مدیریت ریسک مبتنی بر سیستم‏های خبره فازی در پروژه‌های ساخت

نوع مقاله : مقاله پژوهشی

نویسنده

دانشجوی کارشناسی ارشد مهندسی و مدیریت ساخت دانشگاه پیام نور البرز، ایران

چکیده

با گسترش و توسعه روز افزون پروژه‌ها و پیچده‌تر شدن آن‌ها، نیاز به ابزارهای جدید برای کمک به مدیریت پروژه‌ها الزامی است. از جمله‌ی این ابزارها مدیریت ریسک است، چرا که در یک محیط بی‌ثبات و نامعین، هر لحظه می‌توان انتظار وقوع رخدادهای خارج از برنامه و غیر منتظره را داشت. غالباً از دانش افراد خبره برای ارزیابی ریسک پروژه‌ها استفاده می‌گردد اما انسان‌ها همواره از کلمات و عباراتی در محاورات خود استفاده می‌کنند که مرزهای روشنی برای خود ندارند. برای برخورد با چنین کلمات و عبارات مبهمی از منطق فازی بهره گرفته می‌شود. تئوری مجموعه‌های فازی روشی است که کارایی خود را برای مدیریت عدم قطعیت‌هایی مشابه موارد ذکر شده در مورد پروژه‌های ساخت نشان داده است. سیستم خبره‌ی فازی عبارت است از یک سیستم خبره یا سیستم مبتنی بر دانش که برای استدلال داده‌ها از مجموعه‌یی از توابع عضویت و قواعد فازی به جای منطق دودویی استفاده می‌کند. برای سیستم‌های با عدم قطعیت زیاد که اطلاعات کافی و دقیقی نیز در دسترس نیست، رویکرد استدلال تقریبی فازی مطرح می‌شود. ورودی سیستم فازی می‌تواند اطلاعات نادقیق باشد و پردازش‌های سیستم نیز با بهره‌گیری از استدلال تقریبی انجام می‌شوند. در این تحقیق به بررسی ریسک‌های موجود در پروژه‌های عمرانی از طریق کسب نظرات خبرگان حوزه‌های کارفرمایی، مشاور و پیمانکاری پرداخته شد. با ارائه گام‌بندی سعی در شناسایی ریسک‌ها، ارزیابی آن‌ها و کنترل ریسک‌های با اولویت بالا با استفاده از منطق فازی و سیستم‌های خبره داشته‌ایم.

کلیدواژه‌ها


عنوان مقاله [English]

Risk Management Based on Fuzzy Expert Systems in Construction Projects

نویسنده [English]

  • Somayeh Ghorbani Noe
Master of Engineering and Construction Management, Payam Noor University of Alborz, Iran
چکیده [English]

As projects grow and develop and become more complex, new tools are needed to help manage projects. One of these tools is risk management, because in an unstable and uncertain environment, one can expect Out-of-schedule and unexpected events at any time. Experts' knowledge is often used to assess the risk of projects, but humans always use words and phrases in their conversations that have no clear boundaries. Fuzzy logic is used to deal with such ambiguous words and phrases. Fuzzy set theory is a method that has proven effective in managing uncertainties similar to those mentioned in construction projects. A fuzzy expert system is an expert or knowledge-based system that uses a set of fuzzy membership functions and rules to reason data instead of binary logic. For systems with high uncertainty where sufficient and accurate information is not available, the fuzzy approximation reasoning approach is proposed. Fuzzy system input can be inaccurate information and system processing is done using approximate reasoning. In this study, the risks in construction projects were investigated by obtaining the opinions of experts in the fields of clients, consultants and contractors. By providing steps, we have tried to identify risks, evaluate them, and control high-priority risks using fuzzy logic and expert systems.

کلیدواژه‌ها [English]

