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2024 | OriginalPaper | Chapter

Artificial Intelligence Decision Systems to Support Industrial Equipment Manufacturing

Authors : Beatriz Andres, Miguel Angel Mateo-Casali, Juan Pablo Fiesco, Raul Poler

Published in: Proceedings of the 17th International Conference on Industrial Engineering and Industrial Management (ICIEIM) – XXVII Congreso de Ingeniería de Organización (CIO2023)

Publisher: Springer Nature Switzerland

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Abstract

This article discusses how integrating artificial intelligence (AI) into Industry 4.0 can promote sustainability and resilience in production systems. It addresses the lifecycle manufacturing concept, which aims to minimise waste and reduce the environmental impact of manufacturing operations. This paper focuses on the specific machine tool production sector and how AI technology can optimise production processes by reducing downtimes and improving overall manufacturing efficiency. Accordingly, the article aims to identify the needs that industrial equipment manufacturers have during the replenishment, production and delivery processes, and how AI could fulfil these needs. By leveraging AI technologies, manufacturers can significantly improve efficiency, profitability and customer satisfaction, which results in improved performance and business growth. The paper also introduces European HORIZON project AIDEAS, which aim to develop AI technologies to support the manufacturing phase of the industrial equipment life cycle.

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previous chapter Single-Station Unrelated Parallel Machines Scheduling Problem: A Case Study in a Real Factory

next chapter Optimising Machinery Utilisation by Applying Artificial Intelligence

AIDEAS. AI Driven Industrial Equipment Product Life Cycle Boosting Agility, Sustainability and Resilience. European Union’s Horizon Europe research and innovation programme under grant agreement No. 101057294 (2022)

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Title: Artificial Intelligence Decision Systems to Support Industrial Equipment Manufacturing
Authors: Beatriz Andres
Miguel Angel Mateo-Casali
Juan Pablo Fiesco
Raul Poler
Publisher: Springer Nature Switzerland
Book: Proceedings of the 17th International Conference on Industrial Engineering and Industrial Management (ICIEIM) – XXVII Congreso de Ingeniería de Organización (CIO2023)
Print ISBN: 978-3-031-57995-0

Electronic ISBN: 978-3-031-57996-7

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-3-031-57996-7_75

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