NEED A SECOND OPS PART MAKER OR A PERFECT PROTYPING MACHINE?

Make one-off and small batch parts in-house while your bigger machines handle production.

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of manufacturing processes that do not fully utilize this capability. a s a recent example, we have been doing research through collaborations led by two experts in additive manufacturing in our department. This additive manufacturing tool was a stir friction welding additive manufacturing where a rotating spindle required control of friction and force resulting in growth of material. all of the previous machines did not have a tunable and adaptive feedback control using on-the-fly sensor information from temperature, heat, contact force, and other moving parts to just name a few. Our modified system has been able to enable a much more optimized operation.

When I got involved in this process, I asked why are we not using all the sensors available to us? This was as recent as last year, and indicated that a lot of manufacturing process capabilities are available but we don’t take full advantage of them. So today, we may not need to invent a new manufacturing technique, instead we can go to an existing manufacturing technique and add a software level operation to optimally control the process. In a lot of places you can do this at the software level, without bringing in any hardware. all you have to do is adjust the operating and commanding of the process. In this specific project that we were involved in, we realized that there were no force or heat sensors used in a feedback control manner. So for that project, we started adding a force sensor and heat and temperature measurement sensors. While the original equipment cost was somewhere between $500k to $1 million, the added hardware and modified software were at the noise level and only a few thousand dollars.

TB: So $2k or $3k for those items to get the improvement?

DJ: yes, and the software. I think this is the number one key in my expert opinion on what has been overlooked in the manufacturing equipment. I think the second important factor would be the data that you can collect that are readily available. We have the technology today, we have the aI (artificial intelligence) to decide about the health of the device using data collected. We may not need a new manufacturing technique, but instead a robust adaptive control addition to predict the life of the equipment and enable predictive maintenance may suffice. What is being done in Industry 4.0 and Industry 5.0, they are collecting data and instrumenting the robot even more by adding various sensors. They might add, for example, an inexpensive camera as well, and integrate that with all the other measurements. With all that information, you will be able to get the state of health of the robot and try to predict when it will be failing. If the predictive analytics say the arm of the robot is going to fail in two months, for example, you start placing the order for that part and schedule the preventive maintenance to change out the arm without disruption. That’s what I’m thinking are the top two factors we need to take advantage of, as I’m witnessing by my own research and funded projects.

TB: Great stuff Dr. Jalili. Now I want you to look out over the horizon, shift forward five years, give us a forward looking perspective of something in its infancy, that we are just reading about or hearing about, something that industrial companies should have on their radar for consideration.

DJ: a s we are only beginning to scratch the surface, and as I talked about the human side of manufacturing, we will be moving towards what is referred to as discrete manufacturing. The designer, for example, could be in country a , the robot is in Country b, and the products to sell and deliver are in Country C. all of these are coming together in a virtual environment that could bring everybody into the same virtual and cloud-based space where they can interact. So everyone can see the product using their goggles, in a virtual and augmented reality, and can talk with each other to predict what could be done collaboratively. What we do today with Zoom is similar. I could not have imagined writing a major multi-investigator proposal with five different universities on only my computer and from my home, during the Covid 19 pandemic. everyone was sharing their presentations and working at the same time and commenting at the same time. That was made possible and now everybody is enjoying this environment where we can just do all of this collaboratively - sharing, presenting, producing. Now imagine that you can actually take this to the manufacturing world and create a virtual place where everyone can join and start testing their product, and testing that process virtually.

again, people are physical, but they join that virtual environment where that manufacturing process is actually built and viewed step-by-step as you are in that domain. We have a real example where we used a custom trailer that had everything in it, including power generators, air conditioning, etc. to power a small ‘manufacturing plant’ inside the trailer. you can see everything and go through the interactive steps, and come out with a product in your hand that has been produced.

We have to get that trailer to high schools, and that is what we have been doing, and say ‘Hey, students, manufacturing is not about an oily, dirty factory where you walk around with a lot of large and ugly machines, gearboxes and grease on the floor. No it could be as nice as computer-based manufacturing like this trailer. Go inside and be amazed.’ We teach undergraduates and high school students that this is the future of manufacturing and we attract them to our program. but imagine that you create a virtual version of this one, that you don’t have to have a trailer that moves around. Then you would create a virtual environment where everyone can join and run through manufacturing education and research by experiencing an avatar-like environment generated by a headset.

TB: Thank you for giving us a great perspective today Dr. Jalili. Good luck in your research!

DJ: you’re welcome. Thank you.