A study on the lean pull system for fishing-net manufacturing using simulation optimization

• Main Authors: Chia-Lin Ho, 侯佳伶
• Other Authors: Ta-ho Yang
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/72480700117224078827

碩士 === 國立成功大學 === 製造工程研究所碩博士班 === 97 === The fishing-net industry is in Make-to-order environment. Different order form its net material, the size and the knitting way are all different. Because in demand uncertainty, using push system will cause the mass work-in-process（WIP）, therefore needed other way avoid the situation. This paper consider about product flowing type for non-fixed（calls the variable unitload）on fishing-net manufacturing, and set up two kind of unit-load（area and weight）. The proposed a lean pull system, combining Kanban system and Supermarket, which is applying value stream mapping methodoloty in a fishing-net manufacturing case study under demand uncertainty. By using simulation optimization to solve supermarket design problem,with improves the waste which WIP in the system, enhances the service level. This paper also proposes to use Womack’s lean thinking and Rother’s 7 guiding principles procedure as applying the lean pull system. The proposed procedure is illustrated to begin value, to address the critical improvement point through the current value stream mapping, and to draw the future value stream mapping for implement the improved alternative. Finally, implemented the proposed procedure to a real-world fishing-net manufacturing case study. After compared current-state map and future-state map, the results indicated that the optimal solution could reduce the WIP respectively from 63971 kg reductions to 25300 kg, improves 60.45%, and 57700 kg reductions to 25300 kg, improve 56.15%. The service level respectively from 67.62% increase to 88.42%, improves 20.80%, and 66.93% increase to 88.42%, improves 21.4%. The cycle time from original 44.86 days and 41.15 days, reduces to 33.51 days, improves 25.30% separately and 18.57%.