Human Injuries Risk Assessment of Medium Voltage Electrocution using Bow Tie Model in Fuzzy Environment (Case Study: Golestan Province Electricity Distribution Company)

Mohammad Mehdi Babaei, Mousa Jabbari, Ahmad Ali Babaei


Individuals involved in development, repair and maintenance activities of power transmission and distribution are at high risk of electrocution. The purpose of this research is to calculate the human injuries risk of medium voltage electrocution accidents using Bow Tie model in fuzzy environment. Therefore, existing evidences and documents was investigated, and accident causes was determined using the FTA technique. Then, their outcomes were identified by using ETA and William Fine method, and Bow Tie diagrams were drawn based on the results. After that, because of inadequate data, the fuzzy logic was used to calculate the probability of the root causes and outcomes of the accident. The probability of the middle causes and top event was also calculated by probabilistic equations. The results showed that in terms of frequency, medium voltage electrocution accident with probability of 2.2E-4 is one of the significant accidents in the electricity distribution activities, as well as the outcome of "permanent total disability or death of one person" and "with no injury", are the maximum and minimum outcome of the mentioned accident with the probability of 2.1E-6 and 1.29E-10, respectively. These outcomes with the risk of 1.05E-8 and 1.29E-10 are also considered as highest and lowest risk, respectively. "Permanent total disability or death of one person" is the most important outcome of medium voltage electrocution accident, in terms of both frequency and risk. "Lack of installing earth system" and "absence of double insulation" are the most important root causes of accidents. Finally, the results of this research can facilitate financial and human resources planning, and also, the use of Bow Tie in the fuzzy environment can resolve risk assessment problem greatly in the uncertainty and lack of inadequate data.


Power Distribution, Medium Voltage Electrocution, Risk, Fuzzy Bow Tie, Human Injuries

Full Text:



Alex AL, Matthew R. Safety risk management for electrical transmission and distribution line construction, SAFETY SCI. 2013 Jan;51(1):118–26

Cawley J, Homce G. Trends in Electrical Injury in the U.S., 1992–2002. IEEE Trans Ind Appl. 25 July 2008; 44(4):962-78.

Lee R.C, Zhang D, Hannig J. Biophysical injury mechanisms in electrical shock trauma. ANNU REV BIOMED ENG. 2000 Aug; 2: 477–509. Available from: (2017)

Thepaksorn p, Pongpanich S. Occupational Injuries and Illnesses and Associated Costs in Thailand. Saf Health Work, June 2014; 5(2): 66-72.

Leigh JP, Cone JE, Harrison R. Costs of occupational injuriesand illnesses in California, Prev Med.2001; 32(5): 393-06.

Oxenburgh M, Marlow P. The productivity assessment tool: computer based cost benefit analysis model for the economic assessment of occupational health and safety interventions in the workplace. J Safety Res. 2005; 36(3):209-14.

Miller TR, Galbraith M. Estimating the costs of occupational injury in the United States. Accident Analysis and Prevention. Dec 1995; 27(6): 741-47.

Guidelines on risk assessments and safety statements: the Health and Safety Authority. HAS website 2006 Jan [cited 2006 Nov 15]; Available from: (2016)

Cardick J, Capelli-Schellpfeffer M, Neitzel D. Electrical Safety Handbook. 3th Ed. New York: McGraw-Hill; 2005. Available from: (2017)

Construction Focus Four: Electrocution Hazards. OSHA Directorate of Training and Education. OSHA website 2006 jan [cited 2011 Apr]; Available from: (2016)

Gordon LB, Cartelli L. Complete Hazard Classification system and its Application. IEEE ISA Electrical Safety Workshop. 2009; 1-12 Available from: (2017)

Lee CR, Dougherty W. Electrical injury: mechanisms, manifestations and therapy. IEEE Trans Dielectr Electr Insul. 2003; 10(5): 810–819.

Soelen WV. The Field Guide for Powerline Workers, 1th ed. USA New York: Thomson Delmar Learning; 2006. Available from: (2017)

Clifton AE. Hazard analysis techniques for system safety. 2th Ed. New jersey, USA. John Wiley & Sons, Inc; 2005. Available from: (2017)

Head L, Harcourt M. The Direct and Indirect Costs of Workplace Accidents in New Zealand. 1997 AIRAANZ Conference, Retrieved 29 NOV 2016 avilible from:

Sing Sii H, Ruxton T, Wang J. A fuzzy-logic-based approach to qualitative safety modelling for marine systems. Reliability Engineering & System Safety. July 2001; 73(1):19-34.

Sun YU, Fang DE, Wang S, Dai M, Lv X. Safety Risk Identification and Assessment for Beijing Olympic Venues Construction. J Manage Eng. Jun 2008; 24(1): 40-47.

Atrkar Roshan S, Daneshvar S. Fire risk assessment and its economic loss estimation in tehran subway. Iranian Journal of Health, Safety & Environment, 10 Dec 2014; 2(1):229-34.

Kangavari M, Salimi S, Nourian R, Omidi L, Askarian A. An application of failure mode and effect analysis (FMEA) to assess risks in petrochemical industry in Iran. Iranian Journal of Health, Safety & Environment, 20 May 2015; 2(2):257-63.

Wilson J, Koehn E. Safety management: problems encountered and recommended solutions. J Constr Eng Manage. Jan 2000; 126 (1):77–79.

