CBR and PLM applied to diagnosis and technical support during problem solving in the Continuous Improvement Process of manufacturing plants

被引:11
|
作者
Camarillo, A. [1 ,2 ]
Rios, J. [2 ]
Althoff, K. D. [3 ,4 ]
机构
[1] Exide Technol GmbH, Odertal 35, D-37431 Bad Lauterberg im Harz, Germany
[2] Univ Politecn Madrid, Mech Engn Dept, Jose Gutierrez Abascal 2, Madrid 2800, Spain
[3] German Res Ctr Artificial Intelligence DFKI, Trippstadter Str 122, D-67663 Kaiserslautern, Germany
[4] Univ Hildesheim, Univ Pl 1, D-31141 Hildesheim, Germany
来源
MANUFACTURING ENGINEERING SOCIETY INTERNATIONAL CONFERENCE 2017 (MESIC 2017) | 2017年 / 13卷
关键词
Case-Based Reasoning (CBR); Product Lifecycle Management (PLM); Continuous Improvement (CIP); Manufacturing Problem Solving; Process Failure Mode and Effect Analysis (PFMEA);
D O I
10.1016/j.promfg.2017.09.096
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Currently many multinational companies have manufacturing plants with similar processes, but they suffer from barriers to share knowledge. Knowledge Management (KM) techniques may help to capture and reuse knowledge generated during processes execution. Literature shows Case-Based Reasoning (CBR) as a technique for implementing KM, and Product Lifecycle Management Systems (PLM) as the main data repository of Product-Processes-Resources data. This paper proposes a Continuous Improvement Process (CIP) approach to facilitate the capture and reuse of knowledge, integrating CBR and PLM technologies. It aims supporting production technicians during the resolution of manufacturing daily problems directly at shop floor level. (C) 2017 The Authors. Published by Elsevier B.V. Peer -review under responsibility of the scientific committee of the Manufacturing Engineering Society International Conference 2017.
引用
收藏
页码:987 / 994
页数:8
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