under performance.

This analysis helped the operator to select a right functional threshold for the
equipment.Such proactive approach helped them to manage their turbines and its
health condition before any breakdown thus avoiding any significant loss in business
due to downtime.

PETROCHEMICAL

The IOT-powered predictive maintenance solutions have also made an indispensable

impact on oil refining and petrochemical companies.The major challenge faced by oil
refineries is that the physical inspection of the equipment located at deep ocean floor is
very dangerous and inefficient process.

Therefore oil refining industry has always been in need of the better method not only for
predictive maintenance, to identify potential failure, but also for better asset tracking.

Oil fields generally have assets fitted with sensors, to assimilate the vast amount of
data. But most of these data is never utilized
Dyogram, an IoT service provider for Industrial, Retail, Manufacturing and Logistics,
helped one of its oil and gas industry customers, to implement the predictive
maintenance solution and big data analytics.

Advanced predictive maintenance solutions helped mitigate the challenges associated

with huge volume of data generated by Oil refining and petrochemical companies.

The big data analytics ensures huge volume of data is managed in a scalable and cost-
effective way thus shooting down the maintenance costThese advanced solutions also
incorporate methods like, data storage in the central repository and efficient remote
monitoring.The solution was designed to compare the real-time data with historical
failure rate models and identifying potential equipment failure.This helped in efficient
resource maintenance, without the need for equipment replacement due to permanent
damage.

PROACTIVE MAINTENANCE

With new sensor information, IOT can help a manufacturer improve overall equipment
effectiveness (OEE), save money by minimizing equipment failure and allow the
company to perform planned maintenance.

BREAKDOWN MAINTENANCE

Unplanned failure Maintenance

When it comes to unplanned failure maintenance, the IOT enabled devices can make it
easier and more efficient to maintain assets in remote locations. As it was mentioned
before, IoT reduces unnecessary visits to remote locations where you need to inspect
assets through predictive maintenance. For example connecting assets through IoT like
wind farms or pumps would make assets generate work orders based on their condition.
By using EAM and mobile solutions, technicians would get exact location of the object
that needs maintenance, described problem and list of spare parts needed to fix the
asset. That would extremely reduce time and costs associated with emergency repairs
in Asset Intensive Industries.

Every industry can find value from IoT devices, but the best results are possible only if
IoT seamlessly integrated with your other systems like ERP(Enterprise Resource
Planning) and EAM(Enterprise Asset Management) . The IoT can also be a game-
changer for OEMs. It will redefine the business model as equipment vendors
supplement their offerings with software and data analytics services. Hardware will ship
with greater computing power, becoming more intelligent and more connected.
Manufacturers who are adapting and implementing IoT technologies are enabled to
create better value propositions and differentiate from their competitors because they
can more efficiently monitor and analyze, improve reliability while reducing unnecessary
maintenance costs. Leading to companies being able to reallocate their resources in
more efficient ways.

CONNECTED MACHINES
Communication is much more than just written and spoken word. Take it from
connected machines, which systematically work together via machine-to-machine
(M2M) communication.

Maintenance managers use M2M techniques to collect data on KPIs, such as assets
most likely to breakdown or top causes of unscheduled downtime.

Coupled with IoT sensors, M2M data helps maintenance managers gain insight into
how often an asset is underperforming, or how long it’s been since the last work order
was performed. Using this data, managers can map out when downtime will occur and
tie this data back to their preventive schedules to improve uptime.

Examples of strategies maintenance teams can use to collect M2M data include:

■ Vibration analysis: Gauges machine vibration to identify potential failures.

■ Infrared thermography: Detects radiation to measure and analyze the heat
of objects.
 ■ Ultrasound: Helps to hear issues that we normally cannot like a gas leak.
■ Tribology: Measures particles in fluids that prove mechanical wear.
■ Motor circuit analysis: Analyzes motor health through detection of
electrical imbalances.
■ Laser alignment: Assists in the aligning of rotating machines.

IMPROVED INVENTORY MANAGEMENT

Using the IoT, maintenance managers can connect their stockrooms to track orders,
incoming shipments or low stock.

For instance, the maintenance team has the ability to collect data remotely via sensors
that tracks when certain inventory may be low. From there, they’re able to connect this
sort of data collection to a software device to produce alerts when certain stock may be
close to out.

If you depend on the power of a computerized maintenance management system

(CMMS), connect your stockroom with your tool to automate reorders, generate
inventory reports and track costs to avoid shortages and improve budget. This results in
fewer emergency inventory orders and less downtime due to out-of-stock inventory to
fulfill a work order.

Inventory optimization

The better inventory managers know their stock, the more likely they are to have the
right items in the right place at the right time. With the real-time data about the quantity
and the location of the inventory items, manufacturers can lower the amount of
inventory on hand while meeting the needs of the customers at the end of the supply
chain.IoT systems can also collect and feed delivery information into an ERP system;
providing up-to-date information to accounting functions for billing. Real-time information
access will help manufacturers identify issues before they happen, lower their inventory
costs and potentially reduce capital requirements.

Automation of inventory tracking and reporting

With RFID and IIoT, inventory managers don’t need to spend time on manual tracking
and reporting. Each item is tracked and the data about it is recorded to a big data
warehouse automatically. Automated asset tracking and reporting save up to 18 hours
of working time per month and reduces the probability of human error.

Constant visibility into the inventory items’ quantity, location and movements
An IoT-based inventory management solution gives manufacturers precise visibility into
the flow of raw materials and components, work-in-progress and finished goods by
providing real-time updates about the status, location, and movement of the items, so
that inventory managers see when an individual inventory item enters or leaves a
particular location.

