Knowledge-based multi-agent system for manufacturing problem solving process in production plants

Alvaro Camarillo; José Ríos; Klaus-Dieter Althoff

In: Journal of Manufacturing Systems, Vol. 47, Pages 115-127, Elsevier, 2018.


This paper proposes a novel approach to develop a production-oriented software system aimed to assist shop floor actors during a Manufacturing Problem Solving (MPS) process. The proposed system integrates the problem-solving method 8D, Process Failure Mode and Effect Analysis (PFMEA), Case-Based Reasoning (CBR), and Product Lifecycle Management (PLM). The system is based on an ontology that enhances and extends existing proposals to allow representing any type of manufacturing problem linked to production lines and reusing PFMEA analysis results. The architecture of the system is based on SEASALT (Shared Experience using an Agent-based System Architecture LayouT), which is a multi-case base domain-independent reasoning architecture for extracting, analyzing, sharing, and providing experiences. A proof of concept prototype was developed, implemented, and tested in a company. The results, which were collected in two different manufacturing plants of the company, show the feasibility of the proposed approach and validate the conceptual proposal presented in this paper.

Weitere Links

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence