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Productivity Improvement in Manufacturing Systems Through TPM, OEE and Collaboration Between Maintenance and Production: A Case Study

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Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems (APMS 2021)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 634))

Abstract

The following paper describes a project where Total Productive Maintenance (TPM) methodology was used in order to improve an automotive industry production line availability and quality. After performing a diagnosis, major flaws were revealed about maintenance and production communication, as well as missing information about the production of defects and maintenance interventions. It was necessary to solve these problems before being able to analyse production inefficiencies, define and implement improvement actions. This project showed the significant impact on costs and quality that can be achieved using TPM, OEE and collaboration between production and maintenance. But beyond that, it showed that despite the industry 4.0 being on the agenda, there is a low use of communication technologies and, therefore, significant gains can still be achieved through basic analysis of recorded data if they are properly organized and standardized. It appears that special attention must be paid to the collection of data, to ensure its proper use for decision making.

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Costa, R., Lopes, I. (2021). Productivity Improvement in Manufacturing Systems Through TPM, OEE and Collaboration Between Maintenance and Production: A Case Study. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-030-85914-5_28

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  • DOI: https://doi.org/10.1007/978-3-030-85914-5_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85913-8

  • Online ISBN: 978-3-030-85914-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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