工具機整機AI動態出廠檢測技術

傳統工具機生產履歷與品管檢測多以靜態精度與幾何精度為主，對於動態性能的檢驗極為缺乏，無法有效檢測預壓力、接合面狀態、鎖緊力、地角承重均勻性…等關鍵組裝變數。本文開發目標為建立工具機AI組裝檢測平台，以動態響應FRF為指標進行組裝品質判定，透過智慧化AI檢測確保產線機台加工性能的出廠均一性，提升產品組裝品質、加工能力與設備穩定性，降低售服比例，提升工具機品牌形象，才是擺脫價格競爭的解決方案。

Traditional machine tool production records and quality inspections have primarily focused on static accuracy and geometric precision, while dynamic performance assessment remains insufficient. Consequently, critical assembly variables such as preload, joint surface condition, clamping force, and base load distribution cannot be effectively evaluated, often resulting in inconsistencies in machining performance and equipment reliability. To address this challenge, this study proposes an AI-based assembly inspection platform for machine tools, utilizing the dynamic response frequency response function (FRF) as the core indicator for assembly quality assessment. Through intelligent AI inspection methods, the platform ensures consistent machining performance of production-line machines upon delivery, thereby improving product assembly quality, machining capability, and equipment stability while reducing after-sales service demands. Moreover, the platform enhances the brand image of machine tool manufacturers by offering a solution to break free from price-based competition, thereby advancing intelligent manufacturing and strengthening high-value competitiveness in the global market.