ABSTRACT
BACKGROUND: Apparel exports bring in sizeable foreign income to Sri Lanka. To protect and promote this industry is a paramount need. This can be carried out by applying Human Factors/Ergonomics (HFE) which has proved to control negative effects at work places. OBJECTIVES: This paper reports a case study which describes the demands and benefits of HFE in MAS Holdings which owns a large share of the apparel industry in Sri Lanka. METHODS: The study consisted of walk through observation survey, a questionnaire survey and ergonomic work place analysis followed by a training programme to selected employees in three companies. RESULTS: Positive responses to questionnaires revealed good ergonomic practices in the work places surveyed. Ergonomically unfit chairs and potential hazards e.g. exposure to noise and hot environment were detected. It is seen that MAS have introduced strategies originated by Toyota Production System viz. 5S, Kaizen, six sigma etc., which are in fact ergonomic methods. A progressive project MAS boast of viz. 'MAS Operating System' (MOS) empowers training and development to employees. CONCLUSIONS: MAS Holdings has adequately realized the benefits of applying HFE as evident by the number of awards received. Relevant companies were advised to take appropriate corrective measures to control the potential hazards.
Subject(s)
Clothing , Ergonomics , Occupational Health , Textile Industry , Female , Humans , Male , Needs Assessment , Noise, Occupational/prevention & control , Posture , Sri Lanka , Temperature , Textile Industry/organization & administration , WorkloadABSTRACT
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.
