Contribution of celluar manufacturing design to the reduction of production lead time utilizing simulation modeling

The ever-increasing competition in the market place is the driving force behind the rising emphasis on embracing Cellular Manufacturing Systems and their methods in effort to shorten the product lead time. One such method is Lean Production Systems (LPS) which are JIT based production systems that consist of manufacturing cells as their building blocks. The research in this thesis addresses and assesses the impact of some of the critical parameters involved in the design of these cells on cycle times.

Simulation models are developed for various situations to evaluate several issues that are believed to influence the performance of manufacturing cells. These include process/product variation, the product mix, demand increases,setups under random arrivals, SOH, and defect rates. Cell cycle times and line efficiency are the response variables used to measure the cell's performance. The results of the simulation models have shown that product p cycle time increases significantly with increased process variation, increased demand, defect rates,and stochastic arrivals which increases setups. While cycle times have increased, the cell's line efficiency has statistically decreased.Other factors such as the product mix, SOH, and increased product variation are shown to have no significant impact on cycle times and the cell's line efficiency was also shown to improve under these conditions. An overall improvement in the cell's performance is also shown to occur with minimized variation in the cell's process.