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Publication Type : Conference Paper
Publisher : 2016 IEEE International Conference on Computational Intelligence and Computing Research,
Source : 2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016, Institute of Electrical and Electronics Engineers Inc. (2017)
ISBN : 9781509006113
Keywords : Artificial intelligence, Control measures, Interpretive structural modeling, Level of safeties, Manufacture, Manufacturing firms, Safety measures, Safety policies, Safety practices, Visual management
Campus : Coimbatore
School : School of Business
Department : Business
Year : 2017
Abstract : Safety measures are the ones to increase the level of safety or rather are control measures, to alleviate the physical destruction by the formulated safety policies or visual management practices or through physical signage. Two factors which determine the impact of non-existence of safety practices in any organization are economic repercussions and large humanitarian. This is particularly prevalent among the manufacturing firm which holds a track record of maximum illness and injury rate for the past couple of years. This outlays the importance of safety in any organization. The contemporary trend of manufacturing firms is that, the safety practices that exist in the organization or in the shop floor is aligned with the very nature of its business or the way its operations run. This gives us a limited understanding on safety implementation in those firms. This paper primarily focuses upon identifying the most important drivers that are rudimentary for improvement of safety practices. This paper makes use of interpretive structural modeling whose output elucidates two important components namely, driving power and dependence power. Driving power is the level of prominence that each driver has got in importance in the safety practice improvement. Dependence power is the level of interdependency between them. © 2016 IEEE.
Cite this Research Publication : K. Renganath and Dr. Suresh M., “Analyzing the drivers for safety practices using interpretive structural modeling: A case of Indian manufacturing firms”, in 2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016, 2017.