Performance improvement of a multi product assembly shop by integrated fuzzy simulation approach
This paper presents an integrated fuzzy simulation approach for performance improvement of assembly shops with ambiguous and uncertain parameters. The basic subject of simulation is the probabilistic approach to describe real world uncertainty. However, in several cases, there is not sufficient information to build the corresponding probabilistic models or there are some human factors that prevent us from doing so. In such conditions the statistical and mathematical tools of fuzzy set theory may be successfully used. The design and superiority of fuzzy simulation is discussed for an actual large complex multi product assembly shop. This paper applies t test for evaluating the fuzzy simulation results versus true production rate of the assembly shop. Results show that production rates calculated by fuzzy simulation are closer to true production rates than that of conventional simulation. Moreover, fuzzy simulation is used to improve the performance of assembly shop by considering production constraints, system limitations and desired targets. This is the first study that uses fuzzy simulation for performance improvement of a multi product assembly shop.
performance improvement multi product assembly shop fuzzy simulation intelligent simulation fuzzy parameters