Blog post by Sam Hoff, CEO of Patti Engineering
I was recently meeting with a client who has 200 manufacturing engineers working for him. Of those 200 engineers, he estimates that 100 of them will retire within the next five years. He doubts he will be able to adequately replace all the bodies and knowledge that will be walking out his door.
According to AdvancedManufacturing.org, “Over the next decade, nearly 3.5 million manufacturing jobs will be available, and 2 million are expected to go unfilled due to the skills gap. US leadership in the automotive manufacturing sector is indeed threatened by this lack of skilled talent, an issue exacerbated by the large numbers of experienced workers, in enterprises big and small, that will retire between now and 2030.”
In addition, millennials are not going to behave like their parents or grandparents. My experience is that millennials will work 60-80 hours per week when required for short periods of time, but they will not be willing to spend 60-80 hours a week in a manufacturing facility for 10-15 straight years as past generations have.
These factors help drive the need for digital twins.
In the design phase of manufacturing lines, simulation has been used for well over a decade to create and design the systems. This digital twin is a great template but is often not used beyond the design stage. Often the line builder will then go into the build phase, modifying what is needed to create an as-built system. The as-built system is delivered to the manufacturer with as-built prints, manuals, PM schedules, etc. Often the digital twins are not delivered to the customer. If they are delivered, they are usually not accurate to the as-built system.
Even if the digital twin is delivered, the manufacturer rarely has the training or the time to maintain the twin. I recently talked to an engineering manager who explained that he gets all kinds of data daily from his manufacturing systems, but does not have the time to sit down and analyze the data.
So, in regards to digital twins, why does the person who is perfecting the digital twin need to be in the facility? With the proper data being feed to the cloud through a platform such as Siemens MindSphere, the digital twin can be perfected remotely. One system I like is Beet Analytics which creates an EKG of a system thereby marrying up the timing of the physical and digital worlds.
In addition, instead of sending an overabundance of data to the already strained manufacturing engineers tied to the manufacturing lines, do the data analysis remotely, summarize the data highlights and report the findings to the manufacturing engineer.
Data will be increasingly analyzed through artificial intelligence. AI techniques are being perfected by many in Silicon Valley and can be applied to manufacturing. The biggest issue affecting the use of AI in manufacturing is the fact that rarely the data from a manufacturing system is clean or verifiable. This will change in the future as companies such as Patti Engineering clean the data on legacy manufacturing systems.
Manufacturing over the next 5-10 years will be all about doing more with less manpower and engineering expertise at the physical equipment. The manufacturers that adopt the digital revolution in the future are going to separate themselves from the ones that are stuck in the past. At Patti Engineering, we are prepared up to help you realize the benefits of digital twins, IIoT, and applying data science to your manufacturing facility. We look forward to showing you what the digital revolution can do for your facility.
For more information on how to harness the power of digital twins and Industry 4.0 automation, please contact Patti Engineering.
- Why Virtual Commissioning?
- What Can Go Wrong When You Underestimate The Edge
- Profibus Debugging
- Identifying Production Blocks Using MindSphere
- Patti Engineering Announces Leadership Changes in Austin, Texas Office Amid Growth in Automotive Industry Opportunities