Today’s era of manufacturing is spiked with words such as digitalization, disruptive, analytics, AI(1), flexibility, platform, predictive, digital continuity, order of one and many others. To address those in one or the other way, companies have no choice to achieve their transition without the Digital Twin. Of course, each company defines its Digital Twin slightly differently and there are many different definitions out there.
To make it simple, for me a Digital Twin is an executable virtual model representing a physical system with objects.
In my work as Senior Operations Consulting Director, I get the impression that many customers know what they want to achieve. However, many do not fully understand the huge potential coming along with it. However, before harvesting those huge benefits, it is key as a company to fully commit to such a transformation. This may be difficult, as different Business Units will need to be convinced and aligned, such as Product Design, Production Engineering, Process Engineering, Supply Chain, Manufacturing and Service. Additionally, supporting Business Units such as IT and Finance need to play along as well to make it happen.
Therefore, it does not strike me as a surprise, that
only 23% of companies with a Digital Twin budget, allocate more than \$1 million to it.
Why? Because the Value it will bring is never fully understood by the complete organization. Moreover, it needs some visionary mindset as well.
The most common value use cases expressed by customers are
- Improve product quality (34%)
- Reduce manufacturing costs (30%)
- Reduce unplanned downtime (28%)
- Increase throughput (25%)
Of course, they are all valid however, other direct impacts such as speed for NPI(2), improve SOP(3), testing of new design ideas and especially simulation in all different flavors are significantly underestimated.
Just imagine you could reduce the time from the first version of a new product to serial production in two different factories by more than 50%! The value is huge.
Let me know your opinion in the comments section.
In the meantime, I will recap some thoughts on the usage of data in a Digital Twin and will share those in my next post.
(1) Artificial Intelligence (2) New Product Introduction (3) Start of Production Numbers of impact estimation and budgets based on lnsresearch.com
