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Ergonomics for enhancing detection of machine abnormalities
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0001-8693-3431
Work Science Academy, Sweden.
Mechanical Engineering Department, Government College of Engineering & Technology, Jammu.
Number of Authors: 3
2016 (English)In: Work: A journal of Prevention, Assesment and rehabilitation, ISSN 1051-9815, E-ISSN 1875-9270, Vol. 55, no 2, 271-280 p.Article in journal (Refereed) Published
Abstract [en]

BACKGROUND:

Detecting abnormal machine conditions is of great importance in an autonomous maintenance environment. Ergonomic aspects can be invaluable when detection of machine abnormalities using human senses is examined.

OBJECTIVES:

This research outlines the ergonomic issues involved in detecting machine abnormalities and suggests how ergonomics would improve such detections.

METHODS:

Cognitive Task Analysis was performed in a plant in Sri Lanka where Total Productive Maintenance is being implemented to identify sensory types that would be used to detect machine abnormalities and relevant Ergonomic characteristics.

RESULTS AND CONCLUSIONS:

As the outcome of this research, a methodology comprising of an Ergonomic Gap Analysis Matrix for machine abnormality detection is presented.

Place, publisher, year, edition, pages
2016. Vol. 55, no 2, 271-280 p.
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-60020DOI: 10.3233/WOR-162416ISI: 000386411800005PubMedID: 27689599Scopus ID: 2-s2.0-84992027309OAI: oai:DiVA.org:ltu-60020DiVA: diva2:1040732
Note

Validerad; 2016; Nivå 2; 2016-10-28 (andbra)

Available from: 2016-10-28 Created: 2016-10-28 Last updated: 2017-03-31Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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