Research Article
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A New Accident Analysis Model Proposal in Occupational Safety Risk Management: "Star Diagram"

Year 2023, Volume: 21 Issue: 48, 205 - 219, 28.03.2023
https://doi.org/10.35408/comuybd.1231675

Abstract

Occupational accidents are a global problem in terms of their effects. Different techniques for the analysis of accidents are available in the literature. Accident analyzes, which experts often conduct with linguistic expressions, cause some problems in expressing the sizes and distributions of root and supporting factors. Existing approaches do not clearly reflect the distribution of factors that may cause an accident. In this direction, a new model has been proposed to the literature for the analysis of occupational accidents within the scope of this study. The proposed model was developed based on accident theories and complies with the principles of root cause analysis. However, it has brought many innovations to existing applications. The proposed method, the factors affecting the accident; It divides it into 5 main groups as “Personal”, “Environment”, “Management”, “Machine and Equipment” and “Organization”. Each of these identified main factors is characterized by schematic distribution to the 5 arms of a star. For this reason, the method is called "Star Diagram". The proposed model is a first in the literature in this field. The main parameters in risk analysis are probability and severity. Before accidents occur, the magnitude of the risk is expressed in line with these parameters. Inspired by this, the proposed model determines to what extent the impact categories contribute to the probability of the event and the severity of the damage after the accident occurs. In this direction, relative data can be expressed as a percentage of which category affects the formation of the accident. The proposed model stands out with its categorized root cause analysis and quantitative magnitude expressions, which are not available in other techniques. In this respect, it fills an important gap in the literature.

References

  • Andrews, J. D. & Dunnett, S. J. (2000). Event-Tree Analysis Using Binary Decision Diagrams. IEEE Transactions on Reliability, 49(2), 230-238.
  • Aşkın, A., & Öztürk, Ö. F. (2022). Mobilya sektörü çalışanlarında iş kazası ve meslek hastalıklarının incelenmesi üzerine bir araştırma. Bartın Orman Fakültesi Dergisi, 24(2), 351-364.
  • Boyle, T. (2002). Health and Safety: Risk Management. Taylor and Francis Group. London.
  • Cinar, U. (2022). İş Sağlığı ve Güvenliğinde Skorlama Tabanlı Uygulamalı Risk Analizi Rehberi. İKSAD Publishing House. Ankara.
  • Cinar, U. & Cebi, S. (2020). A Hybrid Risk Assessment Method for Mining Sector Based on QFD, Fuzzy Inference System, and AHP. Journal of Intelligent & Fuzzy Systems. 39(5), 6047-6058.
  • Cinar, U. & Cebi, S. (2022). A Novel Approach to Assess Occupational Risks and Prevention of Hazards: The House of Safety & Prevention. Journal of Intelligent & Fuzzy Systems, 42(1), 517-528.
  • Güllüoğlu, E. N. & Taçgın, E. (2018). Türkiye Tekstil Sektöründe İstihdam ve İş Kazalarının Analizi. Tekstil ve Mühendis, 25(112), 344-354.
  • Gürcanlı, G. E. (2015). İşçi Sağlığı ve İş Güvenliği Mücadelesinde Kavramları Netleştirmek, Kavramlarda Ortaklaşmak. TTB Mesleki Sağlık ve Güvenlik Dergisi, 15(54), 77-87.
  • Harms-Ringdahl, L. (2004). Relationships between Accident Investigations, Risk Analysis, and Safety Management. Journal of Hazardous Materials, 111(1-3), 13-19.
  • Heinrich, H. W. (1931). Industrial Accident Prevention. McGrawHill. New York.
  • Hollnagel, E. & Goteman, Ö. (2004). The Functional Resonance Accident Model, Cognitive System Engineering in Process Control, 4-5 Nov 2004, CSEPC, 155-161.
  • Hollnagel, E. (2012). FRAM: The Functional Resonance Analysis Method. Ashgate. Farnham.
  • Hoyos, C. G. & Zimolong, B. M. (2014). Occupational Safety and Accident Prevention: Behavioral Strategies and Methods. Elsevier. Amsterdam.
  • Khakzad, N., Khan, F. & Paltrinieri, N. (2014). On the Application of Near Accident Data to Risk Analysis of Major Accidents. Reliability Engineering & System Safety, 126, 116-125.
  • Leveson, N. (2004). A new accident model for engineering safer systems. Safety Science, 42(4), 237-270.
  • McLeod, R. W. (2015). Designing for human reliability: human factors engineering in the oil, gas, and process industries. Gulf Professional Publishing.
  • Ohno, T. (1978). Toyota production system: Beyond large-scale production. Productivity Press. New York.
  • Qureshi, Z. H. (2008). A Review of Accident Modelling Approaches for Complex Critical Sociotechnical Systems. Defence Science and Technology Organisation. Eddingburg, Australia.
  • Reason, J. (1990). Human Error. Cambridge University Press. Cambridge.
  • Underwood, P. & Waterson, P. (2013). Accident Analysis Models and Methods: Guidance for Safety Professionals. Loughborough University Press. Leicestershire.
  • Watson, H. A. (1961). Launch control safety study. Bell Laboratories.
  • Murray Hill. Williams, P. M. (2001). Techniques for Root Cause Analysis. Baylor University Medical Center Proceedings, 14(2), 154-157.
  • Xing, L. & Amari, S. V. (2008). Handbook of Performability Engineering: Fault Tree Analysis. Springer. London.

