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Agent-Based Monitoring using Case-Based Reasoning for Experience Reuse and Improved Quality
Mälardalen University, School of Innovation, Design and Engineering. (ISS)
Mälardalen University, School of Innovation, Design and Engineering. (ISS)ORCID iD: 0000-0002-5562-1424
2009 (English)In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, Vol. 15, no 2, p. 179-192Article in journal (Refereed) Published
Abstract [en]

Purpose – The purpose with this paper is to propose an agent-based condition monitoringsystem for use in industrial applications. An intelligent maintenance agent is described that isable to autonomously perform necessary actions and/or aid a human in the decision makingprocess. An example is presented as a case-study from manufacturing of industrial robots.Design/methodology/approach – The paper is mainly based on a case-study performed at alarge multi-national company aiming to explore the usefulness of case-based experience reusein production.Findings – This paper presents a concept of case-based experience reuse in production. Amaintenance agent using a Case-Based Reasoning approach to collect, preserve and reuseavailable experience in the form of sound recordings exemplifies this concept. Sound fromnormal and faulty robot gearboxes are recorded during the production end test and stored in acase library together with their diagnosis results. Given an unclassified sound signal, relevantcases are retrieved to aid a human in the decision making process. The maintenance agentdemonstrated good performance by making right judgments in 91% of all the tests, which isbetter than an inexperienced technician.Originality/value – The main focus of this paper is to show how to perform efficientexperience reuse in modern production industry to improve quality of products. Twoapproaches are used: a case-study describing an example of experience reuse in productionusing a fault diagnosis system recognizing and diagnosing audible faults on industrial robotsand an efficient approach on how to package such a system using the agent paradigm and agent architecture.

Place, publisher, year, edition, pages
Emerald , 2009. Vol. 15, no 2, p. 179-192
Keywords [en]
Experience Reuse, Decision Support Systems, Condition Monitoring, Intelligent Agents, Case-Based Reasoning, Quality Improvement
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:mdh:diva-6534DOI: 10.1108/13552510910961129Scopus ID: 2-s2.0-67650668459OAI: oai:DiVA.org:mdh-6534DiVA, id: diva2:226829
Projects
IntMaintAvailable from: 2009-07-06 Created: 2009-07-06 Last updated: 2018-01-13Bibliographically approved
In thesis
1. Fault Diagnosis of Industrial Machines using Sensor Signals and Case-Based Reasoning
Open this publication in new window or tab >>Fault Diagnosis of Industrial Machines using Sensor Signals and Case-Based Reasoning
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Industrial machines sometimes fail to operate as intended. Such failures can be more or less severe depending on the kind of machine and the circumstances of the failure. E.g. the failure of an industrial robotcan cause a hold-up of an entire assembly line costing the affected company large amounts of money each minute on hold. Research is rapidly moving forward in the area of artificial intelligence providing methods for efficient fault diagnosis of industrial machines. The nature of fault diagnosis of industrial machines lends itself naturally to case-based reasoning. Case-based reasoning is a method in the discipline of artificial intelligence based on the idea of assembling experience from problems and their solutions as ”cases” for reuse in solving future problems. Cases are stored in a case library, available for retrieval and reuse at any time.By collecting sensor data such as acoustic emission and current measurements from a machine and representing this data as the problem part of a case and consequently representing the diagnosed fault as the solution to this problem, a complete series of the events of a machine failure and its diagnosed fault can be stored in a case for future use.

Place, publisher, year, edition, pages
Västerås: Mälardalens högskola, 2009. p. 186
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 76
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-6539 (URN)978-91-86135-32-4 (ISBN)
Public defence
2009-09-18, Pathos, Mälardalens högskola, R-2, Västerås, 13:00 (English)
Opponent
Supervisors
Available from: 2009-07-13 Created: 2009-07-06 Last updated: 2018-01-13Bibliographically approved

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Funk, Peter

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