首页> 外文会议>IEEE International Conference on Computational Intelligence and Computing Research >Analyzing the drivers for safety practices using interpretive structural modeling: A case of Indian manufacturing firms
【24h】

Analyzing the drivers for safety practices using interpretive structural modeling: A case of Indian manufacturing firms

机译:使用解释性结构模型分析安全实践的驱动因素:以印度制造公司为例

获取原文

摘要

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.
机译:安全措施是提高安全水平的措施,或更确切地说是控制措施,旨在通过制定的安全政策或视觉管理措施或通过物理标志减轻物理破坏。决定不存在任何安全实践对任何组织的影响的两个因素是经济影响和庞大的人道主义。这在制造公司中尤其普遍,该公司在过去几年中一直保持着最大疾病和伤害率的记录。在任何组织中,这都超过了安全性的重要性。制造企业的当代趋势是,组织或车间中存在的安全实践与企业的本质或运营方式保持一致。这使我们对这些公司的安全实施了解有限。本文主要侧重于确定对改善安全实践至关重要的最重要的驱动因素。本文利用解释性结构建模,其输出阐明了两个重要组成部分,即驱动力和依赖力。驱动力是每个驾驶员在安全实践改进中已变得越来越重要的突出水平。依赖性能力是它们之间相互依赖性的水平。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号