半導體設備商客服工程師（Customer Engineer, CE）的每日派工，會直接影響晶圓製造廠設備故障排除效率與產線運作穩定性。現行派工決策多仰賴管理者之主觀經驗，然而面對精密且複雜的設備故障排除任務，如何以較系統化的方式評估工程師能力並進行人力配置，已成為半導體設備商派工管理的重要課題。本研究旨在建構一套結合多重權重與排序方法之派工決策模型，以作為客服工程師每日派工之決策輔助依據。本研究採用多準則決策（Multi-Criteria Decision Making, MCDM）方法建立模型架構，於權重設定階段結合層級分析法（Analytic Hierarchy Process, AHP）與排序準則法（Rank Order Criteria, ROC）確立評估構面之重要性，評估構面涵蓋硬體能力、軟體能力、客戶溝通、跨部門合作與製程原理等五大項；於方案評估階段則導入逼近理想解排序法（Technique for Order Preference by Similarity to Ideal Solution, TOPSIS）與折衷排序法（Vlse Kriterijumska Optimizacija I Kompromisno Resenje, VIKOR），進行工程師方案排序。透過兩種權重方法與兩種排序方法之交互整合，本研究形成四種分析組合，並進一步應用於軟體故障排除、硬體故障排除、軟硬體綜合故障排除與跨部門支援等四種實務情境模擬。研究結果並透過產業專家之李克特量表（Likert Scale）評估模型之適用性與可行性，結果顯示本研究所建構之派工決策模型可提升決策透明度，降低對單一管理者經驗判斷之依賴，並提供半導體設備商一套具備系統性與實務參考價值之每日派工決策輔助工具。

The efficiency of daily dispatching for Customer Engineers (CEs) at semiconductor equipment vendors is critical to timely equipment troubleshooting in wafer fabs. Since traditional dispatching decisions often rely heavily on managers’ subjective experience, this study develops an MCDM-based Dispatch Decision Model to support manpower allocation for complex and technically demanding troubleshooting tasks. The proposed model applies the Analytic Hierarchy Process (AHP) and Rank Order Criteria (ROC) methods to determine the weights of five key evaluation dimensions: Hardware Capability, Software Capability, Customer Communication, Cross-departmental Collaboration, and Process Principles. For engineer alternative evaluation, TOPSIS and VIKOR are introduced as ranking methods. By cross-combining the two weighting methods with the two ranking methods, four analytical combinations are formed and simulated across four practical scenarios: software troubleshooting, hardware troubleshooting, integrated software/hardware troubleshooting, and cross-departmental support. Based on Likert-scale evaluations by industry experts, the results indicate that the proposed model is applicable to practical dispatching scenarios, enhances decision transparency, and reduces reliance on individual managerial experience. This study provides semiconductor equipment vendors with a scientifically grounded and standardized decision support model for daily CE dispatching.

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