螺絲工廠設置AGV搬運系統規劃之模擬分析
|
| 摘要 在現代社會與經濟發展迅速的時代，由於大眾的需求已逐漸改變，故產品製造的生態已有著大幅變化；但傳統製造業卻跟不上社會的腳步。為了能在現代市場的需求變化下繼續生存，各家傳產業紛紛投入現代科技以求轉型如大數據分析、工廠智慧化生產等等，否則就可能慘遭淘汰。 鑑於上述之情況，本研究將針對個案工廠以Flexsim軟體模擬導入AGV(Automated Guided Vehicle)無人搬運車。模型設定之部分，模擬時間範圍為2023年8月並扣除周末後故模擬天數為23天。將使用三項控制因子：三種派車法則(最近車輛、最先完工及隨機派車)、AGV車輛數(1~5台)及兩種接單生產情境(原始訂單量及增加50%訂單量)，並觀察四項績效指標：搬運總距離、搬運總時間、機台平均等待總時間及加工總時間進行模擬，共有30種組合以找出適合工廠較佳的配置。
關鍵字：Flexsim、系統模擬、無人搬運車、AGV。 ABSTRACT In the rapidly evolving modern society and economy, the landscape of product manufacturing has undergone significant changes due to the shifting demands of the populace. However, the traditional manufacturing sector has struggled to keep pace with these societal shifts. To sustain their existence amidst the changing demands of the modern market, numerous traditional industries have embarked on a journey of transformation by integrating modern technologies such as big data analytics and intelligent manufacturing processes, without such transformations, they risk being eliminated. Given the context, this study focuses on a case study involving the use of Flexsim software to simulate the implementation of Automated Guided Vehicles (AGVs) in a factory setting. The simulation covers a period of August 2023, excluding weekends, resulting in a total of 23 operational days. It employs three control factors: three vehicle dispatch rules (closest vehicle, first to finish, and random dispatch), a range of AGV units (from 1 to 5), and two production scenarios (original order volume and an increase of 50% in order volume). The study observes four performance indicators: total transportation distance, total transportation time, average total waiting time for machines, and total processing time. A total of 30 combinations are simulated to identify the optimal configuration for the factory's improved performance. KEYWORDS: Flexsim; System Simulation; Automated Guided Vehicle. |