Optimisation and Control of Engineering Change Schedules in the Automotive Industry with Metaheuristics and Machine Learning

Author:   Ognjen Radišić-Aberger
Publisher:   Springer Fachmedien Wiesbaden
ISBN:  

9783658510732


Pages:   283
Publication Date:   22 February 2026
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Optimisation and Control of Engineering Change Schedules in the Automotive Industry with Metaheuristics and Machine Learning


Overview

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.

Full Product Details

Author:   Ognjen Radišić-Aberger
Publisher:   Springer Fachmedien Wiesbaden
Imprint:   Springer Vieweg
ISBN:  

9783658510732


ISBN 10:   3658510730
Pages:   283
Publication Date:   22 February 2026
Audience:   College/higher education ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Author Information

Ognjen Radišić-Aberger works in production planning. His academic research focuses on AI approaches to optimise production processes and production management.

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Latest Reading Guide

MRG 26 2

 

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