一些製造行業試圖通過使用自動材料處理系統 (AMHS) 來減少運輸浪費，這實際上可以增強製造區域生產線中原材料從一個位置到另一個位置的運輸。此外，運輸和作業流程問題是生產線瓶頸的主要原因，因為一些生產站需要等待在製品（WIP）交付。
無人搬運車 (AGV) 運輸過程需要對工廠的物理基礎設施和模擬進行交通控制設置，同時可以幫助展示和幫助評估可能的缺陷，這些缺陷可以在生產的實際工作流場景中加以改進線。實驗設計 (DOE) 在發現和解釋在經常作為假設以反映或描述變化的條件下的信息變化方面發揮著巨大作用。
採用簡化的無人搬運車參數實現仿真模型。模型開發包括並在以下結構的假設下指定：系統規範→機器規範→AGV規範→離散事件模擬模型→實驗設計→性能指標分析（PI）。
為了準確反映評估上述問題的替代方案，本研究提出了上述模型和基於績效指標的分析。選擇方差分析 (ANOVA) 結果來分析影響性能指標的不同因素，表明通過使用階乘 ANOVA 測試結果，主要利用 1-way 交互作用和 2-way 交互作用來建立關係之間的比較這些因素：作業流程時間和 AGV、AGV 利用率、AGV 數量和平均等待時間。

Several manufacturing industries try to reduce transportation waste by using automatic material handling systems (AMHS) which in fact could enhance the transportation of raw materials from one location to another in the production line of a manufacturing area. Furthermore, the issue with transportation and Job flow is the main reason for bottlenecks in a production line because some production stations need to wait for the work-in-progress (WIP) to be delivered.
Automated Guided Vehicles (AGVs) transportation process needs a set-up of traffic control over a factory’s physical infrastructure and simulation, at the same time, could help showcase and help evaluate possible deficiencies that can be improved in the real job flow scenario of the production line. Design of experiments (DOE) plays a huge role in finding and explaining variations of information under conditions that are regularly put as a hypothesis in order to reflect or describe the variation.
A simulation model is implemented by adopting simplified automated guided vehicles parameters. The model development consists and is specified on the assumptions of the following structure: System specification →Machine specification→ AGV specification → Discrete Event Simulation Model → Experimental Design → Analysis of Performance indicators (PI).
To precisely reflect an alternative for evaluating aforementioned issues, this study proposes the model stated above and an analysis that is based on the performance indicator. Analysis of Variance (ANOVA) results are chosen to analyze different factors affecting the performance indicator and show that by the use of the factorial ANOVA test results, 1-way interactions and 2-way interactions were mainly utilized to establish a comparison between the relationship of these factors: Job Flow Time and AGVs, AGV Utilization, number of AGVs and average Waiting Time.

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