Systematic Approach of TOPSIS Decision-Making for Construction Method Based on Risk Reduction Feedback of Extended QFD-FMEA

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Abstract

The key factors in the decision-making process are uncertainty, probability, and impact. The appropriate construction methods must be selected based on review safety requirements, which are to be adjusted accordingly depending on highly uncertain and continually changing technological requirements. The evaluation of the construction method should account for various technical characteristics of the method, including changeable safety risk reduction. In most cases, the decision maker's insufficient knowledge and response to an uncertain and changing environment contribute primarily to the selection of inappropriate construction methods. This paper presents a feedback-based decision-making model that involves systematic safety evaluation and changing environmental risks for selecting the construction method using a technique for order preference by similarity to ideal solution (TOPSIS) model, which is a multicriteria decision-making tool, and extended quality function deployment-failure mode effect analysis (extended QFD-FMEA) simultaneously. Extended QFD-FMEA model presented herein provides an objective and quantitative analysis of risk reduction and mitigation based on the risk assessment and safety cost of construction methods. Risk factors are analyzed comprehensively to minimize safety uncertainties. The proposed decision-making process is based on a changing risk environment, where a tradeoff exists between technological options and safety issues. A case study is conducted to verify the proposed model. Results of risk assessment and possible risk reduction are presented using the extended QFD-FMEA, where two cases of feedback process in decision-making are presented for selecting the most appropriate construction method.

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Cho, J., & Chae, M. (2022). Systematic Approach of TOPSIS Decision-Making for Construction Method Based on Risk Reduction Feedback of Extended QFD-FMEA. Mathematical Problems in Engineering, 2022. https://doi.org/10.1155/2022/1458599

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