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بررسی مدیریت ریسک در مرحله احداث با روش مدل‌سازی ساختاری تفسیری (مطالعه موردی: پروژه احداث خط لوله نفت یزد- نائین) | ||
| نشریه مهندسی عمران امیرکبیر | ||
| دوره 55، شماره 4، تیر 1402، صفحه 833-848 اصل مقاله (1.75 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/ceej.2023.21184.7643 | ||
| نویسندگان | ||
| میثم سهرابی؛ هیرش سلطان پناه* ؛ امیراسعد نصری زر؛ محمدصدیق ثابتی | ||
| گروه مهندسی عمران، دانشکده فنی و مهندسی، واحد سنندج، دانشگاه آزاد اسلامی، سنندج، ایران. | ||
| چکیده | ||
| شناخت ماهیت ریسک‌های تأثیرگذار بر پروژههای نفتی یک موضوع مهم در مدیریت ریسک در شرکت‌هایی مانند شرکت خطوط لوله و مخابرات نفت ایران است. هدف این مقاله، شناسایی ریسک‌‌ها و استخراج ساختار روابط میان ریسک‌های بحرانی پروژه احداث خط لوله نفت یزد- نائین با بهکارگیری رویکرد مدل‌سازی ساختاری تفسیری جهت کمک به ارکان پروژه می‌‌باشد. برای این کار ابتدا با استفاده از تکنیک‌‌های مختلف، ریسک‌های بحرانی پروژه شناسایی و اولویت‌بندی شده و سپس با استفاده از مدل‌سازی ساختاری تفسیری، روابط متقابل میان ریسک‌‌ها و قدرت تأثیرگذاری و تأثیرپذیری آن‌ها بر یکدیگر مشخص شدند. در این مقاله تلاش شد با استفاده از مدل‌سازی ساختاری تفسیری درک واقع‌بینانه‌تری جهت مواجهه با عدم اطمینان ناشی از ریسک‌های پروژه احداث خط لوله نفت یزد- نائین ایجاد گردد. نتایج پژوهش نشان داد که ریسک تحریم‌‌ها بر پروژه به جهت آنکه دارای بیشترین تأثیر بر سایر ریسک‌‌ها است و کمترین اثرپذیری را از آن‌ها دارد، می‌‌بایست در کانون توجه مدیریت ریسک قرار گیرد. همچنین ازآنجاکه در این پژوهش از نظرات کارشناسان و افراد خبره درگیر در پروژه استفاده گردیده است، انتظار می‌‌رود اجرای ساختار بیان‌‌شده در این مقاله بتواند در صورت بهکارگیری در پروژههای مشابه، تأثیر مثبت و به سزایی جهت تحقق اهداف پروژه از قبیل هزینه، زمان، محدوده پروژه، کیفیت و بهداشت، ایمنی و محیط‌زیست داشته باشد. | ||
| کلیدواژه‌ها | ||
| مدیریت ریسک؛ شناسایی ریسک؛ تجزیه‌وتحلیل ریسک؛ مدل‌سازی ساختاری تفسیری؛ تحلیل ماتریسی تأثیر متقابل | ||
| موضوعات | ||
| مدیریت ریسک | ||
| عنوان مقاله [English] | ||
| The Investigation of Risk Management at the Stage of Construction with Interpretive Structural Modeling method (Case Study: Yazd-Naein Oil Pipeline Construction Project) | ||
| نویسندگان [English] | ||
| Meysam Sohrabi؛ Heirsh Soltanpanah؛ AmirAsad Nasrizar؛ MohammadSedigh Sabeti | ||
| Ph.D. Candidate in Civil Engineering- Construction Engineering and Management, Department of Civil Engineering, Faculty of Science and Engineering, Islamic Azad University, Sanandaj Branch, Sanandaj, Iran. | ||
| چکیده [English] | ||
| Recognizing the nature of risks effectively on oil projects is an important issue in the risk management of companies such as the Iranian Oil Pipeline and Telecommunication Company. This study aims at identifying risks and extracting the structure of relationships between critical risks of the Yazd-Naein oil pipeline construction project using Interpretative Structural Modeling (ISM) to help the pillars of the project. To do this, using different techniques, first, the critical risks of the project are identified and prioritized, and then using ISM, the reciprocal relationships between risks and their effectiveness on each other are recognized. This study has attempted to make a more realistic comprehension for confrontation with non-security caused by the risks of the Yazd-Naein oil pipeline construction project using ISM. The results showed that sanctions risk on project has to be concentrated by risk management since it has the highest effect on other risks and the least affectability from them. Also, since the opinion of experts has been used in this study, in the case of using in similar projects, it is expected that the implementation of the mentioned structure may positively and significantly influence the achievement of project goals such as cost, time, project scope, quality and sanitation, security and environment. | ||
| کلیدواژه‌ها [English] | ||
| Risk management, risk identification, risk analysis, interpretive structural modeling (ISM), Cross-Impact matrix multiplication applied to classification | ||
| مراجع | ||
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[1] E. Banks, Risk culture: A practical guide to building and strengthening the fabric of risk management, Springer, 2012. [2] A. Correljé, C. Van der Linde, Energy supply security and geopolitics: A European perspective, Energy Policy, 34(5) (2006) 532–543. [3] A.B. Badiru, S.O. Osisanya, Project management for the oil and gas industry: a world system approach, CRC Press, 2013. [4] E. Briel, P. Luan, R. Westney, Built-In bias jeopardizes project success, Oil and Gas Facilities, 2(02) (2013) 19-24. [5] D. Cooper, S. Grey, G. Raymond, P. Walker, Managing risk in large projects and complex procurements, Chichester, John Willey and Sons Ltd, (2005). [6] D. Cooper, P. Bosnich, S. Grey, G. Purdy, G. Raymond, P. Walker, M. Wood, Project Risk Management Guidelines: Managing Risk with ISO 31000 and IEC 62198, John Wiley & Sons, 2014. [7] T. Aven, J.E. Vinnem, H.S. Wiencke, A decision framework for risk management, with application to the offshore oil and gas industry, Reliability Engineering & System Safety, 92(4) (2007) 433-448. [8] M. Basova, A. Mitselsky, Risk management KPIs: efficiency tool or formality, in: Enterprise Risk Management Symposium, Society of Actuaries, 2011. [9] C. Liu, X. Sun, J. Chen, J. Li, Statistical properties of country risk ratings under oil price volatility: Evidence from selected oil-exporting countries, Energy policy, 92 (2016) 234-245. [10] V.R. Tummala, J.F. Burchett, Applying a risk management process (RMP) to manage cost risk for an EHV transmission line project, International journal of project management, 17(4) (1999) 223-235. [11] B.W. Boehm, Software risk management: principles and practices, IEEE software, 8(1) (1991) 32-41. [12] R.M. Wideman, Project and program risk management a guide to managing project risks and opportunities, Project Management Institute, Inc., 1992. [13] C. Chapman, S. Ward, Project risk management processes, techniques and insights, John Wiley & Sons Ltd, 1997. [14] S.C. Ward, Assessing and managing important risks, International Journal of Project Management, 17(6) (1999) 331-336. [15] A. Airmic, Irm, A risk management standard, (2002). [16] A. Standard, Australian Standard/New Zealand Standard Risk Management 4360: 2004, Sydney and Wellington Author, (2004). [17] OfficeofGovernmentCommerce, Managing successful projects with PRINCE2, The Stationery Office, 2017. [18] PMI, A Guide to the Project Management Body of Knowledge (PMBOK Guide), Newtown Square, PA, USA: Project Management Institute, (2017). [19] PMI, Project Management Institute, a Guide to the Project Management Body of Knowledge (PMBOK). Newton Square, Project Management Institute, (2016). [20] R.V. Dandage, S.S. Mantha, S.B. Rane, V. Bhoola, Analysis of interactions among barriers in project risk management, Journal of Industrial Engineering International, 14 (2018) 153-169. [21] J. Peixoto, A. Tereso, G. Fernandes, R. Almeida, Project risk management methodology: a case study of an electric energy organization, Procedia Technology, 16 (2014) 1096-1105. [22] O. Shabarchin, S. Tesfamariam, Risk assessment of oil and gas pipelines with consideration of induced seismicity and internal corrosion, Journal of Loss Prevention in the Process Industries, 47 (2017) 85-94. [23] M. Bai, Y. Du, Y. Chen, Y. Xing, P. Zhao, Risk assessment of long gas and oil pipeline projects inducing landslide disasters during construction, Journal of performance of constructed facilities, 31(5) (2017) 04017063. [24] X. Yu, W. Liang, L. Zhang, G. Reniers, L. Lu, Risk assessment of the maintenance process for onshore oil and gas transmission pipelines under uncertainty, Reliability Engineering & System Safety, 177 (2018) 50-67. [25] L. Kraidi, R. Shah, W. Matipa, F. Borthwick, Analyzing the critical risk factors associated with oil and gas pipeline projects in Iraq, International Journal of Critical Infrastructure Protection, 24 (2019) 14-22. [26] W.