MacCollum DV. Construction Safety Engineering Principles: Designing and Managing Safer Job Sites. New York: McGraw-Hill Professional. Available from: (2017)

USA Department of Labor. Occupational Safety and Health Administration (OSHA). Controlling electrical hazards. OSHA 3075. Safety and Health Admin (OSHA). OSHA Web Sit 2002 [cited 2002] Available from: (2016)

Soyka PA, Feldman SJ. Capturing the business value of EH&S excellence. Corporate Environmental Strategy. Jun 1998; 5(2): 61–68.

Arewa AO, Farrell P. A review of compliance with health and safety regulations and economic performance in small and medium construction enterprises. In:Smith, S.D (Ed) Procs 28th Annual ARCOM Conference,3-5 September 2012, Edinburgh UK. Association of Researchers in Construction Management, 423-432. Available from: 0432_Arewa_Farrell.pdf (2017)

BERR (2011) Improving outcomes from health and safety. A report to Government by the Better Regulation Executive. Department for Business Enterprises and Regulatory Reform, London, August, pp. 6±29. Available from: (2017)

Lancaster R, Ward R, Talbot P, Brazier A. Costs of compliance with health and safety regulations in SME’s. Health and Safety Executive: Research, Report 147. 1th ed. England Norwich: UK Entec Limited; 2003. Available from: (2017)

Zadeh LA. Fuzzy sets. INFORM CONTROL. Jun 1965; 8(3):338-353.

Sivanandam SN, Sumathi S, Deepa SN. Introduction to Fuzzy Logic using MATLAB.1th ed. Berlin Heidelberg: Springer; 2007, P95-101. Available from: (2017)

Tadic D, Djapan M, Misita M, Stefanovic M, Milanovic D. A Fuzzy Model for Assessing Risk of Occupational Safety. Int J Occup Saf Ergon. 2012; 18(2): 115-26.

Miller GA, The magical number seven plus or minus two: some limit on our capacity for processing information. The PSYCHOL REV. Apr 1994; 101(2):343-52.

Zimmerman HJ. Fuzzy set teory and its Applications.4th ed. Norwell, Massachusetts: Kluwer Academic Publishers; 2001. Available from: (2017)

Mahmood YA, Srividya A, Ahmadi A, Kumar U, Verma AK. Fuzzy fault tree analysis: a reviw of concept and application. Int J Syst Assur Eng Manag. (Jan-Mar 2013) 4(1):19–32.

Cockshott JE. Probability Bow-Ties: a transparent risk management tool. Process Saf Environ Prot. July 2005; 83(4): 307-16.

Jacinto C, Silva C. A semi-quantitative assessment of occupational risks using bow-tie representation. SAFETY SCI. October 2010; 48(8): 973–79.

Vijayaraghavan G, Jayalakshmi M. Fuzzy logic in process safety modeling of chemical process. Int J Adv Engg Res Studies. Sept 2013; 2(4):118-21.

Daneshvar S. Comparative assessment of fire risk in the subway in Tehran by ETA, FTA and Bow Tie and provide control methods to reduce risk [dissertation]. Tehran Iran: Medical Sciences Faculty of Tarbiat Modares University; 2013.

Rahmani S, Omidvari M. Assessing safety risk in electricity distribution processes using ET & BA improved technique and its ranking by VIKOR and TOPSIS models in fuzzy environment. Health and Safety at Work (JHSW). April 2016; 6(1):1-12.

Safari M, Golmohamadi A, Amjadi A. Procedures to identify safety hazards, environmental aspects and risk assessment cod: PI3202. 4th ed. Tehran Iran, Electricity Distribution Company of West Tehran. 2009.

American National Standards Institute (ANSI). ANSI B11. TR3-2000, Risk assessment and risk reduction – a guide to estimate, evaluate risk associated with machine tools. 2000. Available from: (2017)

Renjith VR, Madhu G, Nayagam VL, Bhasi AB. Two-dimensional fuzzy fault tree analysis for chlorine release from a chlor-alkali industry using expert elicitation. J Hazard Mater. 15 Nov 2010; 183(1-3):103-110.

Chen SJ, Hwang CL. Fuzzy Multiple Attribute decision-making: Methods and Applications, Lecture Notes in Economics and Mathematical Systems. 1st Ed. Germany: Springer–Verlag Berlin Heidelberg; 1993. Available from: (2017)

Clemen RT, Winkler R L. Combining probability distribution from experts in risk analysis. RISK ANAL. April 1999; 19(2): 187–03.

Hauge S, Onshus T. Reliability Data for Safety Instrumented Systems: PDS Data Handbook. 1st Ed. New York: SINTEF Technology and Society; 2009. Available from: (2017)

Onisawa T. An approach to human reliability in man-machine systems using error possibility. Fuzzy Sets and Systems. Aug 1988; 27(2): 87-103.

National Fire Protection Association (NRPA). Standard on Fire Department Occupational Safety and Health Program (NFPA 1500).ed 2013. Available from:: (2017)

Hallowell MR. Safety risk perception in construction companies in the Pacific Northwest of the USA. Construction Management and Economics. 19 Apr 2010; 28(4):403–13.

Iranian Journal of Health, Safety and Environment e-ISSN: :2345-5535 Iran university of Medical sciences, Tehran, Iran