Quantitative Analysis on Time Delay Factors Influencing Firefighters' Response Time in the Process Industries Using Fuzzy Sets Theory
Abstract
Response time management is one of the most critical issues for firefighting organizations in the process industries. Thus, in emergency response success, it is of particular importance to apply an appropriate method to identify, prioritize, and manage factors influencing response time. The current study aimed to determine factors affecting firefighters' response time in Iranian process industries. Therefore, firstly a Hierarchical Task Analysis (HTA) was performed for firefighting emergency response-related activities. Then, time influencing factors for each task were determined. Finally, we chose the importance of each influencing factor and its priority based on the Fuzzy Chang approach. The results showed that factors, including the proper location of the firefighting truck, wearing and adjusting the breathing apparatus (BA) strap, and crowded at the scene had a significant impact on the response time to fire alarms. The related weights were equal to 0.049, 0.0485, and 0.0481, respectively. On the contrary, the wrong size of protective ensembles, BA weight, and height of car chassis factors were not significant in the response time. Their weight was equal to 0.0003, 0.002, and 0.0073, respectively. The results showed that the Fuzzy Hierarchical Task Analysis Approach (FHTA) could be used to identify and prioritize the factors influencing firefighting response time.
1. Aliabadi MM, Gholamizadeh K. Locating urban CNG stations using quantitative risk assessment: using the Bayesian network. Safety and Reliability. 2021;40(1):48-64.
2. Industrial and Manufacturing Property Fires. Fact Sheet. Massachusetts.USA: National Fire Protection Association(NFPA); 2016.
3. Paulin Jr AW, Woods GE, editors. Economic Impact of Current SIF, Flexibility, Inspection and Manufacturing Changes As They Relate to the B31 Piping Codes. Pressure Vessels and Piping Conference; 2019: American Society of Mechanical Engineers.
4. Bansal A. Industrial Accidents and their Prevention: A Case of Satluj Jal Viduat Nigam Limited, Shimla, Himachal Pradesh. Intel Prop Intel Prop Rights. 2016;4:171.
5. Accident Statistics in Iranian Industries. Iran: Organization of Statistics and Informations; 2017.
6. Oil and Gas Industry Fatal and Nonfatal Occupational Injuries. Fact Sheet. Washington, DC_USA: Bureau of Labor Statistics (BLS); April 20, 2010.
7. Subramaniam C, Ali H, Shamsudin FM. Initial emergency response performance of fire fighters in Malaysia. International Journal of Public Sector Management. 2012.
8. Feng Y, Cui S. A review of emergency response in disasters: Present and future perspectives. Natural Hazards. 2021;105(1):1109-38.
9. Wu B, Zhang J, Yip TL, Guedes Soares C. A quantitative decision-making model for emergency response to oil spill from ships. Maritime Policy & Management. 2021;48(3):299-315.
10. Nosov P, Cherniavskyi V, Zinchenko S, Popovych I, Nahrybelnyi YА, Nosova H. Identification of marine emergency response of electronic navigation operator. 2021.
11. Aleisa E, Savsar M, editors. Response Time Analysis of Firefighting Operations Using Discrete Event Simulation. 2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation; 2014: IEEE.
12. Snyder NA, Cinelli ME. Aperture Crossing in Virtual Reality: Physical Fatigue Delays Response Time. Journal of Motor Behavior. 2021:1-9.
13. Zarei E, Gholamizadeh K, Khan F, Khakzad N. A dynamic domino effect risk analysis model for rail transport of hazardous material. Journal of Loss Prevention in the Process Industries. 2022;74:104666.
14. Lee S, Jang JW, Kim D-Y. Emergency vehicle priority signal system based on deep learning using acoustic data. Journal of Platform Technology. 2021;9(3):44-51.
15. Mahmoudi H, Pishvaei MS, Saberian P, Slogan M. Presenting A Multi-objective Location Model in GIS Environment: A Case Study in East Tehran Emergency Stations. Health in Emergencies and Disasters. 2021;6(4):235-44.