-S. Wu, C.-F. Yang, J.-C. Chang, P.-A. Château, Y.-C. Chang, Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project, Reliability Engineering & System Safety, 142 (2015) 515-524. [27] T. Zuofa, E.G. Ochieng, Issues in risk management: the perspectives of managers in Nigeria’s oil and gas industry, International Journal of Engineering Research & Technology, 3(4) (2014) 369-374. [28] P.K. Dey, Managing project risk using combined analytic hierarchy process and risk map, Applied Soft Computing, 10(4) (2010) 990-1000. [29] M. Krechowicz, Comprehensive risk management in horizontal directional drilling projects, Journal of construction engineering and management, 146(5) (2020) 04020034. [30] J. Ghaobadi, J. Rezaeian, M. Haji Aghaei Keshteli, Identification and prioritization the risks of green building projects based on the combination of FANP and FDEMATEL:(case study: Savadkooh county), Amirkabir journal of civil engineering, 51(3) (2019) 599-616. [31] E. Jokar, B. Aminnejad, A. Lork, Risk Assessment and Prioritization in Projects with Private Public Participation Method Based on Combination of Fuzzy Multi-criteria Decision-Making Techniques (Case Study: North Freeway), Amirkabir Journal of Civil Engineering, 53(3) (2021) 847-862. [32] M.P. Jalal, S. Moradi, H. Niksirat, A Model For Managing The Risks of International Project Procurement of Iranian Companies (Case study-Syrian Cement and Venezuelan Cement projects), Amirkabir Journal of Civil Engineering, 54(3) (2022) 10-10. [33] PMI, A Guide to the Project Management Body of Knowledge (PMBOK Guide), Newtown Square, PA, USA: Project Management Institute, (2013). [34] S. Sushil, Interpreting the interpretive structural model, Glob. J. Flex. Syst. Manag, 13(2) (2012) 87-106. [35] S.K. Yadav, V. Tripathi, G. Goel, Modelling strategic orientation dimensions and performance of small and medium enterprises: An application of interpretative structural modelling, Journal of Modelling in Management, 14(3) (2019) 754-772. [36] S. Kumar Sharma, A. Bhat, Modelling supply chain agility enablers using ISM, Journal of modelling in management, 9(2) (2014) 200-214. [37] A. Verma, N. Seth, N. Singhal, Application of interpretive structural modelling to establish interrelationships among the enablers of supply chain competitiveness, Materials Today: Proceedings, 5(2) (2018) 4818-4823. [38] P. Charan, R. Shankar, R.K. Baisya, Analysis of interactions among the variables of supply chain performance measurement system implementation, Business Process Management Journal, 14(4) (2008) 512-529. [39] K. Govindan, M. Palaniappan, Q. Zhu, D. Kannan, Analysis of third party reverse logistics provider using interpretive structural modeling, International Journal of Production Economics, 140(1) (2012) 204-211. [40] A. Ramesh, D. Banwet, R. Shankar, Modeling the barriers of supply chain collaboration, Journal of Modelling in Management, 5(2) (2010) 176-193. [41] D.-W. Kwak, V.S. Rodrigues, R. Mason, S. Pettit, A. Beresford, Risk interaction identification in international supply chain logistics: Developing a holistic model, International Journal of Operations & Production Management, 38(2) (2018) 372-389. [42] V. Ravi, R. Shankar, Analysis of interactions among the barriers of reverse logistics, Technological Forecasting and Social Change, 72(8) (2005) 1011-1029. [43] A. Agarwal, R. Shankar, M. Tiwari, Modeling agility of supply chain, Industrial marketing management, 36(4) (2007) 443-457. | ||
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