Florida Tech Assisting in Manufacturing Optimization
Florida’s Space Coast has seen a resurgence in the space industry over the past five years. Companies such as United Launch Alliance and SpaceX have are providing a source for the nation’s increased demand for U.S.-based commercial and private spaceflight.
As more operations expand on the Space Coast, their ability to keep on deadline is vital – and Florida Tech is helping to ensure the manufacturing process is optimized for efficiency and success.
Beshoy Morkos, associate professor of mechanical and civil engineering, received a grant from an aerospace manufacturer and spaceflight services company located near Kennedy Space Center to conduct a manufacturing optimization and simulation analysis. The grant, worth nearly $130,000, called for the analysis of how the company can use resources, such as space in its facility, number of employees, and size and quantity of machines, in the most efficient ways possible.
The study uses various optimization and event simulation models to determine peak capacity and optimum scheduling – a capability that will allow executives justification for making resource-related decisions.
“On one side, you have your resources, and on the other side is how you allocate them, which will drive your scheduling,” Morkos said. “You know your scheduling, and the goal is for it to be the most aggressive, so can I then use that to work backwards to determine what my resource allocation should be?”
In the manufacturing industry, learning curves – an industrial tool or formula for the expected reduction of unit costs for large quantity production of components – have an impact on production rate. Factors ranging from employees’ experiences to shift times can affect production estimates. During the research, Morkos and his team modeled learning curves down to specific operations, allowing for a deeper analysis of production rate. They found that the exclusion of what may seem to be trivial variables could in fact have a substantial effect downstream.
The team’s findings, that a manufacturing capacity model that optimizes scheduling, provided company engineers an accurate, all-encompassing tool for determining when the flight vehicle will be complete.
“The findings played a significant role, which can now translate to hundreds of thousands of dollars, because that could mean having the rocket ready last week versus this week,” Morkos said.
For instance, while Morkos and his team developed solutions to optimize production, they also discovered the company needed to increase its workforce by 20 percent in order to account for the amount of manufacturing equipment and production goals.
Morkos and his team look to have more phases of the project, moving beyond doing projections and into simulations. This would give officials at the aerospace manufacturer a step-by-step look into the manufacturing optimization process.
By developing various models, the team’s research is focused on providing valuable information companies can use to maximize productivity and increase revenue.
“Regardless of the company, whether they are making rockets or pencil sharpeners, it’s about how do we take information about the design and manufacturing process and use that to help us to make tools that are informative to engineers,” Morkos said.