16. Jaldell H. How important is the time factor? Saving lives using fire and rescue services. Fire technology. 2017;53(2):695-708.
17. Lu L, Peng C, Zhu J, Satoh K, Wang D, Wang Y. Correlation between fire attendance time and burned area based on fire statistical data of Japan and China. Fire Technology. 2014;50(4):851-72.
18. Buffington T, Ezekoye OA. Statistical Analysis of Fire Department Response Times and Effects on Fire Outcomes in the United States. Fire Technology. 2019;55(6):2369-93.
19. Zarei E, Khan F, Abbassi R. Importance of human reliability in process operation: a critical analysis. Reliability Engineering & System Safety. 2021;211:107607.
20. Zarei E, Ramavandi B, Darabi AH, Omidvar M. A framework for resilience assessment in process systems using a fuzzy hybrid MCDM model. Journal of Loss Prevention in the Process Industries. 2021;69:104375.
21. Wang D, Lu L, Zhu J, Yao J, Wang Y, Liao G. Study on correlation between fire fighting time and fire loss in urban building based on statistical data. Journal of Civil Engineering and Management. 2016;22(7):874-81.
22. Association NFP. NFPA 1710, standard for the organization and deployment of fire suppression operations, emergency medical operations, and special operations to the public by career fire departments: National Fire Protection Association; 2010.
23. Hansen R. Pre-incident planning of fires in underground hard rock mines: Old and new risks. TheAustralian Journal of Emergency Management. 2021;36(4):68-74.
24. Wild J, Greenberg N, Moulds ML, Sharp M-L, Fear N, Harvey S, et al. Pre-incident training to build resilience in first responders: recommendations on what to and what not to do. Psychiatry. 2020;83(2):128-42.
25. Eskandari S, Chuvieco E. Fire danger assessment in Iran based on geospatial information. International Journal of Applied Earth Observation and Geoinformation. 2015;42:57-64.
26. Mohammadfam I, Gholamizadeh K. Investigation of causes of plasco building accident in Iran using timed MTO and ACCIMAP methods. Journal of Failure Analysis and Prevention. 2020;20(6):2087-96.
27. Williams-Bell FM, Boisseau G, McGill J, Kostiuk A, Hughson RL. Air management and physiological responses during simulated firefighting tasks in a high-rise structure. Applied ergonomics. 2010;41(2):251-9.
28. Wilde ET. Do emergency medical system response times matter for health outcomes? Health economics. 2013;22(7):790-806.
29. McCoy CE, Menchine M, Sampson S, Anderson C, Kahn C. Emergency medical services out-of-hospital scene and transport times and their association with mortality in trauma patients presenting to an urban Level I trauma center. Annals of emergency medicine. 2013;61(2):167-74.
30. Blanchard IE, Doig CJ, Hagel BE, Anton AR, Zygun DA, Kortbeek JB, et al. Emergency medical services response time and mortality in an urban setting. Prehospital Emergency Care. 2012;16(1):142-51.
31. Harmsen A, Giannakopoulos G, Moerbeek P, Jansma E, Bonjer H, Bloemers F. The influence of prehospital time on trauma patients outcome: a systematic review. Injury. 2015;46(4):602-9.
32. Picado-Aguilar G, Aguero-Valverde J. Emergency response times and crash risk: An analysis framework for Costa Rica. Journal of Transport & Health. 2020;16:100818.
33. Sund B, Svensson L, Rosenqvist M, Hollenberg J. Favourable cost-benefit in an early defibrillation programme using dual dispatch of ambulance and fire services in out-of-hospital cardiac arrest. The European Journal of Health Economics. 2012;13(6):811-8.
34. Jaldell H, Lebnak P, Amornpetchsathaporn A. Time is money, but how much? The monetary value of response time for Thai ambulance emergency services. Value in health. 2014;17(5):555-60.
35. Zhao M, Liu Z, Wang S, editors. Research on Simulation and Analysis of Fire Emergency Decision. 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017); 2017: Atlantis Press.
36. Cabral ELdS, Castro WRS, Florentino DRdM, Viana DdA, Costa JFd, Souza RPd, et al. Response time in the emergency services. Systematic review1. Acta cirurgica brasileira. 2018;33:1110-21.
37. Yeboah G. FIRST RESPONDERS’EMERGENCY RESPONSE TIME ANALYSIS: CITY OF SASKATOON CASE STUDY: University of Saskatchewan Saskatoon; 2017.
38. Challands N. The relationships between fire service response time and fire outcomes. Fire technology. 2010;46(3):665-76.
39. Tzavella K, Fekete A, Fiedrich F. Opportunities provided by geographic information systems and volunteered geographic information for a timely emergency response during flood events in Cologne, Germany. Natural Hazards. 2018;91(1):29-57.
40. Gholamizadeh K, Kalatpour O, Mohammadfam I. Evaluation of health consequences in chemicals road transport accidents using a fuzzy approach. Journal of Occupational Hygiene Engineering. 2019;6(3):1-8.
41. Gholamizadeh K, Zarei E, Omidvar M, Yazdi M. Fuzzy Sets Theory and Human Reliability: Review, Applications, and Contributions. Linguistic Methods Under Fuzzy Information in System Safety and Reliability Analysis. 2022:91-137.
42. Mohammadfam I, Gholamizadeh K. Developing a Comprehensive Technique for Investigating Hazmat Transport Accidents. Journal of Failure Analysis and Prevention. 2021;21(4):1362-73.
43. Mohammadfam I, Gholamizadeh K. Assessment of Security Risks by FEMA and Fuzzy FEMA Methods, A Case Study: Combined Cycle Power Plant. Journal of Occupational Hygiene Engineering Volume. 2021;8(2):15-23.
44. Mohammadfam I, Kalatpour O, Gholamizadeh K. Quantitative assessment of safety and health risks in HAZMAT road transport using a hybrid approach: a case study in Tehran. ACS Chemical Health & Safety. 2020;27(4):240-50.
45. Mohammadfam I, Zarei E, Yazdi M, Gholamizadeh K. Quantitative Risk Analysis on Rail Transportation of Hazardous Materials. Mathematical Problems in Engineering. 2022;2022:6162829.
46. Dancygier B. The Cambridge handbook of cognitive linguistics: Cambridge University Press; 2017.
47. Promann M, Zhang T. Applying hierarchical task analysis method to discovery layer evaluation. Information Technology and Libraries. 2015;34(1):77-105.
48. Tripathi B, Rajesh R, Maiti J. Ergonomic evaluation of billet mould maintenance using hierarchical task analysis, biomechanical modeling and digital human modeling. Computer-Aided Design and Applications. 2015;12(3):256-69.
49. Fargnoli M, Lombardi M, Puri D. Applying Hierarchical Task Analysis to Depict Human Safety Errors during Pesticide Use in Vineyard Cultivation. Agriculture. 2019;9(7):158.
50. Chang D-Y. Applications of the extent analysis method on fuzzy AHP. European journal of operational research. 1996;95(3):649-55.
51. Janka A, Adler C, Fischer L, Perakakis P, Guerra P, Duschek S. Stress in crisis managers: evidence from self-report and psychophysiological assessments. Journal of behavioral medicine. 2015;38(6):970-83.
52. Thompson DJ, Weissbecker I, Cash E, Simpson DM, Daup M, Sephton SE. Stress and cortisol in disaster evacuees: an exploratory study on associations with social protective factors. Applied psychophysiology and biofeedback. 2015;40(1):33-44.
53. Ye Z, Xu Y, Veneziano D, Shi X. Evaluation of winter maintenance chemicals and crashes with an artificial neural network. Transportation Research Record. 2014;2440(1):43-50.
