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Open AccessArticle

Product Lifecycle Management as Data Repository for Manufacturing Problem Solving

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Exide Technologies SAS, 5 allée des Pierres Mayettes, 92636 Gennevilliers, France
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Mechanical Engineering Department, Polytechnic University of Madrid, Jose Gutierrez Abascal 2, 28006 Madrid, Spain
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German Research Center for Artificial Intelligence (DFKI), Trippstadter Straße 122, 67663 Kaiserslautern, Germany
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Institut für Informatik, University of Hildesheim, Universitätsplatz 1, 31141 Hildesheim, Germany
*
Author to whom correspondence should be addressed.
Materials 2018, 11(8), 1469; https://doi.org/10.3390/ma11081469
Received: 2 July 2018 / Revised: 9 August 2018 / Accepted: 14 August 2018 / Published: 18 August 2018
(This article belongs to the Special Issue Special Issue of the Manufacturing Engineering Society (MES))
Fault diagnosis presents a considerable difficulty to human operators in supervisory control of manufacturing systems. Implementing Internet of Things (IoT) technologies in existing manufacturing facilities implies an investment, since it requires upgrading them with sensors, connectivity capabilities, and IoT software platforms. Aligned with the technological vision of Industry 4.0 and based on currently existing information databases in the industry, this work proposes a lower-investment alternative solution for fault diagnosis and problem solving. This paper presents the details of the information and communication models of an application prototype oriented to production. It aims at assisting shop-floor actors during a Manufacturing Problem Solving (MPS) process. It captures and shares knowledge, taking existing Process Failure Mode and Effect Analysis (PFMEA) documents as an initial source of information related to potential manufacturing problems. It uses a Product Lifecycle Management (PLM) system as source of manufacturing context information related to the problems under investigation and integrates Case-Based Reasoning (CBR) technology to provide information about similar manufacturing problems. View Full-Text
Keywords: product lifecycle management (PLM); manufacturing problem solving (MPS); fault diagnosis; smart factory; process failure mode and effect analysis (PFMEA); case-based reasoning (CBR) product lifecycle management (PLM); manufacturing problem solving (MPS); fault diagnosis; smart factory; process failure mode and effect analysis (PFMEA); case-based reasoning (CBR)
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Camarillo, A.; Ríos, J.; Althoff, K.-D. Product Lifecycle Management as Data Repository for Manufacturing Problem Solving. Materials 2018, 11, 1469.

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