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A fuzzy-based model for risk assessment of routes in oil transportation

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Abstract

The transportation of oil is the final step that the oil is taken before it is distributed to consumer. Road transport is a type of oil transportation methods, and transfers between facilities of primary and secondary bases are carried out by tanker trucks. A particular advantage of tanker trucks is that they provide direct travel from the source to the destination. However, road transport involves possible hazards for population and environment. At this point, this study presents a fuzzy-based risk assessment model for the routes in an oil transportation company. Fuzzy analytic hierarchy process, which is a commonly used multi-criteria decision-making method, is applied in weighting nine criteria related to the road characteristics. Then, risk scores for eleven different routes which the tanker trucks of the company followed are determined by using a basic multi-criteria scoring method. Results of the case study emerge that the most important criterion is narrow road. The riskiest route for the company has been determined. In order to reduce risks to an acceptable level, a number of control measures are suggested such as to assign experienced drivers for this route, provide regular training for drivers, make regular vehicle maintenance and transport large quantities at one time as possible. To demonstrate validity, a comparison is also provided between the proposed approach and Pythagorean fuzzy analytic hierarchy process-based risk scoring model. In conclusion, this study contributes to the applicability of fuzzy analytic hierarchy process to assess riskiness for routes in oil transportation.

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References

  • Ambituuni A, Amezaga JM, Werner D (2015) Risk assessment of petroleum product transportation by road: a framework for regulatory improvement. Saf Sci 79:324–335

    Article  Google Scholar 

  • Buckley JJ (1985) Fuzzy hierarchical analysis. Fuzzy Set Syst 17(3):233–247

    Article  Google Scholar 

  • Celik E, Erdogan M, Gumus AT (2016) An extended fuzzy TOPSIS–GRA method based on different separation measures for green logistics service provider selection. Int J Environ Sci Te 13(5):1377–1392

    Article  Google Scholar 

  • Fabiano B, Curro F, Palazzi E, Pastorino R (2002) A framework for risk assessment and decision-making strategies in dangerous good transportation. J Hazard Mater 93(1):1–15

    Article  CAS  Google Scholar 

  • Fabiano B, Curro F, Reverberi AP, Pastorino R (2005) Dangerous good transportation by road: from risk analysis to emergency planning. J Loss Prevent Proc 18(4):403–413

    Article  Google Scholar 

  • Grassi A, Gamberini R, Mora C, Rimini B (2009) A fuzzy multi-attribute model for risk evaluation in workplaces. Saf Sci 47(5):707–716

    Article  Google Scholar 

  • Gul M (2018a) A review of occupational health and safety risk assessment approaches based on multi-criteria decision-making methods and their fuzzy versions. Hum Ecol Risk Assess 24(7):1723–1760

    Article  CAS  Google Scholar 

  • Gul M (2018b) Application of Pythagorean fuzzy AHP and VIKOR methods in occupational health and safety risk assessment: the case of a gun and rifle barrel external surface oxidation and colouring unit. Int J Occup Saf Ergon. https://doi.org/10.1080/10803548.2018.1492251

  • Gul M, Ak MF (2018) A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. J Clean Prod 196:653–664

    Article  Google Scholar 

  • Gul M, Guneri AF (2016) A fuzzy multi criteria risk assessment based on decision matrix technique: a case study for aluminum industry. J Loss Prevent Proc 40:89–100

    Article  CAS  Google Scholar 

  • Gul M, Ak MF, Guneri AF (2017a) Occupational health and safety risk assessment in hospitals: a case study using two-stage fuzzy multi-criteria approach. Hum Ecol Risk Assess 23(2):187–202

    Article  CAS  Google Scholar 

  • Gul M, Ak MF, Guneri AF (2017b) A hybrid risk-based approach for maritime applications: the case of ballast tank maintenance. Hum Ecol Risk Assess 23(6):1389–1403

    Article  CAS  Google Scholar 

  • Gul M, Guneri AF, Baskan M (2018a) An occupational risk assessment approach for construction and operation period of wind turbines. Global J Environ Sci Manage 4(3):281–298

    Google Scholar 

  • Gul M, Guven B, Guneri AF (2018b) A new Fine-Kinney-based risk assessment framework using FAHP-FVIKOR incorporation. J Loss Prevent Proc 53:3–16

