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.
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