近年來，電子資訊產品的市場需求快速成長，電腦組裝常常被要求快速反應市場的需要，所以要如何快速、正確的產生產品的裝配規劃，在生產計劃中是很重要的。電腦組裝工廠有前置時間(lead time)極短之特性，使得電腦組裝工廠之指派方式難以規劃。其次，電腦組裝因為其外型之緣故，無法進行自動化或半自動化組裝，故皆為純人力組裝，因此需要考量學習曲線(learning curve)於指派之規劃。當作業員所分派之組裝作業之種類加倍時，因為熟練度不足之緣故，其所耗費之組裝時間超過兩倍組裝單一作業之時間，這便是學習曲線中規模效應所造成之影響。因此，如何在考量人力成本與makespan間選擇適宜之規模大小，便是電腦組裝規劃之問題所在。本研究希望能針對電腦組裝指派發展出一即時模式，同時考量人力成本與makespan之多目標規劃，即時決策訂單分割與否、組裝線數量、組裝步驟與作業員之指派並配合基因演算法求解，以作為實際電腦組裝工廠之參考。

In recent years, needs of electronic products grow rapidly. For the PC assembly, immediate response to the market needs is required. In the production planning, fast and precise product assignment design is, thus, very important. The characteristics of extreme short lead time of computer assembly factories makes the assignment difficult to be planned. In addition, because of the external form of computer, automatic or semi-automatic assembly is not possible. Manual assembly is the only method. Therefore, for the assigned program, learning curve should be taken into consideration. The size effect has influence on learning curve. For example, when the assigned assembly operation of operator varies, it consumes twice the time that a single machine requires. It is due to lacking adaptation. Thus, the main issue of computer assembly program is about choosing an adequate scale between manual cost and makespan.
This research targets on the development of a real-time model of computer assembly assignment. In order to be the reference of actual computer assembly factories, multiple aims arrangement between manual cost and makespan, decision of whether split the order, the quantity of assembly lines, the process of operation, and the assignment of operators are to be considered. At last, genetic algorithms will be applied in order to obtain the result.

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