A New Accident Analysis Model Proposal in Occupational Safety Risk Management: "Star Diagram"

Year 2023, Volume: 21 Issue: 48, 205 - 219, 28.03.2023
https://doi.org/10.35408/comuybd.1231675

Abstract

Occupational accidents are a global problem in terms of their effects. Different techniques for the analysis of accidents are available in the literature. Accident analyzes, which experts often conduct with linguistic expressions, cause some problems in expressing the sizes and distributions of root and supporting factors. Existing approaches do not clearly reflect the distribution of factors that may cause an accident. In this direction, a new model has been proposed to the literature for the analysis of occupational accidents within the scope of this study. The proposed model was developed based on accident theories and complies with the principles of root cause analysis. However, it has brought many innovations to existing applications. The proposed method, the factors affecting the accident; It divides it into 5 main groups as “Personal”, “Environment”, “Management”, “Machine and Equipment” and “Organization”. Each of these identified main factors is characterized by schematic distribution to the 5 arms of a star. For this reason, the method is called "Star Diagram". The proposed model is a first in the literature in this field. The main parameters in risk analysis are probability and severity. Before accidents occur, the magnitude of the risk is expressed in line with these parameters. Inspired by this, the proposed model determines to what extent the impact categories contribute to the probability of the event and the severity of the damage after the accident occurs. In this direction, relative data can be expressed as a percentage of which category affects the formation of the accident. The proposed model stands out with its categorized root cause analysis and quantitative magnitude expressions, which are not available in other techniques. In this respect, it fills an important gap in the literature.

References

  • Andrews, J. D. & Dunnett, S. J. (2000). Event-Tree Analysis Using Binary Decision Diagrams. IEEE Transactions on Reliability, 49(2), 230-238.
  • Aşkın, A., & Öztürk, Ö. F. (2022). Mobilya sektörü çalışanlarında iş kazası ve meslek hastalıklarının incelenmesi üzerine bir araştırma. Bartın Orman Fakültesi Dergisi, 24(2), 351-364.
  • Boyle, T. (2002). Health and Safety: Risk Management. Taylor and Francis Group. London.
  • Cinar, U. (2022). İş Sağlığı ve Güvenliğinde Skorlama Tabanlı Uygulamalı Risk Analizi Rehberi. İKSAD Publishing House. Ankara.
  • Cinar, U. & Cebi, S. (2020). A Hybrid Risk Assessment Method for Mining Sector Based on QFD, Fuzzy Inference System, and AHP. Journal of Intelligent & Fuzzy Systems. 39(5), 6047-6058.
  • Cinar, U. & Cebi, S. (2022). A Novel Approach to Assess Occupational Risks and Prevention of Hazards: The House of Safety & Prevention. Journal of Intelligent & Fuzzy Systems, 42(1), 517-528.
  • Güllüoğlu, E. N. & Taçgın, E. (2018). Türkiye Tekstil Sektöründe İstihdam ve İş Kazalarının Analizi. Tekstil ve Mühendis, 25(112), 344-354.
  • Gürcanlı, G. E. (2015). İşçi Sağlığı ve İş Güvenliği Mücadelesinde Kavramları Netleştirmek, Kavramlarda Ortaklaşmak. TTB Mesleki Sağlık ve Güvenlik Dergisi, 15(54), 77-87.
  • Harms-Ringdahl, L. (2004). Relationships between Accident Investigations, Risk Analysis, and Safety Management. Journal of Hazardous Materials, 111(1-3), 13-19.
  • Heinrich, H. W. (1931). Industrial Accident Prevention. McGrawHill. New York.
  • Hollnagel, E. & Goteman, Ö. (2004). The Functional Resonance Accident Model, Cognitive System Engineering in Process Control, 4-5 Nov 2004, CSEPC, 155-161.
  • Hollnagel, E. (2012). FRAM: The Functional Resonance Analysis Method. Ashgate. Farnham.
  • Hoyos, C. G. & Zimolong, B. M. (2014). Occupational Safety and Accident Prevention: Behavioral Strategies and Methods. Elsevier. Amsterdam.
  • Khakzad, N., Khan, F. & Paltrinieri, N. (2014). On the Application of Near Accident Data to Risk Analysis of Major Accidents. Reliability Engineering & System Safety, 126, 116-125.
  • Leveson, N. (2004). A new accident model for engineering safer systems. Safety Science, 42(4), 237-270.
  • McLeod, R. W. (2015). Designing for human reliability: human factors engineering in the oil, gas, and process industries. Gulf Professional Publishing.
  • Ohno, T. (1978). Toyota production system: Beyond large-scale production. Productivity Press. New York.
  • Qureshi, Z. H. (2008). A Review of Accident Modelling Approaches for Complex Critical Sociotechnical Systems. Defence Science and Technology Organisation. Eddingburg, Australia.
  • Reason, J. (1990). Human Error. Cambridge University Press. Cambridge.
  • Underwood, P. & Waterson, P. (2013). Accident Analysis Models and Methods: Guidance for Safety Professionals. Loughborough University Press. Leicestershire.
  • Watson, H. A. (1961). Launch control safety study. Bell Laboratories.
  • Murray Hill. Williams, P. M. (2001). Techniques for Root Cause Analysis. Baylor University Medical Center Proceedings, 14(2), 154-157.
  • Xing, L. & Amari, S. V. (2008). Handbook of Performability Engineering: Fault Tree Analysis. Springer. London.
There are 23 citations in total.

Details

Primary Language English
Journal Section Research Article
Authors

Ulas Cınar 0000-0003-3924-0768

Publication Date March 28, 2023
Submission Date January 9, 2023
Published in Issue Year 2023 Volume: 21 Issue: 48

Cite

APA Cınar, U. (2023). A New Accident Analysis Model Proposal in Occupational Safety Risk Management: "Star Diagram". Yönetim Bilimleri Dergisi, 21(48), 205-219. https://doi.org/10.35408/comuybd.1231675

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