Because the lifecycles of consumable electronic products are very short nowadays it has become very difficult for original equipment manufacturers to precisely prepare materials for production In this paper a real case of a worldwide leading company in the integrated circuit (IC) assembly industry is revealed To avoid specific materials from being idle stock forecasting customer’s demand has become an important strategy for the firm under consideration However it is almost impossible to collect enough data to build robust forecasting models because of the short product lifecycles Over the past two decades the grey model (GM) has been shown to be effective tools to deal with short-term time series data To further enforce the effectiveness of data uncertainty treatment for dynamic IC industries a novel GM model is developed based on a fuzzy-set concept called fuzzy-based GM (FGM) In FGM short term series data is fuzzified to form a fuzzy time series for building GM models where the final prediction is aggregated by the predictions of the GM models with proposed weights The experimental results for the real case and a public dataset indicate that FGM outperforms GM and thus has practical value in tackling the real case
Date of Award | 2019 |
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Original language | English |
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Supervisor | Der-Chiang Li (Supervisor) |
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Developing Fuzzy Grey Models to Forecast Customer Demand of Substrates in the Integrated Circuit Assembly Industry
晉民, 蘇. (Author). 2019
Student thesis: Doctoral Thesis