Leveraging The Closed-Loop Digital Twin - tcm27-87251

LEVERAGING THE CLOSED-LOOP
DIGITAL TWIN
Of the powerful capabilities made possible by the industrial Internet of Things (IoT), smarter
maintenance and closed-loop digital twins are two that yield the most significant and immediate
benefits.
To gain a competitive advantage, manufacturers must continue to

push the boundaries of technology and advance their processes.
As the power of the industrial IoT becomes increasingly apparent — to address operational issues
and drive competitive advantage— forward-thinking organizations are pioneering new ways to
leverage it. Driven by fierce competition, thin product margins, aging fleets of factory assets and fast-
changing customer choices, manufacturers are turning to digitalization to optimize products and
processes—and, ultimately, to increase profitability and stay ahead of the innovation curve.
Most manufacturers understand the value of using digital twins to establish a permanent connection
between the physical asset and its virtual counterpart, as well as integrate with product lifecycle
management (PLM) systems to continuously optimize production digitally.
Fewer are familiar with the benefits of extending digital twins across the production cycle to
products in the field. Using MindSphere, Siemens’ industrial IoT as a service solution, manufacturers
can now build digital twins of performance. The product, production and performance twins
connect to create a closed feedback loop, ensuring that performance data from products in the field
and from production environments feed into the product and production.
Leveraging the Closed-Loop Digital Twin 2

The Closed-Loop Digital Twin
Implementing condition monitoring is widely considered to be among the
best use cases for companies just beginning their digitalization journey.
Manufacturers can conduct a pilot on a single, critical machine and gain a return
on investment (ROI) within months. From there, they can extend it to other
machines, entire lines and value chains, and even to customer equipment in the
field.
Deploying the closed-loop digital twin often occurs further along the
digitalization journey–especially if the digital twin mirrors the entire, fully
connected product lifecycle. Manufacturers commonly begin implementing the
digital twin in new product R&D and planning cycles, with a focus on virtually
simulating new designs. More advanced companies also have digital twins of
their production processes to confirm manufacturability and streamline new
product engineering.
The most progressive organizations are pushing the boundaries toward using
the digital twin to monitor the live performance of products and the production
line. A digital twin that enables changes based on live data is called the closed-
loop digital twin. With this advanced approach, production line machines
are evaluated to determine if the line works as intended. Also, a product’s
performance is tracked after it leaves the production line. The product is
monitored to analyze its expected use and performance against its actual use
and performance. This data can then feed back into the design as well as the
production line, allowing real-time adjustments and quick simulation updates.

The Benefits of a Comprehensive Closed-Loop
Digital Twin
When a manufacturer’s strategy includes a closed-loop digital twin, smarter
maintenance can be extended into every area of production using the newest
form of the digital twin, the digital twin of performance:
Digital Twin of the Product. In the early stages of design, manufacturers use
the digital twin to virtually simulate and validate properties, rather than
build and test physical prototypes. Virtual prototyping allows you to better
understand how a product design will perform under various conditions
while reducing development time, improving product quality and enabling
faster iterations.
The closed-loop digital twin introduces live performance data to this

process. Once the product leaves the production line, the digital twin of
the product continues to collect real-time data about its performance.
Manufacturers use this live performance information to make changes to
the current design in production or to improve future design iterations
by making updates to simulations. As an example, if a part is found to be
defective in the field, it can be changed out in the live production line.
Furthermore, with this constant flow of performance information,

manufacturers can adopt new business models, such as maintenance
as a service. Manufacturers can offer their customers remote condition

monitoring through the end of the product’s lifecycle. They can also lease
machines to customers and charge based on actual usage.
Digital Twin of Production. A typical production twin validates critical aspects

of the production line through virtual simulations, ranging from plant assets
to controllers. This capability enables industrial organizations to identify
sources of error or failure in a production line before implementing the line.
The closed-loop digital twin introduces live performance data to production

