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PLM Applied to Manufacturing Problem Solving: A Case Study at Exide Technologies

  • Alvaro Camarillo
  • José RíosEmail author
  • Klaus-Dieter Althoff
Chapter
Part of the Decision Engineering book series (DECENGIN)

Abstract

This chapter presents a case study of a prototype Knowledge Management system that supports the process of Manufacturing Problem Solving in a multinational company. The prototype system allows capturing and reusing knowledge generated during the resolution of Overall Equipment Effectiveness (OEE) problems in multiple locations at shop floor level. The developed system was implemented in Exide Technologies. The system integrates the 8D method, Case-Based Reasoning (CBR) and Product Lifecycle Management (PLM). The PLM system is used as the source of extended problem context information (i.e. Products, Processes and Resources) that will enrich the similarity calculation of the CBR application. Process Failure Mode and Effect Analysis (PFMEA) is used as the source of the initial set of cases to populate the case-base. From the development perspective, the system comprises a multi-agent architecture based on SEASALT (Shared Experience using an Agent-based System Architecture LayouT) and programmed in Java. The development infrastructure comprises: Eclipse, JADE (Java Agent DEvelopment framework) and AML (Adaptive Mark-up Language) studio. The selected software applications are myCBR and Aras. The prototype system was tested and validated in three main steps with an increasing level of complexity. The results demonstrated the feasibility of the adopted approach. An overall description of the system, results, lessons learned, and recommendations are provided.

Keywords

Product lifecycle management (PLM) Manufacturing problem solving (MPS) Fault diagnosis Process failure mode and effect analysis (PFMEA) Case-based reasoning (CBR) 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alvaro Camarillo
    • 1
    • 2
  • José Ríos
    • 2
    Email author
  • Klaus-Dieter Althoff
    • 3
    • 4
  1. 1.Exide Technologies SASGennevilliersFrance
  2. 2.Mechanical Engineering DepartmentUniversidad Politécnica de MadridMadridSpain
  3. 3.German Research Center for Artificial Intelligence (DFKI)KaiserslauternGermany
  4. 4.Institut für Informatik, University of HildesheimHildesheimGermany

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