Mining safety rules for derailments in a steel plant using correspondence analysis

被引:16
|
作者
Maiti, J. [1 ]
Singh, Abhijit K. [1 ]
Mandal, Saptarshi [1 ]
Verma, Abhishek [1 ]
机构
[1] Indian Inst Technol, Dept Ind & Syst Engn, Kharagpur 721302, W Bengal, India
关键词
Derailments; Steel plant; Correspondence analysis; Safety management; Risk based maintenance; ACCIDENTS;
D O I
10.1016/j.ssci.2014.02.011
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this study, we have analyzed a steel plant's derailment data using correspondence analysis. The primary purpose of this analysis is to find out associations of categories of factors contributing to the derailments which ultimately lead to the development of meaningful rules for preventing derailments. 348 derailment incidents collected over a period of 42 months were analyzed considering 4 factors namely, shift of working, location, cause of derailment and department responsible. Descriptive statistics show that by shift of working there is not much difference in the occurrence of derailments. But from location, cause of derailment and responsibility (departments) points of view, 'raw material line', 'manual operations' and 'production (raw material)' accounted for 50%, 60% and 48.28% of derailments, respectively. From correspondence analysis, it is found that 'level of movements', 'level of human involvement', 'management of wagons', and 'criticality of movements' are the hidden root causes of derailments in the plant studied. In order to improve the safety of in-plant rail transport of the plant studied, the plant management should (i) collect and analyze derailment data related to 'level of movements' and 'human involvement', (ii) adopt collaborative maintenance of wagons as external agencies are also involved in rail transport, and (iii) practice risk based maintenance of the in-plant rail transportation systems. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:24 / 33
页数:10
相关论文
共 50 条
  • [1] USING STAINLESS-STEEL PLANT WITH SAFETY
    不详
    [J]. PROCESSING, 1978, 24 (05): : 67 - 68
  • [2] OVERHAULING PLANT SAFETY RULES
    Hess, Glenn
    [J]. CHEMICAL & ENGINEERING NEWS, 2014, 92 (38) : 20 - 23
  • [3] Identifying patterns of safety related incidents in a steel plant using association rule mining of incident investigation reports
    Verma, Abhishek
    Das Khan, Sudha
    Maiti, J.
    Krishna, O. B.
    [J]. SAFETY SCIENCE, 2014, 70 : 89 - 98
  • [4] NEW RULES FOR PLATING PLANT SAFETY
    不详
    [J]. ENVIRONMENTAL CONTROL AND SAFETY MANAGEMENT, 1970, 140 (01): : 56 - &
  • [5] Text Mining based Safety Risk Assessment and Prediction of Occupational Accidents in a Steel Plant
    Sarkar, Sobhan
    Vinay, Sammangi
    Maiti, Jhareswar
    [J]. 2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL TECHNIQUES IN INFORMATION AND COMMUNICATION TECHNOLOGIES (ICCTICT), 2016,
  • [6] Hit and run crash analysis using association rules mining
    Das, Subasish
    Kong, Xiaoqiang
    Tsapakis, Ioannis
    [J]. JOURNAL OF TRANSPORTATION SAFETY & SECURITY, 2021, 13 (02) : 123 - 142
  • [7] Analysis of Firewall Policy Rules Using Data Mining Techniques
    Golnabi, Korosh
    Min, Richard K.
    Khan, Latifur
    Al-Shaer, Ehab
    [J]. 2006 IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM, VOLS 1 AND 2, 2006, : 305 - +
  • [8] Analysis of firewall policy rules using traffic mining techniques
    Abedin, Muhammad
    Nessa, Syeda
    Khan, Latifur
    Al-Shaer, Ehab
    Awad, Mamoun
    [J]. INTERNATIONAL JOURNAL OF INTERNET PROTOCOL TECHNOLOGY, 2010, 5 (1-2) : 3 - 22
  • [9] Data mining of tuberculosis patient data using multiple correspondence analysis
    Rennie, T. W.
    Roberts, W.
    [J]. EPIDEMIOLOGY AND INFECTION, 2009, 137 (12): : 1699 - 1704
  • [10] Plant-wide detection and diagnosis using correspondence analysis
    Detroja, K. P.
    Gudi, R. D.
    Patwardhan, S. C.
    [J]. CONTROL ENGINEERING PRACTICE, 2007, 15 (12) : 1468 - 1483