lines. Once a line is set up, data can be captured during test runs that
allow manufacturers to optimize the production by checking machine
performance and adjusting the timing between product runs.
After testing, live data is continually collected, which allows monitoring

of the condition and performance of each machine in the production line.
Using this data, manufacturers can go beyond identifying machines or parts
that will soon fail. They can identify areas that are not running as expected
and then simulate changes to the line before making adjustments. With
the simulations, manufacturers can proactively change the line to boost
productivity, reduce scrap and decrease manufacturing errors without
affecting production.
Introducing the digital twin of performance augments the capabilities of the

other twins. More importantly, it effectively creates the closed feedback loop that
links the very design of the product to its implementation and then back to its
design. The implications are powerful.

Smarter maintenance can be
extended into every area of
production using the closed-
loop digital twin.

Real-time Data Means Real-time Improvements
Because the digital twin can be continuously updated with real-time data, it
changes as the physical asset is changed. Digital twin-enabled maintenance
allows scheduling according to real-world usage data and enables real-time
virtual simulations, both a step-change improvement. With a real-time model of
an asset, manufacturers can run virtual simulations to determine performance
based on age, runtime or exposure to harsh conditions. The addition of the
closed-loop digital twin enables manufacturers to peer into the future to
determine maintenance needs.
With a permanent connection between a physical asset and a digital twin,

manufacturers can continually optimize a product and its production digitally–
including its maintenance requirements.
Once deployed, the digital twin-based solution delivers these enhanced benefits
to the production process:
Downtime reduction. Using real-time data, manufacturers can identify and

solve problems before they cause shutdowns, and schedule maintenance
during times that would be least disruptive to operations.
Reduced maintenance costs. Enhanced with a digital twin, maintenance can

be smarter to prevent it from being performed neither too early nor too
late, both of which are costly. Maintenance can be planned and based on

the actual condition of the equipment, so manufacturers can be sure the
maintenance they perform is the most cost-effective.
Improved equipment performance and reliability. Leveraging real-time

asset performance data allows manufacturers to virtually adjust and test
variables to determine how the changes affect equipment performance and
reliability. By using those insights, manufacturers can make smart decisions
about whether and when to make adjustments to the physical process.
Additionally, they can see expected vs. actual performance, for example,
to learn if unplanned variables are affecting performance, and then make
adjustments based on the new knowledge.
Extended asset lifespan. With a simulated model, manufacturers will be

better able to reduce emergency downtime and other unnecessary “wear
and tear” to ensure they attain optimum performance from, and a maximum
lifespan of, the asset.
Inventory management. When it can be predicted more accurately what

maintenance needs to be completed and when, manufacturers can reduce
internal service and spare parts inventory levels to more closely match the
need. Maintaining safety stocks of parts and supplies, purchased and stored
“just-in-case,” is no longer necessary.
Fleet management. Whether monitoring hundreds of customer machines

located throughout the world or multiple production lines replicated in
several factories, the digital twin will gather all the data points from the

assets in near-real time. Manufacturers can establish benchmarks and
thresholds that enable the digital twin to automatically highlight anomalies
that may require action. Likewise, with IoT-enabled maintenance, updates to
machines and production lines can more easily be replicated across a fleet of
assets.
What-if simulation. Manufacturers can run simulations that will help them
predict how an asset will respond to various changes, such as runtime or
exposure to operating conditions. They also can perform test maintenance
scenarios or specific repairs to see how they work digitally before applying
them to the physical asset, reducing the risk and cost associated with
making adjustments to machines and processes.
Improved safety. Unplanned events, and especially emergencies, create

unsafe conditions. With a digital twin informing maintenance schedules,
manufacturers can reduce–or even eliminate–the chance of an unexpected
event or emergency.
Beyond production, additional benefits of the digital twin of performance

emerge. With these new capabilities, manufacturers can:
Implement and develop a maintenance as a service business model.

