A fuzzy project buffer management algorithm: a case study in the construction of a renewable project
Zohrehvandi, Shakib Khalilzadeh, Mohammad Amiri, Maghsoud Shadrokh, Shahram
Zohrehvandi, Shakib
Khalilzadeh, Mohammad
Amiri, Maghsoud
Shadrokh, Shahram
Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2023
Journal
International Journal of Construction Management
Book
Publication Volume
23
Publication Issue
12
Publication Begin page
2134
Publication End page
2143
Publication Number of pages
Collections
Abstract
One of the major problems with projects is that they are not completed according to schedule. Uncertainty always exists at the heart of real-world project scheduling problems. This paper introduces a fuzzy project buffer management (FPBM) algorithm which is a combination of the adaptive procedure with resource tightness (APRT) and fuzzy failure mode and effects analysis (FFMEA) methods. This paper aims to present an efficient model for project buffer sizing by taking FFMEA into account to reach a more realistic schedule. In this research, for increasing the efficiency of the APRT method, the FFMEA technique is simultaneously applied with them. This research was carried out as a case study in a renewable energy (RE) project. The methodology of this research consists of two phases. The first phase is the implementation of the APRT buffer sizing method. In the second phase of the research methodology, the fuzzy FMEA method is implemented. To validate the proposed model, the results are compared to several buffer management models proposed recently. Also, the results were compared with the results of similar projects. The findings show that considering the fuzzy FMEA technique in the APRT method, a more realistic schedule was obtained in this project.
Research Projects
Organizational Units
Journal Issue
Keywords
Critical Chain Project Management Method, Fuzzy Project Buffer Management, Project Scheduling, Renewable Energy Project, Project Buffer Sizing, Adaptive Procedure with Resource Tightness, Fuzzy Failure Mode and Effects Analysis