虛實整合之加工精度與效能優化智能監控系統

本研究發展出一套可在加工前根據實驗建模與演算法同時優化精度、效率及耗能，進而產出適當CNC加工程式的虛實整合系統。該系統也與知識雲端資料庫(iKM)整合，建立雙向資訊收集模組與iKM分析引擎與生產優化模組，使可進一步優化加工程式，以避免加工異常的發生，其中整合多種線上加工監控模組(含:切削異常模組、精度指標模組、機台效能優化模組)，執行不同演算法分析以建議最佳的加工參數，同時也會回傳相關設計資料至iKM雲端資料庫，介面系統以Visual C#建立並串接整合所有功能模組及加工機台，收集模擬結果、加工參數與實際切削結果，持續更新iKM的專家資料庫，為未來設計優化的基礎，最後以實際加工驗證比較有經過優化模組與無經過優化模組兩者之差異性，例如以鋁材料之實驗，加工時間從2.6分鐘縮短至1.7分鐘，同時表面精度從0.97μm提升至0.49μm，證明此系統確實可達到精度與效能同步優化之成效。

關鍵字

iKM ； CPS ；工具機；雲端；虛擬平台

並列摘要

This study is to develop a system that we can build an optimization of NC programs and predict abnormal processing at pre-process by modeling and algorithm. The system is also integrated with the Intelligent Knowledge Management (IKM) to build a two-way information gathering module and IKM analysis engine and production optimization module to further optimize machining programs to avoid machining anomalies, including the integration of a variety of in-line process control modules (Abnormal Monitoring Control module, Roughness module, Energy Consumption module.). A large of data collected from each module, and each module will use these data to perform different algorithms analysis. After that, the best NC processing will be obtained from the optimization module. Finally, the actual machining verification Compare the difference between optimized module and non-optimized module to prove the reliability of the system. For example, in the experiment of aluminum materials, the processing time was shortened from 2.6 minutes to 1.7 minutes while the surface accuracy was improved from 0.97μm to 0.49μm, which proves that the system can achieve the effect of simultaneous optimization of accuracy and efficiency.

並列關鍵字

iKM ； CPS ； Machine ； cloud ； Virtual platform

參考文獻

[30] 王貫宇, “複合指標加工參數優化及刀具臨界壽命監控智慧系統整合研究”, 私立中原大學機械工程研究所碩士論文,2016。

[33] 蔡柏承, “新線上顫振監控系統與切削穩定圖輔佐抑制顫振之研究”, 私立中原大學機械工程研究所碩士論文, 2014。

[34] 何建鐽, “CNC工具機線上切削異常智能監控與製程優化輔助系統之研究”, 私立中原大學機械工程研究所碩士論文, 2011。

[1] Jens F., Heiner Lasi, Hans-Georg Kemper, “Simulation of production processes involving cyber-physical systems”, Procedia CIRP 62 ( 2017 ) 577 – 582

[2] Jeongcheol Lee, Sungbum Jun, Tai-Woo Chang, and Jinwoo Park, “A Smartness Assessment Framework for SmartFactories Using Analytic Network Process”, Sustainability 2017, 9, 794.

國際替代計量

虛實整合之加工精度與效能優化智能監控系統

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