Manufacturers can provide customers with the option to outsource product

With digital twin informing
maintenance schedules, manufacturers
can reduce the chance of an
unexpected event or emergency.

maintenance to them by offering service level agreements (SLAs) based on
customer need. This provides a recurring revenue stream and also helps:
• Reduce support costs by minimizing asset failures, which reduces
end-user downtime costs along with internal service and spare parts
inventory costs.
• Increase customer satisfaction by increasing asset productivity.
Minimize warranty claims. By understanding exactly how end-users are using

equipment, manufacturers can assess the validity of warranty claims.
Continually offer innovative products. By understanding how products

behave in operation and at peak times, manufacturers can refine product
development to drive quality and innovation.
Bringing the Closed-Loop Digital Twin to Life

While many manufacturers already use the digital twins of the product and
production, they lack the ability to fully enable the digital twin of performance
and create the feedback loop necessary for the closed-loop digital twin. It
requires a cloud-based IoT solution that can not only remotely monitor assets,
but also seamlessly integrate with the other technologies used in the digital twin
of the product and the digital twin of production.
Siemens is leading the innovation–it is the only company able to fully provide
the closed-loop digital twin (Figure 1). MindSphere, its industrial IoT as a service
solution, adds the digital twin of performance to an already robust digital twin
of the product and digital twin of production. The full digital thread is managed

with integrated CAD, CAM, CAE, PDM and IoT software, giving you operational
transparency and a closed-loop digital twin that spans the enterprise and across
the full product lifecycle. With all processes connected and updated in real time,
you can leverage the closed-loop digital twin to power smarter maintenance
across products, plants, systems and machines.
Figure 1: The Siemens closed-loop digital twin.
With the continuous collection and intelligent analysis of operating data from
IoT-ready sensors, digitalization has opened up entirely new possibilities with
advanced analytics and data collection from connected assets. By extending
the digital twin out to machines and systems in the field, manufacturers
have the opportunity to enable full-scale maintenance capabilities across the
manufacturing enterprise and the full product lifecycle. With these capabilities,
manufacturers will not only improve profitability but will establish a competitive
advantage.
This content was developed in partnership with Siemens Digital Industries Software.

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LEVERAGING THE CLOSED-LOOP

To gain a competitive advantage, manufacturers must continue to

Leveraging the Closed-Loop Digital Twin 2

Leveraging the Closed-Loop Digital Twin 3

The closed-loop digital twin introduces live performance data to this

Furthermore, with this constant flow of performance information,

Leveraging the Closed-Loop Digital Twin 4

Digital Twin of Production. A typical production twin validates critical aspects

The closed-loop digital twin introduces live performance data to production

After testing, live data is continually collected, which allows monitoring

Introducing the digital twin of performance augments the capabilities of the

Leveraging the Closed-Loop Digital Twin 5

Leveraging the Closed-Loop Digital Twin 6

With a permanent connection between a physical asset and a digital twin,

Downtime reduction. Using real-time data, manufacturers can identify and

Reduced maintenance costs. Enhanced with a digital twin, maintenance can

Leveraging the Closed-Loop Digital Twin 7

Improved equipment performance and reliability. Leveraging real-time

Extended asset lifespan. With a simulated model, manufacturers will be

Inventory management. When it can be predicted more accurately what

Fleet management. Whether monitoring hundreds of customer machines

Leveraging the Closed-Loop Digital Twin 8

Improved safety. Unplanned events, and especially emergencies, create

Beyond production, additional benefits of the digital twin of performance

Implement and develop a maintenance as a service business model.

Leveraging the Closed-Loop Digital Twin 9

Leveraging the Closed-Loop Digital Twin 10

Minimize warranty claims. By understanding exactly how end-users are using

Continually offer innovative products. By understanding how products

Bringing the Closed-Loop Digital Twin to Life

Leveraging the Closed-Loop Digital Twin 11

Figure 1: The Siemens closed-loop digital twin.

Leveraging the Closed-Loop Digital Twin 12

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Inventory management. When it can be predicted more accurately what

Implement and develop a maintenance as a service business model.