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An Integrated Bayesian BWM and Classifiable TOPSIS Model for Risk Assessment

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Multi-Criteria Decision Analysis for Risk Assessment and Management

Part of the book series: Industrial Ecology and Environmental Management ((IEEM,volume 1))

Abstract

Due to the constant occurrence of natural disasters and human error, risk assessment has become one of the indispensable tasks for governments, organizations, enterprises, etc. In recent years, the risk assessment model based on multiple criteria decision-making (MCDM) is quite popular. Methodologies of this type must rely on experts to assist decision-making in order to make risk analysis results more reliable. However, best-worst method (BWM) is based on pairwise comparison to determine the weight method, which overcomes many shortcomings of analytic hierarchy process (AHP). Currently, BWM has been widely used in various risk management and decision-making issues. In this study, we propose an integrated Bayesian BWM and classifiable technique for order preference by similarity ideal solution (classifiable TOPSIS) model to rank critical failure modes. First, Bayesian BWM is used to generate the group weights of risk factors. Bayesian BWM optimizes original BWM, which effectively integrates the judgments of multiple experts. Then, classifiable TOPSIS is used to rank and classify failure modes. The feasibility of the proposed model was demonstrated by conducting a case study involving a computer numerical control (CNC) rotary table. The analysis results showed that the model can effectively help risk analysts in assessing the risk level of failure modes.

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Author information

Authors and Affiliations

  1. Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan

    Huai-Wei Lo

  2. Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan

    James J. H. Liou

Authors
  1. Huai-Wei Lo
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  2. James J. H. Liou
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Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China

    Jingzheng Ren

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Lo, HW., Liou, J.J.H. (2021). An Integrated Bayesian BWM and Classifiable TOPSIS Model for Risk Assessment. In: Ren, J. (eds) Multi-Criteria Decision Analysis for Risk Assessment and Management. Industrial Ecology and Environmental Management, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-78152-1_2

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