Optimisation and Control of Engineering Change Schedules in the Automotive Industry with Metaheuristics and Machine Learning
暫譯: 汽車產業工程變更排程的優化與控制：以元啟發式演算法與機器學習為基礎

Adaptation and change are imperative for products and companies to remain competitive. Managing these changes, however, is increasingly difficult and requires thorough planning and management. Especially in complex production systems, the efficient handling of these engineering changes becomes a competitive edge. This book embarks upon the task to manage the increasingly difficult optimisation and control of engineering changes through artificial intelligence. Based on a knowledge base gained from a systematic literature review, it is shown how AI methods can be applied to resolve challenges faced in production environments. Based on metaheuristic algorithms, optimal EC effectivity dates are determined, which are then validated and controlled by machine learning based business process monitoring. These advances provide significant support for change coordinators and material planners by reducing administrative effort end ensuring complexity control.