December 20, 2024

At Mizzou, we believe in the power of hands-on learning. We call it the Missouri Method, and it is an important part of our curriculum and what makes Mizzou Made engineers valuable in the workforce. For Mizzou Engineers, that process culminates with a senior capstone class where students develop solutions to real-world problems.

Students studying industrial engineering work with a client to develop solutions to engineering problems. One group of students was partnered with Schneider Electric. The students—Ben Ennis, Miles Kousoulas, Mohammad Mayyal and Brian Oster—were tasked with optimizing Schneider’s overall production flow, which was experiencing downtime on the lines because material handling tuggers were not able to fully support production demand. Their goal was to increase product throughput.

Learn more about the problem, how the students worked to solve it and what they learned from the experience.

Optimizing a production line

Miles Kousoulas: Schneider told us that there was a lot of work in progress getting built up, which was causing downtime on the lines. So, they wanted us to work on the tugger system.

Mohammad Mayyal: We were assigned to work on a system supporting production lines with two different tuggers, each tugger having specific pickup stations. The problem was traffic congestion between two tuggers in specific areas of the facility.

Ben Ennis: Essentially, the lines were backing up because the trains were too full to pick up products. And then when the lines would back up, the production would stop on those lines. That’s a problem because a line would go down simply because it’s made too much product and it can’t move it.

Using data to create simulation models

Brian Oster: Once we were given the problem from Schneider, they gave us data to work with, which we analyzed and used to create a model, or simulation model, of their tugger system. This took us a lot of time because we tried to match it as closely as we could to their real system. Then, we developed alternative solutions to test in our simulation. We ended the capstone project by presenting to them the findings from our simulation and our alternatives.

Ennis: After we created the simulation model, we came up with three ideas for what they could do to improve it. First, Schneider could add carts to the tugger train; second, they could develop a monitoring system for the train; and third, they could standardize the palletization at the end of the lines. All three solutions resulted in increased throughput and utilization. It will be up to them as to what they want to choose based on the predicted cost and time to go through with these changes to their current lines.

There is a trade-off between the different alternatives, more expensive alternatives will have greater system performance impact and will take longer to implement. But alternatives such as adding carts to the train are less costly and easier to install, so they can implement improvements quicker, but have lower system impact.

Learning how to hit the ground running

Kousoulas: We had never done this before. We’ve only learned about this type of work in class, it’s a pretty big shift from being in the classroom. We learned how to get up on our feet and keep going. How to ask the right people the right questions. Or maybe the wrong questions and they point you in the correct path.

Ennis: Like Miles said, you have to figure it out kind of on the fly, and that means going to our previous professors for guidance. Nobody’s telling us to do that. I think that realizing that was important. Dr. Rajendran was crucial in helping us access SIMIO software. Dr. [James] Noble, the course instructor, was very helpful too, and for any questions, he was there for us.

Curriculum is key

Oster: For our capstone the course that we took on using SIMIO, which is the simulation software we used, was very relevant and just general manufacturing knowledge came in handy. But all of our curriculum came into the project as well.

Mayyal: As Brian stated, the curriculum helped us with the project, particularly statistics, to know how to calculate confidence intervals, cycle time and efficiency. As well as what we learned in manufacturing classes.

Learn more about industrial engineering at Mizzou!

Read about other capstone projects here.