    Article  Google Scholar 

  • Hu AH, Hsu CW, Kuo TC, Wu WC (2009) Risk evaluation of green components to hazardous substance using FMEA and FAHP. Expert Syst Appl 36(3):7142–7147

    Article  Google Scholar 

  • Ilbahar E, Karaşan A, Cebi S, Kahraman C (2018) A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Saf Sci 103:124–136

    Article  Google Scholar 

  • Kahraman C, Cebeci U, Ruan D (2004) Multi-attribute comparison of catering service companies using fuzzy AHP: the case of Turkey. Int J Prod Econ 87(2):171–184

    Article  Google Scholar 

  • Karabulut S, Öcalır-Akünal EV (2015) Geographical information system based environmental risk analysis for road transportation of hazmats. J Fac Eng Archit Gaz 30(3):351–359

    Google Scholar 

  • Karasan A, Ilbahar E, Cebi S, Kahraman C (2018) A new risk assessment approach: safety and critical effect analysis (SCEA) and its extension with Pythagorean fuzzy sets. Saf Sci 108:173–187

    Article  Google Scholar 

  • Karimi AR, Mehrdadi N, Hashemian SJ, Bidhendi GN, Moghaddam RT (2011) Selection of wastewater treatment process based on the analytical hierarchy process and fuzzy analytical hierarchy process methods. Int J Environ Sci Te 8(2):267–280

    Article  CAS  Google Scholar 

  • Kheirkhah AS, Esmailzadeh A, Ghazinoory S (2009) Developing strategies to reduce the risk of hazardous materials transportation in Iran using the method of fuzzy SWOT analysis. Transport 24(4):325–332

    Article  Google Scholar 

  • Milovanović B, Jovanović VD, Živanović P, Žeželj S (2012) Methodology for establishing the routes for transportation of dangerous goods on the basis of the risk level-Case study: city of Belgrade. Sci Res Essays 7(1):38–50

    Google Scholar 

  • Oz NE, Mete S, Serin F, Gul M (2018) Risk assessment for clearing & grading process of a natural gas pipeline project: an extended TOPSIS model with Pythagorean fuzzy sets for prioritizing hazards. Hum Ecol Risk Assess. https://doi.org/10.1080/10807039.2018.1495057

  • Ozdemir Y, Gul M, Celik E (2017) Assessment of occupational hazards and associated risks in fuzzy environment: a case study of a university chemical laboratory. Hum Ecol Risk Assess 23(4):895–924

    Article  CAS  Google Scholar 

  • Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48(1):9–26

    Article  Google Scholar 

  • Soner O, Celik E, Akyuz E (2017) Application of AHP and VIKOR methods under interval type 2 fuzzy environment in maritime transportation. Ocean Eng 129:107e116

  • Tzeng GH, Huang JJ (2011) Multiple attribute decision making: methods and applications. CRC Press, New York

    Book  Google Scholar 

  • Vianello C, Maschio G (2014) Quantitative risk assessment of the Italian gas distribution network. J Loss Prevent Proc 32:5–17

    Article  Google Scholar 

  • Wang W, Liu X, Qin Y (2018) A fuzzy fine-kinney-based risk evaluation approach with extended MULTIMOORA method based on Choquet integral. Comput Ind Eng 125:111–123

    Article  CAS  Google Scholar 

  • Yazdi M (2018) Risk assessment based on novel intuitionistic fuzzy-hybrid-modified TOPSIS approach. Saf Sci. https://doi.org/10.1016/j.ssci.2018.03.005

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Acknowledgement

We owe the oil company and the decision makers a debt of gratitude for their valuable helps on getting access data.

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Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Munzur University, 62000, Tunceli, Turkey

    M. Gul

  2. Department of Industrial Engineering, Yildiz Technical University, 34349, Istanbul, Turkey

    A. F. Guneri & S. Miralp Nasirli

Authors
  1. M. Gul
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  2. A. F. Guneri
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  3. S. Miralp Nasirli
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Correspondence to M. Gul.

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Editorial responsibility: Zhenyao Shen.

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Gul, M., Guneri, A.F. & Nasirli, S.M. A fuzzy-based model for risk assessment of routes in oil transportation. Int. J. Environ. Sci. Technol. 16, 4671–4686 (2019). https://doi.org/10.1007/s13762-018-2078-z

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  • DOI: https://doi.org/10.1007/s13762-018-2078-z

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