太陽能是再生能源中成長最快速的一種。然而，太陽能產業目前面臨供大於求、顧客對於品質要求嚴苛等挑戰，使電池製造商在品質或是獲利方面皆接受嚴峻的挑戰。
太陽能電池的品質好壞常以電池的轉換效率作為判定之基礎。而太陽能電池具有以下兩種隨機性。在原料部分，各供應商所提供之晶片所產出之的轉換效率會有所不同。在晶片製造過程部分，使用不同的製程處方（recipe）則最終轉換效率亦不同。
電池成本結構中，購買晶片約占50%。而在電池的售價則是以轉換效率作為售價衡量標準，若每批電池有0.1-0.2%的轉換效率偏移，則導致售價差距US$0.0565。假設一筆訂單數量以10MW計，則轉換效率低於平均0.1%會至少損失US$56500。
因此，如何掌控原料端以及製程端的隨機性，藉此來降低原料成本並提升轉換效率，使公司能夠以最低成本來滿足顧客特定允收條件，是本研究之主要目的。
故本研究提出一使用兩階段模擬最佳化之方法。透過第一階段模擬最佳化來量化原料及製程對轉換效率之影響，並估計其機率分配參數。接著第二階段模擬最佳化則以第一階段模擬最佳化為基礎，並考量顧客允收條件下，求解下生產成本最小化的投料比例組合。最後，以現況之投料機制最為標竿進行比較，可發現兩階段模擬最佳化不論在任何情境之下，皆能以較低之成本來滿足顧客需求，且其改善幅度最少為15%。因此證明本文所提出之方法，能夠有效地來提高企業滿足顧客需求以及獲利之能力。

Green energy is the main focus in the world recently, in particular, solar energy is one of the rapid-growing renewable energy. However, the government’s protection policies lead to a supply-larger-than-demand situation in supply chains. As a result, the market clearing price drops dramatically. In addition, the customers’ requirements for quality and acceptance become more and more serious.
Due to a rapid change of environments and customer requirements the oversupply leads to price drop and high customer’s requirement. It becomes a challenging issue to generate high quality product with lower cost in solar cell manufacturing industry.
The quality of solar cell depends on the efficiency of conversion, which defines the ratio of transforming solar energy to electrical energy. Currently, the most popular product in the market is polycrystalline silicon solar cell, and its efficiency of conversion（EC） is between 16% and 18%. The higher the efficiency of conversion, the more power it can generate. In this field, the customer order is based on the number of Watt as the unit. Thus, the higher the productive efficiency of conversion, the less the cells we need to produce.
In particular, the main cost structure of solar cell presents the 48.57% for silicon wafer, and it’s around a half of total production cost. It reveals an opportunity of cost reduction for the gap between the production quantity and total Watt of the order. Thus, how to find a cost-effective way to give a tradeoff among production cost, the number of wafer release, and the number of Watt from customer orders is eager to answer.
In the other side, the production process of solar cell presents stochastic characteristics. Two sources contribute to a stochastic system: material and process. First, the material from different suppliers may present different purities of silicon, and then it will result in a different efficiency of conversion in final product. Second, the wafer passes through all the manufacturing process, the combination of recipes may significantly affect the efficiency of conversion.
Simulation model is an approach to evaluate the stochastic characteristics in a complicated system. Comparing with mathematical programming, the simulation optimization model could solve the problem and derive an approximate optimal solution efficiently through some meta-heuristic algorithms when a growth of problem complexity. Thus, simulation model is more useful and popular in practice.
Therefore, the study proposes a two-phase simulation optimization (SO) model to support order allocation of suppliers for cost reduction. First-phase SO quantifies the stochastic effects of efficiency of conversion affected by material (eg. silicon wafer) and process (eg. Recipe）, and estimates the parameters of probability distribution with respect to wafer and process. Second-phase SO optimizes the portfolio cost of order allocation given customer requirements based on the result of first-phase SO.
And then, we comparing to the original portfolio decision method, the result show that our two-phase SO method had greater performance, and the improvement of cost almost 8.98%.
Thus, the study focuses on changing suppliers’ order allocation for cost reduction in the stochastic system of solar cell manufacturing and enhance the core competence.

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