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2021 | OriginalPaper | Chapter

Proposed Algorithm to Digitize the Root-Cause Analysis and 8Ds of the Automotive Industry

Authors : Brenda-Alejandra Mendez-Torres, Patricia Cano-Olivos

Published in: Applied Informatics

Publisher: Springer International Publishing

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Abstract

As we adapt to our new post pandemic reality, many activities are being and have been replaced or modified. Companies need to adapt to digitalization as a new way of interacting with staff and customers. The challenge concerns the management of information since it must be aligned to the trends of Engineering 4.0 to solve everyday problems. This article analyzes the quality tool QRCI (Quick Response Continues Improvement), a solution-based method used by automotive company Faurecia for solving production problems related to 5M (Machine, Raw Material, Labor, Environment and Method) the investigation describes the relationship between QRCI and PPAP (Production Parts Approval Process) a standard with technical information to ensure the product quality. During our investigation we identified a disruptive communication between QRCI & PPAP and we propose to include both tools in the same platform and replace the troubleshooting in QRCI done by humans to artificial intelligence analysis, in order to reduce misperception, improve the analysis time and communicate the results to PPAP in real time, reducing operating costs and increasing productivity and quality since the improvement is continuous. Therefore, the fulfilment of the certifications is ensured through an integrated prevention model. A robust system inspires confidence in suppliers and customers based on the effectiveness and efficiency of the production processes.

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Metadata
Title
Proposed Algorithm to Digitize the Root-Cause Analysis and 8Ds of the Automotive Industry
Authors
Brenda-Alejandra Mendez-Torres
Patricia Cano-Olivos
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-89654-6_17

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