54. Frangopol DM, Tsompanakis Y. Maintenance and safety of aging infrastructure: CRC press Boca Raton, FL; 2014.
55. Kim MY, Burton M, Prozzi JA, Murphy M. Maintenance and rehabilitation project selection using artificial neural networks. 2014.
56. Frangopol D. Maintenance and safety of aging infrastructure. Edited by Dan Frangopol and Yiannis Tsompanakis. CRC Press; 2014.
2. Industrial and Manufacturing Property Fires. Fact Sheet. Massachusetts.USA: National Fire Protection Association(NFPA); 2016.
3. Paulin Jr AW, Woods GE, editors. Economic Impact of Current SIF, Flexibility, Inspection and Manufacturing Changes As They Relate to the B31 Piping Codes. Pressure Vessels and Piping Conference; 2019: American Society of Mechanical Engineers.
4. Bansal A. Industrial Accidents and their Prevention: A Case of Satluj Jal Viduat Nigam Limited, Shimla, Himachal Pradesh. Intel Prop Intel Prop Rights. 2016;4:171.
5. Accident Statistics in Iranian Industries. Iran: Organization of Statistics and Informations; 2017.
6. Oil and Gas Industry Fatal and Nonfatal Occupational Injuries. Fact Sheet. Washington, DC_USA: Bureau of Labor Statistics (BLS); April 20, 2010.
7. Subramaniam C, Ali H, Shamsudin FM. Initial emergency response performance of fire fighters in Malaysia. International Journal of Public Sector Management. 2012.
8. Feng Y, Cui S. A review of emergency response in disasters: Present and future perspectives. Natural Hazards. 2021;105(1):1109-38.
9. Wu B, Zhang J, Yip TL, Guedes Soares C. A quantitative decision-making model for emergency response to oil spill from ships. Maritime Policy & Management. 2021;48(3):299-315.
10. Nosov P, Cherniavskyi V, Zinchenko S, Popovych I, Nahrybelnyi YА, Nosova H. Identification of marine emergency response of electronic navigation operator. 2021.
11. Aleisa E, Savsar M, editors. Response Time Analysis of Firefighting Operations Using Discrete Event Simulation. 2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation; 2014: IEEE.
12. Snyder NA, Cinelli ME. Aperture Crossing in Virtual Reality: Physical Fatigue Delays Response Time. Journal of Motor Behavior. 2021:1-9.
13. Zarei E, Gholamizadeh K, Khan F, Khakzad N. A dynamic domino effect risk analysis model for rail transport of hazardous material. Journal of Loss Prevention in the Process Industries. 2022;74:104666.
14. Lee S, Jang JW, Kim D-Y. Emergency vehicle priority signal system based on deep learning using acoustic data. Journal of Platform Technology. 2021;9(3):44-51.
15. Mahmoudi H, Pishvaei MS, Saberian P, Slogan M. Presenting A Multi-objective Location Model in GIS Environment: A Case Study in East Tehran Emergency Stations. Health in Emergencies and Disasters. 2021;6(4):235-44.
16. Jaldell H. How important is the time factor? Saving lives using fire and rescue services. Fire technology. 2017;53(2):695-708.
17. Lu L, Peng C, Zhu J, Satoh K, Wang D, Wang Y. Correlation between fire attendance time and burned area based on fire statistical data of Japan and China. Fire Technology. 2014;50(4):851-72.
18. Buffington T, Ezekoye OA. Statistical Analysis of Fire Department Response Times and Effects on Fire Outcomes in the United States. Fire Technology. 2019;55(6):2369-93.
19. Zarei E, Khan F, Abbassi R. Importance of human reliability in process operation: a critical analysis. Reliability Engineering & System Safety. 2021;211:107607.
20. Zarei E, Ramavandi B, Darabi AH, Omidvar M. A framework for resilience assessment in process systems using a fuzzy hybrid MCDM model. Journal of Loss Prevention in the Process Industries. 2021;69:104375.
