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Technical Design of Condition Based Maintenance Systems - A Case Study Using Sound Analysis and Case-Based Reasoning
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0002-0729-0122
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0002-5562-1424
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0003-4308-2678
2004 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Productivity is a key weapon for manufacturing companies to stay competitive in a continuous growing global market. Increased productivity can be achieved through increased availability. This has directed focus on different maintenance types and maintenance strategies. Increased availability through efficient maintenance can be achieved through less corrective maintenance actions and more accurate preventive maintenance intervals. Condition Based Maintenance (CBM) is a technology that strives to identify incipient faults before they become critical which enables more accurate planning of the preventive maintenance. CBM can be achieved by utilizing complex technical systems or by humans manually monitoring the condition by using their experience, normally a mixture of both is used. Although CBM holds a lot of benefits compared to other maintenance types it is not yet commonly utilized in industry. One reason for this might be that the maturity level in complex technical CBM system is too low. This paper will acknowledge this possible reason, although not trying to resolve it, but focusing on system technology with component strategy and an open approach to condition parameters as the objective is fulfilled. This paper will theoretically discuss the technical components of a complete CBM system approach and by a case study illustrate how a CBM system for industrial robot fault detection/diagnosis can be designed using the Artificial Intelligence method Case-Based Reasoning and sound analysis.

Place, publisher, year, edition, pages
Knoxville, USA, 2004.
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:mdh:diva-9000OAI: oai:DiVA.org:mdh-9000DiVA, id: diva2:301571
Conference
8th International Conference of Maintenance and Realiability
Available from: 2010-03-03 Created: 2010-03-03 Last updated: 2017-03-06Bibliographically approved

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Bengtsson, MarcusFunk, PeterJackson, Mats

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf