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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.
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: 27689599ScopusID: 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: 2016-11-20Bibliographically approved

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Illankoon, Prasanna
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