21. Wang D, Lu L, Zhu J, Yao J, Wang Y, Liao G. Study on correlation between fire fighting time and fire loss in urban building based on statistical data. Journal of Civil Engineering and Management. 2016;22(7):874-81.
22. Association NFP. NFPA 1710, standard for the organization and deployment of fire suppression operations, emergency medical operations, and special operations to the public by career fire departments: National Fire Protection Association; 2010.
23. Hansen R. Pre-incident planning of fires in underground hard rock mines: Old and new risks. TheAustralian Journal of Emergency Management. 2021;36(4):68-74.
24. Wild J, Greenberg N, Moulds ML, Sharp M-L, Fear N, Harvey S, et al. Pre-incident training to build resilience in first responders: recommendations on what to and what not to do. Psychiatry. 2020;83(2):128-42.
25. Eskandari S, Chuvieco E. Fire danger assessment in Iran based on geospatial information. International Journal of Applied Earth Observation and Geoinformation. 2015;42:57-64.
26. Mohammadfam I, Gholamizadeh K. Investigation of causes of plasco building accident in Iran using timed MTO and ACCIMAP methods. Journal of Failure Analysis and Prevention. 2020;20(6):2087-96.
27. Williams-Bell FM, Boisseau G, McGill J, Kostiuk A, Hughson RL. Air management and physiological responses during simulated firefighting tasks in a high-rise structure. Applied ergonomics. 2010;41(2):251-9.
28. Wilde ET. Do emergency medical system response times matter for health outcomes? Health economics. 2013;22(7):790-806.
29. McCoy CE, Menchine M, Sampson S, Anderson C, Kahn C. Emergency medical services out-of-hospital scene and transport times and their association with mortality in trauma patients presenting to an urban Level I trauma center. Annals of emergency medicine. 2013;61(2):167-74.
30. Blanchard IE, Doig CJ, Hagel BE, Anton AR, Zygun DA, Kortbeek JB, et al. Emergency medical services response time and mortality in an urban setting. Prehospital Emergency Care. 2012;16(1):142-51.
31. Harmsen A, Giannakopoulos G, Moerbeek P, Jansma E, Bonjer H, Bloemers F. The influence of prehospital time on trauma patients outcome: a systematic review. Injury. 2015;46(4):602-9.
32. Picado-Aguilar G, Aguero-Valverde J. Emergency response times and crash risk: An analysis framework for Costa Rica. Journal of Transport & Health. 2020;16:100818.
33. Sund B, Svensson L, Rosenqvist M, Hollenberg J. Favourable cost-benefit in an early defibrillation programme using dual dispatch of ambulance and fire services in out-of-hospital cardiac arrest. The European Journal of Health Economics. 2012;13(6):811-8.
34. Jaldell H, Lebnak P, Amornpetchsathaporn A. Time is money, but how much? The monetary value of response time for Thai ambulance emergency services. Value in health. 2014;17(5):555-60.
35. Zhao M, Liu Z, Wang S, editors. Research on Simulation and Analysis of Fire Emergency Decision. 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017); 2017: Atlantis Press.
36. Cabral ELdS, Castro WRS, Florentino DRdM, Viana DdA, Costa JFd, Souza RPd, et al. Response time in the emergency services. Systematic review1. Acta cirurgica brasileira. 2018;33:1110-21.
37. Yeboah G. FIRST RESPONDERS’EMERGENCY RESPONSE TIME ANALYSIS: CITY OF SASKATOON CASE STUDY: University of Saskatchewan Saskatoon; 2017.
38. Challands N. The relationships between fire service response time and fire outcomes. Fire technology. 2010;46(3):665-76.
39. Tzavella K, Fekete A, Fiedrich F. Opportunities provided by geographic information systems and volunteered geographic information for a timely emergency response during flood events in Cologne, Germany. Natural Hazards. 2018;91(1):29-57.
