高科技產品的市場需求始終隨著產品規格的變化而改變，為了在市場中具有競爭力，該產線系統必須兼顧靈活性，並且在面對大量客製化時，產線可以重新配置。彈性裝配線 (flexible assembly line) 可實現高效率的混合性生產，其需要縝密的系統設計與規劃，以利充分利用資源，本案以圖形處理器 (graphic processing unit, GPU) 裝配線為例。由於智能體基的模擬 (agent based simulation, ABS) 富有靈活性及可擴展性，因此本研究採用 ABS模型應用在FAL中。本案擬議框架涵蓋三大部分：實際環境，虛擬環境及評估分析，透過智能體基的模擬模型詳細闡述 GPU裝配線中的排序與調度性能，並使用柏拉圖最適分析解決零件延遲和生產量之間的衝突。

Market demands of high-tech products always evolves over time by product specification. To be competitive, a production system needs to be flexible and reconfigurable as facing mass-customization. Flexible assembly line (FAL) enables mixed production with high efficiency. One example is graphic processing unit (GPU) cards. FAL requires comprehensive system design and scheduling to fully utilize the resources. This study adopts agent based simulation (ABS) modelling for an FAL because of the abilities of ABS in flexibility and scalability. The proposed framework consists of three parts: real environment, virtual environment, and evaluation and analysis. This study elaborates sequencing and scheduling performances in the GPU-card assembly line by using agent-based simulation modelling. Pareto frontier analysis is conducted to resolve conflicts between part tardiness, utilization, throughput.

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