Using the Taguchi Paradigm in Simulation Experiment for Optimum Lunch-Box Manufacturing System Design

• Main Authors: Cheng-An Hsiao, 蕭正安
• Other Authors: Jing-Jung Chen, Ph. D.
• Format: Others
• Language: zh-TW
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/24549160593860569671

碩士 === 東海大學 === 食品科學系 === 87 === ABSTRACT This study describes the use of Taguchi Paradigm for improving the manufacturing productivity. On theoretical and practical points of view, most recent approaches in this study concern development of the economical theory of decreasing return to scale to support the concept of the second order quality loss function in Taguchi algorithms. The experimental design and simulation model tool is described and its use is illustrated with the optimization productivity of a boxed lunch plant product line. The experiment target of this study is a large-scale boxed lunch plant. This plant was modeled by using AweSim network simulation language. The performance is measured according to the throughput putt of the plant. As is typically the objective here is the maximization of throughput. The results of system analysis indicated that the bottleneck is the inappropriate start cooking time of five lunch ingredients. The experiment chosen five lunch ingredients start cooking time as main factors, and four cooking time as different levels of the factors. The L64(421) orthogonal arrays shows that 64 computer simulation runs must be tested. The Signal-noise ratio has been utilized in the criteria of obtaining optimum levels of start cooking time for each lunch ingredient. The result of the study indicated that the productivity of the lunch plant will be increased largely by just change the lunch ingredients start cooking time. The simulation experiment showed 7.63%increase in the throughout compared to the plant original level and 1.5%increase in the throughput compared to best case by using sensitivity analysis. Key words: simulation, Taguchi method, boxed lunch, Experimental design, S/N ratio, optimization.