Proposing an Optimum Model for Time Estimation of Construction Projects in Iranian Gas Refineries

Time management can be effective in a project when the project schedule is based on comprehensive time scheduling. In the industries with complicated processes, many uncertainties and risks affect the timing of projects. Considering the very low reliability of the project planning in certainty-based approach, using more secure models for control and interact with uncertainty should be placed on the agenda. Iranian Gas Company has been using risk management to manage probable uncertainties in construction projects but in the field of possible uncertainties, actions are very scarce. This article aims to propose an optimum model based on the integrated risk management and fuzzy expert systems in order to provide comprehensive project time estimation and in this regard, reviews the results of the implementation of this model in construction projects of Iranian gas refineries. The results show that the proposed model increases the accuracy of time estimation about 8 to 24 percent.Time management can be effective in a project when the project schedule is based on comprehensive time scheduling. In the industries with complicated processes, many uncertainties and risks affect the timing of projects. Considering the very low reliability of the project planning in certainty-based approach, using more secure models for control and interact with uncertainty should be placed on the agenda. Iranian Gas Company has been using risk management to manage probable uncertainties in construction projects but in the field of possible uncertainties, actions are very scarce. This article aims to propose an optimum model based on the integrated risk management and fuzzy expert systems in order to provide comprehensive project time estimation and in this regard, reviews the results of the implementation of this model in construction projects of Iranian gas refineries. The results show that the proposed model increases the accuracy of time estimation about 8 to 24 percent

Multi-layer Decision methodology For ranking Z-numbers

The new concept of a – number has been recently introduced in decision making analysis. This concept is capable of effectively dealing with uncertainty in information about a decision. As this concept is relatively new in fuzzy sets, its underlying theoretical aspects have not been established yet. In this paper, a multi-layer methodology for ranking Z – numbers is proposed for the first time. This methodology consists of two layers: Z – number conversion as the first layer and fuzzy number ranking as the second layer. In this study, the conversion methodology of Z – numbers into fuzzy numbers is extended to conversion into standardised generalised fuzzy number so that the methodology is applicable to both positive and negative data values. The methodology is validated by means of thorough comparison with some established ranking methods for consistency purposes. This methodology is considered as a generic decision making procedure, especially when – numbers are applied to real decision making problems

RISK PRIORITY EVALUATION OF POWER TRANSFORMER PARTS BASED ON HYBRID FMEA FRAMEWORK UNDER HESITANT FUZZY ENVIRONMENT

The power transformer is one of the most critical facilities in the power system, and its running status directly impacts the power system's security. It is essential to research the risk priority evaluation of the power transformer parts. Failure mode and effects analysis (FMEA) is a methodology for analyzing the potential failure modes (FMs) within a system in various industrial devices. This study puts forward a hybrid FMEA framework integrating novel hesitant fuzzy aggregation tools and CRITIC (Criteria Importance Through Inter-criteria Correlation) method. In this framework, the hesitant fuzzy sets (HFSs) are used to depict the uncertainty in risk evaluation. Then, an improved HFWA (hesitant fuzzy weighted averaging) operator is adopted to fuse risk evaluation for FMEA experts. This aggregation manner can consider different lengths of HFSs and the support degrees among the FMEA experts. Next, the novel HFWGA (hesitant fuzzy weighted geometric averaging) operator with CRITIC weights is developed to determine the risk priority of each FM. This method can satisfy the multiplicative characteristic of the RPN (risk priority number) method of the conventional FMEA model and reflect the correlations between risk indicators. Finally, a real example of the risk priority evaluation of power transformer parts is given to show the applicability and feasibility of the proposed hybrid FMEA framework. Comparison and sensitivity studies are also offered to verify the effectiveness of the improved risk assessment approach