Implementing Fuzzy TOPSIS on Project Risk Variable Ranking

Saiful Husin,Maimun Rizalihadi,Fachrurrazi Fachrurrazi,Mubarak Mubarak

doi:10.1155/2019/9283409

Abstract

Managing construction risks with a large number of risks with small impact can increase the additional effort and cost of inefficient construction. Therefore the variables need to be eliminated. The aim of this study is ranking the risk variable based on its frequency of occurrence by integrating time, cost, and quality criteria simultaneously and selecting the top ten variables with the order of the most significant impact. The risk variable ranking based on triple project objective of cost, time, and quality simultaneously is a challenge for particular projects or regions contributing to the risk context. A number of 127 qualitative risk variables of 14 factors occurring in a project to be eliminated require a method/technique. A fuzzy TOPSIS method involving linguistics data is proposed to capture vague conditions. Results show that the top ten rankings of risk variables based on integrating the different weights of cost, time, and quality are successfully identified by concluding that the labour factor is the most dominant variable affecting project risk in context the rehabilitation and reconstruction posttsunami disaster, especially in Aceh-Indonesia. The variables are lack of labour, unskilled labour, undisciplined labour, and low productivity of labour. This condition can differ from different risk contexts. This research is different from other studies that only review cost, time, and quality separately. We stated that to integrate all three criteria of cost, time, and quality simultaneously is more logic to analyze risk variable ranking.

Highlights

In last year’s, the development of risk analysis studies is increasing rapidly; this is due to proper risk assessment could decrease the failure rate to achieve the outcomes and objectives of budget, time, and quality for a project [1], especially in project involving massive resources, such as rehabilitation and reconstruction posttsunami disaster in Aceh-Indonesia [2]
To support this research paper, we introduce some methods of project risk that have been published and well described in [11,12,13,14,15,16,17,18,19,20]
We have ranked 127 variables of risk frequency based on the criteria weight for a time, cost, and quality simultaneously, as the triple constraints, using the fuzzy TOPSIS approach. is concept is different from other studies which generally use individually for each criterion of cost, time, or quality for the basis of the ranking of the project risk variables

Summary

Introduction

In last year’s, the development of risk analysis studies is increasing rapidly; this is due to proper risk assessment could decrease the failure rate to achieve the outcomes and objectives of budget, time, and quality for a project [1], especially in project involving massive resources, such as rehabilitation and reconstruction posttsunami disaster in Aceh-Indonesia [2]. E very high reconstruction intensity in the period can be used as a lesson learned for contractors to recognise the more complex project risks that may occur in other areas. Expansion of the size and complexity of a construction project would lead to an increase in the number of associated risk events rapidly [8]

Objectives

Methods

Results

Conclusion