Digital Twinning:
Embracing Interoperability and Deep Sharing Among Applications
Read the full Digital Twinning eBook:
By Michael Parks, PE, for Mouser Electronics
Companies that design and manufacture mass-produced electronic products must contend with a plethora of different
software applications during the entire product development and sustainment lifecycle. These software families
include (to name just a few):
- Computer-Aided Design/Engineering/Manufacturing (CAD/CAE/CAM)
- Product Lifecycle Management (PLM)
- Manufacturing Execution System (MES)
- Application Lifecycle Management (ALM)
- Application Performance Management (APM)
- Quality Management Software (QMS)
- Customer Relationship Management (CRM)
- Enterprise Resource Planning (ERP)
- Supply Chain Management (SCM)
Each of these contains a mixture of common and unique data about the product or its associated processes and
relationships to business functions. Often, the data isn’t natively interoperable between systems without some
level of manual effort. Embracing the concept of the digital twin (DT) will force product developers to rethink the
“islands of applications” approach if they wish to remain competitive in a world of ever-shrinking
product cycle times and increased competition as manufacturing technologies become more accessible to a broader
number of design firms.
Iterative Design and Engineering Process
One of the most tantalizing benefits of the emerging DT concept is the nearly seamless capability of real-world
data feeds through prototypes and fielded products in the iterative design and engineering process. By incorporating
sensors that monitor both the health of the product and its operating environment, engineers can gain an
understanding of the nuances involved in a device’s functionality within actual operating conditions.
Furthermore, leveraging the ubiquitous Internet as the medium by which to transport data between the fielded
product and the DT means that the operational and maintenance history of literally every device becomes helpful in
refining both the DT and subsequent product generations. This is encapsulated in a five-step process model:
1. Create
Initially, one should capture a design (mechanical, hardware, and software) in a manner that creates deep sharing
between applications. This will require an existing CAD/CAM/CAE that embraces interoperability and appreciates the
entire workflow involved in the product design. Vendors that don›t open their applications to others (whether
upstream or downstream from their own) may soon find themselves a lonely island.
2. Communicate
Enable a device to report its condition and operations back to its DT so the virtual representation can remain
up-to-date based on real-world feedback. IoT and enabling technologies will be crucial in providing the
communication infrastructure necessary to connect the digital and the physical.
3. Aggregate
Information about a single object is great but being able to seamlessly collect data points from an entire product
line is invaluable. Communication to the equipment manufacturers regarding all data, both performance data and
external factors (like ambient temperature), is possible in real time to improve the DT model and simulation
variables. New classes of database software are necessary to handle the data volume and complexity that IoT
generates and DT consumes.
4. Analyze
DT can then analyze the operational data and predict failures if it sees data points outside of prescribed
tolerances. For example, a circuit board might see higher than expected operating temperatures or motors
experiencing an unusually high number of stop-start cycles. DT can determine with (some level of confidence) that
the part will soon fail and take a series of approved actions, such as placing an order with the company responsible
for manufacturing the failing part and alerting a technician to brush up on the process for replacing the component.
Thus, any downtime will be minimal and relatively predictable.
5. Adjust
Lessons learned from analyzing fielded systems could be helpful in refining future iterations of a product by
providing real-world data points. Access to unadulterated data, free from an end user’s subjective
perceptions, enables faster development cycles, significant reductions in product defect-detection time, and/or an
identification of useful tweaks. This access also reduces waste by allowing manufacturers to make real-time
improvements to products still coming off the assembly line. DTs allow designers to test different
“what-if” alternatives, as the cost is negligible, and the risk of failure is low. This can translate
into huge savings by omitting costly rework.
Other Valuable Insights
DT abilities go beyond tweak assessments of the physical properties of a design. DTs can also make it easier to
study software and firmware revision impacts on performance. Various configurations and settings can undergo rapid
testing and assessment to determine which ones will deliver optimum performance. Firmware could seamlessly push out
updates to all relevant devices by leveraging the same Internet connection that initially sends the data out to
identify improvements.
Coupling DTs with other emerging technologies that possess product design implications, such as augmented reality
(AR) goggles, could empower engineers and designers to experiment with near-endless design alternatives before they
commit to a final solution. DTs will allow assembly-line technicians to create a construction-schematics virtual
overlay on top of the physical construction in progress. This will help to identify potential defects far earlier
and more efficiently during production, than otherwise possible. If any issues arise, the DT model’s rich,
visual experience (unencumbered by fumbling through of paper drawings) will translate into significant efficiency
gains on the production line.
Desktop manufacturing tools, such 3D printers, laser cutters, and milling machines, are continuing to evolve as
well. Soon, these machines will be able to leverage DTs to empower Global Development teams to collaborate virtually
and produce (at least) prototype-like physical objects by clicking a button.
Conclusion
DTs will force shifts in business priorities such as investment in telecommunication infrastructure and/or
cloud-based services. Soon, designing with applications software in mind will no longer be sufficient; instead,
engineers and technicians will need to become more tech savvy for the benefit of their designs, especially in
industries that don’t traditionally shift as quickly as consumer-oriented industries do. By seamlessly
bringing what’s virtual and physical together, DTs are positioned to change almost everything about how the
world’s industries build and sustain physical products.
Michael Parks, P.E. is a contributing
writer for Mouser Electronics and the owner of Green Shoe Garage, a custom electronics design studio and technology
consultancy located in Southern Maryland. He produces the S.T.E.A.M. Power Podcast to help raise public awareness of
technical and scientific matters. Michael is also a licensed Professional Engineer in the state of Maryland and
holds a Master’s degree in systems engineering from Johns Hopkins University.
