應用良率學習曲線於太陽能電池產業之投料規劃

Abstract

在環保議題與資源耗竭問題的推動下，加強發展「再生能源」及「綠色能源」使太陽能光電(Photo Voltaic, PV)產業備受市場關注。太陽能電池產業為技術、資本、自動化程度高的科技產業，且由於自動化程度高的關係，太陽能電池廠並不注重學習效果的影響，然而良率的學習現象已被證實確實存在，且其它產業也證明了應用學習曲線可幫助快速累積生產、改善製程、修訂生產日程規劃及決定產品訂價策略等。因此，本研究之主要目的即是針對太陽能電池廠之實際產出資料，建構一個良率學習曲線模型，以探討在考量良率學習效應下，如何決定生產日程投料規劃之修正策略，以做為太陽能電池產業管理階層的參考依據。

Under the issues of environmental protection and depletion of the natural resources, developing “renewable” and “green power” gains a lot of attention in Solar PV (Photo Voltaic) industry. Solar PV industry is a highly automatic industry with huge capitals and high technology. Due to its highly automation property. Solar Cell plant generally pays less attention on the learning effect. However, the learning effect of yield is indeed existed. Moreover, the learning curve has demonstrated to be useful for accumulating production experiences, improving process, planning production scheduling, pricing tactics, and etc. Therefore, the main objective of this study is to construct a learning curve of yield using the data obtained from a Solar Cell plant and utilized it to help Solar Cell manufacturer to make proper amending policy on its production scheduling.