LiveWorx 2018, the annual PTC-sponsored digital transformation conference held in Boston’s Innovation District, was just a few short weeks ago. The conference featured hundreds of interesting sessions around the most cutting-edge technologies, interactive demos on the showroom floor, and PLM and CAD experts on hand to answer attendees’ most burning digital transformation questions.
One session in particular, hosted by Steve Dertien, CTO of CAD and PLM, and Kevin Wrenn, divisional general manager of PLM, from PTC, covered the concept of digital twin that was.
In case you missed it: here’s a quick recap of the session:
First off, what exactly is a digital twin? To answer that question, you need to determine what type of information is included in a twin. A digital twin is comprised of two components – the digital definition of the product and the physical experience of the asset in the field – such as environmental conditions and performance data. Without both the physical and the digital, all you have is a digital sibling – not a true digital twin.
Leveraging both the digital definition and physical experience of a product has a multiplier effect throughout the company. Nearly every stakeholder can benefit from the wealth of information generated:
When you think “digital twin,” you probably imagine that a company or organization has a digital twin system that houses all of the important information that stakeholders throughout the organization need. The truth is, there isn’t one all-encompassing digital twin. Putting too much data into a single digital twin would overwhelm the system – forcing stakeholders to doggie paddle through a data lake to find what is most useful for them.
Data that is valuable to one person might be worthless to another. To ensure that a digital twin is fit-for-purpose, there needs to be multiple views of the twin, depending on stakeholders’ roles and needs. Providing stakeholders with direct access to the information they need can give manufacturers the most value from their digital twin.
For example: engineering and service can use information from the field to improve product design. Manufacturing, meanwhile, can focus on information to can be used to make modifications to the assembly line.
MAN Truck & Bus, a leading provider of commercial vehicles and transport solutions in Europe, is leveraging digital twin as part of their digital transformation. The company has already taken steps to move to a consolidated product data management system and to provide faster, easier access to data with role-based apps.
Now, MAN is exploring the use of smart, connected products and building a digital twin. They have been working on a connected truck that combines the GPS location and other real-world information from products in the field with information from engineering and manufacturing. This combination of digital and physical allows MAN to determine when and where issues arise and allows them to bring that quality information back to production.
Meanwhile, Hirotec, an automotive OEM who produces parts including automotive doors and exhaust components and systems, uses a digital twin to monitor their equipment on the shop floor. Hirotec used to inspect each of the exhaust systems it manufactured by hand -- but this process was too time-consuming.
So the team implemented an advanced robot system that included vision sensors, laser measurement sensors, and force sensors to inspect the exhaust systems for them. This robot system ended up collecting more than 465 data points for each inspection. With a digital twin, Hirotec measures these data points against design requirements to analyze the trends of each inspection point and to determine opportunities to make improvements. This has significantly reduced the time it takes to make improvements: where once it took a month to collect data and investigate potential improvements, the process is now completed within a week.
So how can your organization get started on its digital twin strategy? I think the real question here is, how can you get started on your digital transformation journey?
There’s a few goals you’ll want to achieve to get to digital twin. These steps don’t need to be taken in chronological order – you can run through the processes simultaneously, you can pick one to focus on now and the rest at a later day – heck, you might already have some of these goals completed.
One thing you need to do is “get your digital house in order.” What I mean by that, is that you need to make it easier to find and access product data. A digital product definition makes it easy to consolidate all data – creating a complete foundation for your transformation strategy. Another goal is to extend product data throughout the enterprise for universal data access. Universal data access drives productivity and enables stakeholders to make faster, better decisions.
Now that you have your foundation in place, you can stretch your legs with even more smart, connected tactics. You can now enable a digital thread throughout the entire product lifecycle to ensure digital product traceability. You can begin designing products with smart, connected capabilities in mind. This will ensure that you are able to capture the data streams you need instead of gathering a bunch of data you don’t want and don’t use. Finally, you can begin replacing performance assumptions with real-world data from multiple products and sources to improve the business through better informed decision making.
With these steps taken towards a smart, connected product development process, it is now possible to converge the physical experience and digital definition of a product into a digital twin.
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