40. Gholamizadeh K, Kalatpour O, Mohammadfam I. Evaluation of health consequences in chemicals road transport accidents using a fuzzy approach. Journal of Occupational Hygiene Engineering. 2019;6(3):1-8.
41. Gholamizadeh K, Zarei E, Omidvar M, Yazdi M. Fuzzy Sets Theory and Human Reliability: Review, Applications, and Contributions. Linguistic Methods Under Fuzzy Information in System Safety and Reliability Analysis. 2022:91-137.
42. Mohammadfam I, Gholamizadeh K. Developing a Comprehensive Technique for Investigating Hazmat Transport Accidents. Journal of Failure Analysis and Prevention. 2021;21(4):1362-73.
43. Mohammadfam I, Gholamizadeh K. Assessment of Security Risks by FEMA and Fuzzy FEMA Methods, A Case Study: Combined Cycle Power Plant. Journal of Occupational Hygiene Engineering Volume. 2021;8(2):15-23.
44. Mohammadfam I, Kalatpour O, Gholamizadeh K. Quantitative assessment of safety and health risks in HAZMAT road transport using a hybrid approach: a case study in Tehran. ACS Chemical Health & Safety. 2020;27(4):240-50.
45. Mohammadfam I, Zarei E, Yazdi M, Gholamizadeh K. Quantitative Risk Analysis on Rail Transportation of Hazardous Materials. Mathematical Problems in Engineering. 2022;2022:6162829.
46. Dancygier B. The Cambridge handbook of cognitive linguistics: Cambridge University Press; 2017.
47. Promann M, Zhang T. Applying hierarchical task analysis method to discovery layer evaluation. Information Technology and Libraries. 2015;34(1):77-105.
48. Tripathi B, Rajesh R, Maiti J. Ergonomic evaluation of billet mould maintenance using hierarchical task analysis, biomechanical modeling and digital human modeling. Computer-Aided Design and Applications. 2015;12(3):256-69.
49. Fargnoli M, Lombardi M, Puri D. Applying Hierarchical Task Analysis to Depict Human Safety Errors during Pesticide Use in Vineyard Cultivation. Agriculture. 2019;9(7):158.
50. Chang D-Y. Applications of the extent analysis method on fuzzy AHP. European journal of operational research. 1996;95(3):649-55.
51. Janka A, Adler C, Fischer L, Perakakis P, Guerra P, Duschek S. Stress in crisis managers: evidence from self-report and psychophysiological assessments. Journal of behavioral medicine. 2015;38(6):970-83.
52. Thompson DJ, Weissbecker I, Cash E, Simpson DM, Daup M, Sephton SE. Stress and cortisol in disaster evacuees: an exploratory study on associations with social protective factors. Applied psychophysiology and biofeedback. 2015;40(1):33-44.
53. Ye Z, Xu Y, Veneziano D, Shi X. Evaluation of winter maintenance chemicals and crashes with an artificial neural network. Transportation Research Record. 2014;2440(1):43-50.
54. Frangopol DM, Tsompanakis Y. Maintenance and safety of aging infrastructure: CRC press Boca Raton, FL; 2014.
55. Kim MY, Burton M, Prozzi JA, Murphy M. Maintenance and rehabilitation project selection using artificial neural networks. 2014.
56. Frangopol D. Maintenance and safety of aging infrastructure. Edited by Dan Frangopol and Yiannis Tsompanakis. CRC Press; 2014.
| Files | ||
| Issue | Vol 14 No 1 (2022) | |
| Section | Original Article(s) | |
| Published | 2022-03-30 | |
| Keywords | ||
| Emergency Response Time Process Industries Alarm Assignment FHTA Safety Management | ||
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Gholamizadeh K, Ghasemi F, Pashootan Z, Kalatpour O. Quantitative Analysis on Time Delay Factors Influencing Firefighters’ Response Time in the Process Industries Using Fuzzy Sets Theory. Int J Occup Hyg. 2022;14(1):1-17.
