Digital Twins can be the intelligent edge for IoT in the manufacturing sector – Part 2
The first half of this two-part series looked at the concept of digital twins and explored how it can help manufacturers with visualisation. Now, says Sukamal Banerjee of HCL Technologies, let’s explore the second big advantage digital twins can bring, and think about the questions an industrial enterprise needs to answer to find out what digital twins it needs to implement.
Collaboration is key
The second critical aspect of a digital twin is the ability to share this digital view of machines irrespective of the viewer’s physical distance. This allows multiple individuals to see, track and benchmark manufacturing installations on a global scale. This ability removes the delay in reporting alerts to management, eliminates single points of failure due to human error, and makes seeking expert help easier.
A digital twin expands the horizon of access of the shop floor to product managers, designers, and data scientists. Armed with a new understanding of how productive their processes and machines are, they can design better products, more efficient processes, and foresee problems/issues sooner rather than later. This saves time and reduces wasted materials on building physical models, as well as making it easier to see the gaps between desired and actual outcomes, and running root cause analysis.
It’s important to remember that digital twins are different from traditional 2D or 3D CAD images in scope and use; while CAD images and simulations consist mainly of the data of dimensions of a single piece of equipment or sub parts, digital twins focus on capturing more holistic data of the equipment in terms of how it interacts with other equipment and the environment.
This entails measuring the data and configuration of the installation (including space and other dimensions between different equipment) and data of the ambient environment (temperature, pressure, vibration, etc.); this data is fed on a continual basis from the physical to the digital twin through the digital thread.
So, what should a business think about if it is considering using digital twins?
There are three big questions to consider:
- The first step is to ask, “What do I need to know about my manufacturing operations that will allow me to drive decisions?”. This helps decide what kind of data to capture, and which visualisations to implement.
- The follow-up question is “What are the top three to five roles in my business for which I primarily want the digital twin?”. The answer to this question can effectively clarify what views to create from the captured data. Digital twins, by definition, are customised to roles to ensure only relevant data is shown, thereby reducing visual clutter.
- The final step is to create an incremental roadmap to make the digital twin richer over time. This can be done by either adding more relevant data sets to the existing imagery or by providing access to a wider set of roles within the business. A great example of how to build an incremental digital twin is Google Maps, which today emulates location and traffic data in much more detail and more accurately than it did a decade ago. It has constantly evolved over time in terms of richness of data and hence utility.
The benefits will be worth the pre-planning a digital twin requires. Industrial companies that have digital twins will be able to create sustainable competitive advantage due to better products, higher efficiency, and faster release cycles (from product ideation to market). The key to successful use of digital twins, therefore, is to start with small projects, before reinvesting benefits and ROI to create better, more complete systems in the near future, driving success on an ongoing basis.
The author of this blog is Sukamal Banerjee, corporate vice president – ERS Sales (Hi Tech & Comm) and head of IoT WoRKS at HCL Technologies.