Assessment of safety performance in Indian industries using fuzzy approach

作者: G.S. Beriha , B. Patnaik , S.S. Mahapatra , S. Padhee

DOI: 10.1016/J.ESWA.2011.09.018

关键词: Fuzzy logicComputer scienceInjury preventionPoison controlFuzzy setComputer securityOccupational safety and healthExpert systemRisk analysis (engineering)Inference engineInvestment (macroeconomics)

摘要: This paper presents an artificial intelligence approach for prediction of different types accidents (fatal to minor) in uncertain environment. Likelihood occurrence the work place is a random phenomenon but judicious investment various attribute such as expenses health care, safety training, up-gradation tools and machinery, on equipment may lead reduction accident rate. The relationship between type difficult establish because they do not follow any predictable rule rather associate non-linear manner. In situation, fuzzy logic helps map inputs outputs efficient manner building inference engine so that can be predicted. Prediction managers formulate organizational policies improving performance.

参考文章(47)
Pamela R. McCauley-Bell, Lesia L. Crumpton-Young, Adedeji Bodunde Badiru, Techniques and Applications of Fuzzy Theory in Quantifying Risk Levels in Occupational Injuries and Illnesses Fuzzy Theory Systems#R##N#Techniques and Applications. pp. 223- 265 ,(1999) , 10.1016/B978-012443870-5.50012-5
Marzio Marseguerra, Enrico Zio, Mauro Bianchi, A fuzzy modeling approach to road transport with application to a case of spent nuclear fuel transport Nuclear Technology. ,vol. 146, pp. 290- 302 ,(2004) , 10.13182/NT04-A3507
Elke Hermans, Tom Brijs, Geert Wets, Koen Vanhoof, Benchmarking road safety: lessons to learn from a data envelopment analysis. Accident Analysis & Prevention. ,vol. 41, pp. 174- 182 ,(2009) , 10.1016/J.AAP.2008.10.010
Karen A Brown, P.Geoffrey Willis, Gregory E Prussia, Predicting safe employee behavior in the steel industry: Development and test of a sociotechnical model Journal of Operations Management. ,vol. 18, pp. 445- 465 ,(2000) , 10.1016/S0272-6963(00)00033-4