New Product Manufacturing Unit Cost Forecasting Using Integrated Case-Based Reasoning and Back Propagation Network approach ― The Case of the Mobile Phone

• Main Authors: Ming-Yu Fang, 方明裕
• Other Authors: Pei-Chann Chang
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/18054467068046240245

碩士 === 元智大學 === 工業工程與管理學系 === 96 === The global market scale of mobile phone is tending fast growth in recent years, which demonstrates stable upward growth in developed countries and significant growth in developing countries. High gross profit rate and the demand feature of selling low-price and high-volume products simultaneously have stimulated well-known mobile communication equipment manufacturers to pursue orders and profits. The know-how strategy pending on reasonable prices to win more order opportunities also becomes the desirable focus and study for the present industrial field. In this work, the research method is divided into two steps. The first step is to focus on the analysis of unit production cost by studying specified cases to obtain unit production cost formula and expert advice about the relative nature and quantitative factor. The second step is to take the above factors to integrated Case-Based Reasoning and Back Propagation Network forecast model. This process can be divided into two parts. The first one is to estimate particular quantitative factor by using nature factor to integrated Case-Based Reasoning and calculate MAPE value to confirm its erroneous value in the reasonable value. The second part is to take nature factor to Back Propagation Network forecast model to estimate its unit production cost. After the training, RMSE value has to be calculated to confirm its convergence value in the reasonable value and then calculate MAPE value in order to ensure its erroneous value in the reasonable value. The conclusion of the experiment proves that Case-Based Reasoning and Back Propagation Network forecast model can be used to estimate the erroneous value of unit production cost in the reasonable value. Finally, comparing MAPE values of this model and that of other five types of Case-Based Reasoning and Back Propagation Network, the conclusion indicates that this experimental research design obtains unit production cost in Case-Based Reasoning and Back Propagation Network. Take the research factor to the calculation and the outcome is lower erroneous value, which provides the correlation personnel with estimated references about mobile phone unit production cost.