IOT IN OEE CALCULATION

Internet of Things (IoT) is helping the manufacturing agencies to improve their OEE
evaluation with a detailed understanding of equipment performance through
instrumentation and analytics. IoT solutions help to improve the OEE values in many
ways:

● Analyzing historic process and performance data to optimize maintenance

planning, schedules, and resources.
● Get warnings in advance about the degradation of their machines, with
predictive maintenance to avoid downtime.
● Leading to lower maintenance costs, reduced material and supplies, and
greater equipment availability.
● The production line quality will be carefully monitored. It will help you to
monitor process parameters, find out the calibration, temperature, speed and
production time of the machines.
● It will help in the management of supply chain. Industries will be able to
compare the previous production results with the new ones. It will help them
to decide how they can work on their future schedule
With the new innovative IoT related equipment, companies can easily reach a higher
OEE score, with a proper implementation of technology.

Manufacturing organizations will continue to pursue improvements in OEE. As

discussed above, IoT can deliver significant, quantifiable improvements.

How Industrial Internet of Things (IIoT) can help in improving OEE (availability,
performance, and quality) by connected devices and sensors? Let us take a deep
dive into how this can be achieved?

Connected equipment continuously transmit usage information or data to a central

location. By processing and analyzing the data, a lot can happen. If the data can be
presented in a meaningful way, then this will help in taking the right decision at the right
time to achieve OEE closer to 100% level.

Availability:

Early warning of equipment failure can help avoid unplanned downtime which can
improve the MTTR (mean time to repair). Also, IoT-enabled devices or equipment can
send alerts and/or reminders to the service provider on a real-time basis before any
failure occurs. This will ensure 100% uptime of equipment.

Quality:

Continuous monitoring of the production line can help improve quality drastically. This
can be possible by using IoT-enabled equipment. The equipment itself can send alerts
about preventive maintenance requests. If the equipment needs calibration, any
variation from prescribed dimensions, speed, time, temperature, tolerance level, etc.
then calibration, system upgrade, and change in operation pattern can be done
remotely using IIoT technology from a centralized location. This will ensure better
quality output and, in return, this will reduce recalls and after-sales warranty cost.

Performance:

Connected devices transmit huge amounts of data to a central location by analyzing the
current data along with the historical performance data (usage pattern), as a result of
which maintenance planning can be optimized. By embedding sensors in devices and
equipment as part of IIoT which can completely transform various aspects of equipment
performance. In addition, equipment/sensors can send reminders for preventive
maintenance based on the usage pattern which will help in achieving the best
performance for each of the connected equipment.

RFID tags

Radio frequency identification system (RFID) is an automatic technology and aids

machines or computers to identify objects, record metadata or control individual target
through radio waves.RFID is often seen as a prerequisite for the IoT.
An RFID tag has an ID carrying the information about a specific object. It can be
attached to any physical surface, including raw materials, finished goods, packages,
crates, pallets, etc. In an industrial setting, mainly passive tags are used, i.e. those
without their own power supply. Such tags are cheaper but require the power from the
reader to be able to transmit data.
RFID antennas: An RFID antenna catches the waves from the reader to supply energy

for tags’ operation and relays the radio signal from the tags to the readers.

RFID readers: An RFID reader, which can be either fixed or handheld, uses radio

waves to write to and read from the tags. It can read from the number of tags over

distance. The reader catches the IDs that are written in tags’ memory banks and

transmits them to the cloud, together with the data about the readers’ locations and the

time of readings.

How does an inventory management solution based on IIoT and RFID work?
To see more clearly how the inventory management based on IIoT and RFID works,
let’s consider an example. Say, among other pharmaceutical equipment, an enterprise
produces single-punch tablet presses. The enterprise owns two geographically
dispersed factories: one – to produce press components, the other – to assemble the
final unit.

At the start of the production cycle, the components for, say, die lower punches, get
passive RFID tags. Each tag is granted a unique identification number that contains
data about every part. The list of tags’ IDs is saved to a big data warehouse.

During the manufacturing process, as the tagged components move from station to
station and from shop to shop, the RFID readers scan the tags and relay the IDs, the
time of the readings, and the data about the location of the readers to the cloud.

The cloud analyzes the incoming data and identifies the locations and the statuses of

the components. If any of them is missing, the cloud pinpoints the missing part, sends

an alert to a solution user and sets the status of the item in the inventory management

solution to ‘missing’. As soon as the location of the component is identified, its status is

set back to ‘in production’.

When the production of the die lower punches is finished, they are shipped to the other

facility for assembling. They are packed in packages and crates, put on pallets and

placed in vehicles, the vehicles are scanned with a handheld RFID reader before they

depart. The employees at the assembly affiliate see that the parts have left the

production affiliate. Once the parts arrive at the assembly facility, the vehicles are

scanned with handheld readers one more time to make sure no items are lost.

As soon as the single-punch tablet presses are assembled, each press receives

another tag (the tags from press components can be either kept or removed, depending

on the cost-effectiveness of the required operations). As the presses move from

department to department, say, from assembly to quality check. In the warehouse, the

reader scans the tags and in case the cloud detects a missing unit, it sends an alert to

an operator. If the IoT-based inventory management solution doesn’t report any missing

units, the pallets are forklifted and unloaded.

As a result, manufacturers track the inventory from the day the individual components

were manufactured to the day the assembled unit arrives at a warehouse and then

departs from it to reach end-customers.

 BIBLIOGRAPHY

● Digitising the Industry Internet of Things Connecting the

Physical, Digital and Virtual Worlds
● https://www.hcltech.com/blogs/improving-overall-equipment-
effectiveness-oee-smart-factory-journey
● https://www.scnsoft.com/blog/iot-predictive-maintenance-guide
● https://blogs.partner.microsoft.com/mpn/iot-enabled-predictive-
maintenance-can-transform-business/