A look back at an MSU project with GE Aviation

We take a look back at a consulting project from 2009, conducted by a Manufacturing Extension Partnership of Mississippi (MEP.ms) team from Mississippi State University. The client was GE Aviation, a General Electric company in the process of building a new facility to produce composite parts for jet engines.

Back in 2008, General Electric’s GE Aviation was in the process of building a 300,000-square-foot composites factory in Batesville, MS. A MEP.ms team from Mississippi State was brought in to design and put into application multiple discrete event simulation models before the plant was completed. The team used these models to “analyze and ‘optimize’ plant layout and performance by identifying and eliminating bottlenecks, improving the overall efficiency of the production line, evaluating the line’s sensitivity to product mix changes and evaluating product ramp-up scenarios.”

The project achieved more than $400,000 in cost savings, and the plant appears to be flourishing today. One hundred and ten people were employed at the facility when the simulation project was conducted, but the plant employs over 450 personnel as of April 2013.

The production facility initially produced composite fan platforms for aircraft engines, for use on such aircraft as the Boeing 777 and the Boeing 787 Dreamliner. The products are produced on a shared production line that was designed using lean manufacturing principals (the process is explained in a paper written by the team).

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Example jet engine platform.

According to the paper, a baseline FlexSim model of the facility was developed to help the facility’s team evaluate alternate system designs. The Mississippi State team worked closely with the facility to share their simulation modeling expertise and provide training. Each model run simulated the 374,400 minutes covered in a one-year period of plant operation, which totals 52 weeks of five 24-hour work days.

Discrete event simulation software excels at accounting for the impact of variability on a system, but there was no history of variability at the Batesville plant due to the prevalence of new processes in the system. The model was reconfigured several times for different variability levels so the plant team could see the effect on production performance. For example, 13 weekly product demand patterns were created to represent 13 possible product mixes; the simulation model estimated the time it would take to complete production for each pattern, and considered the different levels of variability on each scenario.

The paper authors reached the following conclusion in their paper:

“The model was an integral part of the facility design process. It was used as a decision support system to help designers quickly assess the performance of various alternative production configurations and resource allocations. One of the analyses conducted during the project was an examination of the sensitivity of manual processing times to various levels of variability. The analysis clearly showed the significant negative effect on system throughput and cycle time when even a relatively small amount of variability is introduced into the proposed lean manufacturing system. The model proved to be an effective design and planning tool.”

Look for the paper, “Use of Simulation Modeling and Analysis to Design New Production Process and Facility,” in the April 2014 edition of FlexSim Quarterly. Reprinted with permission of the MAESC.

Sources:

McDowell, Lucas, Allen Greenwood, and Travis Hill. “Use of Simulation Modeling and Analysis to Design New Production Process and Facility.” MAESC 2009 Conference. (2009).

Innovate Mississippi, “Manufacturing Extension Partnership of Mississippi.” Last modified April 30, 2010. Accessed February 26, 2014. http://www.mep.ms/ge.html.

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