  • Risk Management
  • Fuzzy logic
  • Uncertainty
  • Expert Systems
  • Approximate Reasoning
  • Abu Mousa Hmaid, Risk Management in Construction Projects from Contractors and Owners" perspectives
  • A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in construction Management., The Islamic University of Gaza – Palestine, March, 2005.
  • Admian, Mohammad Hadi; Mehran Zeinalian and Mohammad Javad Amini, 2015, Risk planning, analysis and management in construction projects using program risk analysis method and advanced APRAM model in terms of risks throughout the project life cycle, 10th International Congress of Civil Engineering, Tabriz, University of Tabriz Faculty of Civil Engineering, 2015, Persian.
  • Alipouri, Yaqub, Ardeshir, Abdullah, Sibt, Mohammad Hassan, Fazel Zarandi, Mohammad Hussein. (1394). Application of fuzzy expert system and genetic algorithm to score the performance of safety management in Iranian construction workshops: a study of safety environment factors and personal experience. Sharif Civil Engineering, 31.2 (4.1), 31-39, 2015, Persian.
  • Daud Mohamad, Fatin Liyana Mukhtar, Weighted Mamdani-type Fuzzy Inference System Based on Relative Ideal Preference System, Journal of Soft Computing and Decision Support Systems, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia, August 2018.
  • Fadhili, Ally, RISK MANAGEMENT IN CONSTRUCTION PROJECT Case study of building and civil contractors‟ in partial fulfillment of the requirements for the award of the master‟s degree of „construction economics and management’, 2013.
  • Fadilah Najwa Nina, Apol Pribadi Subriadi, A Need to Modify the Method of Failure Mode and Effect Analysis (FMEA) and Risk Management, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Surabaya, Indonesia, IJSRCSEIT,Volume 3, Issue 6, ISSN : 2456-3307, 2018 .
  • Fallah, Ahmad Ali, Masoud Zeini, Kamran Farrokhi and Morteza Hassannejad, Identification and Analysis of Dam Risks Using FMEA Technique, Case Study of Alborz Babol Dam, 3rd International Conference on New Approaches to Energy Conservation 2014, Persian.
  • GAJEWSKA EWELINA, MIKAELA ROPEL, Risk Management Practices in a Construction Project– a case study, Master of Science Thesis in the Master’s Programme Design and Construction Project Management, Department of Civil and Environmental Engineering Division of Construction Management CHALMERS UNIVERSITY OF TECHNOLOGY, Göteborg, Sweden 2011.
  • Khanzadi, Mustafa; Sajjad Hosseinpour; Ali Golshan and Yasin Vazirinia, 2017, Risk Management and Stakeholders' Perspectives on Civil Projects, International Conference on Civil Engineering, Architecture and Urban Planning in Contemporary Iran, Tehran, Osweh University - Tehran - Shahid Beheshti University, 2017, Persian.
  • Naderpour, Abbas, Mofid, Massoud, Sardrood injured, Javad. (1398). Integrating risk management and fuzzy inference system to estimate project execution time in gas refineries (Case study: Khangiran Campus Complex construction project). Sharif Civil Engineering. 35.2 (1.2), 41-49, 2019, Persian.
  • Nasirzadeh, Farnad, Khanzadi, Mostafa, Afshar, Abbas. (1393). Simulate the simultaneous consequences of risks on project cost and time, taking into account uncertainties. Sharif Civil Engineering, Volume 2-30 (1.1), 3-11, 2014, Persian.
  • Otobo Odimabo, Onengiyeofori, Risk Management System To Guide Building Construction Projects’ In Developing Countries: A Case Study Of Nigeria PhD February, 2016
  • Peng-cheng Li, Chen Guo-hua, Dai Li-cao, Zhang Li, Fuzzy logic-based approach for identifying the risk importance of human error, Institute of Safety Science and Engineering, South China University of Technology, Guangzhou, Elsevier Ltd., 2010.
  • Roghanian Emad, Fatemeh Mojibian, Using fuzzy FMEA and fuzzy logic in project risk management, Iranian Journal of Management Studies (IJMS), Vol. 8, No. 3, Print ISSN: 2008-7055, pp: 373-395, July 2015.
  • Soleimanpour Hashemi, Neda and Seyed Mohammad Hijrati, 2016, Risk Management of Construction Projects Based on PMBOK Standard Project on Construction of the Panoramic Museum of Jerusalem, International Conference on Civil Engineering, Architecture and Urban Landscape, Turkey-Istanbul University, Permanent Secretariat of the Conference, Istanbul University, 2016, Persian.
  • Tavakolan Mehdi, Construction Risk Management Framework using Fuzzy sets and Failure Mode and Effect Analysis, University of Tehran, 2015.
  • Carr, J.H.M. Tah, A fuzzy approach to construction project risk assessment and analysis: construction project risk management system, Civil-Comp Ltd and Elsevier Science Ltd, 2001.
  • Zahraei, Banafsheh, Roozbehani, Abbas, Mirshakari, Mostafa. (1395). Provide a risk analysis model based on fuzzy expert systems for managing construction projects. Sharif Civil Engineering. Volume 2-32, Number 1/4, Winter, Pages 61 to 70, 2016, Persian.