Verma A, Maiti J, Gaikwad V N
a Department of Industrial and Systems Engineering , Indian Institute of Technology, Kharagpur , India.
b Chief Safety (India and SEA), Tata Steel Limited , Jamshedpur , India.
Int J Inj Contr Saf Promot. 2018 Jun;25(2):180-194. doi: 10.1080/17457300.2017.1416482. Epub 2017 Dec 27.
Large integrated steel plants employ an effective safety management system and gather a significant amount of safety-related data. This research intends to explore and visualize the rich database to find out the key factors responsible for the occurrences of incidents. The study was carried out on the data in the form of investigation reports collected from a steel plant in India. The data were processed and analysed using some of the quality management tools like Pareto chart, control chart, Ishikawa diagram, etc. Analyses showed that causes of incidents differ depending on the activities performed in a department. For example, fire/explosion and process-related incidents are more common in the departments associated with coke-making and blast furnace. Similar kind of factors were obtained, and recommendations were provided for their mitigation. Finally, the limitations of the study were discussed, and the scope of the research works was identified.
大型综合钢铁厂采用有效的安全管理系统,并收集大量与安全相关的数据。本研究旨在探索并可视化这个丰富的数据库,以找出导致事故发生的关键因素。该研究是基于从印度一家钢铁厂收集的调查报告形式的数据进行的。使用帕累托图、控制图、石川图等一些质量管理工具对数据进行了处理和分析。分析表明,事故原因因部门所开展的活动而异。例如,火灾/爆炸和与工艺相关的事故在与炼焦和高炉相关的部门更为常见。获得了类似的因素,并针对其缓解提出了建议。最后,讨论了该研究的局限性,并确定了研究工作的范围。