Systems failure analysis using Z-number theory-based combined compromise solution and full consistency method


Yousefi S., Valipour M., Gul M.

APPLIED SOFT COMPUTING, vol.113, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 113
  • Publication Date: 2021
  • Doi Number: 10.1016/j.asoc.2021.107902
  • Journal Name: APPLIED SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
  • Keywords: Risk assessment, Failure Mode and Effects Analysis, Full Consistency Method, Combined Compromise Solution, Z-number theory, RISK-EVALUATION, SELECTION, ENVIRONMENT, INDUSTRY, MODE, FMEA
  • Istanbul University Affiliated: No

Abstract

Financial and time constraints force managers to put limited failure modes in priority to implement corrective and preventive actions. Thus, how prioritization can be done more constructively is of particular importance. This study aims to introduce an improved Failure Modes and Effects Analysis (FMEA) technique based on an extension of the Combined Compromise Solution (CoCoSo) method and the Full Consistency Method (FUCOM) to assess and prioritize failures in a production process. These developed methods called Z-CoCoSo and Z-FUCOM rely on the Z-number theory. They can consider uncertainty and reliability simultaneously in determining the weights of risk factors and the value of these factors in the studied problem. The proposed approach can cover some shortcomings of the conventional FMEA technique employed in identifying potential failures before their occurrence. Applying this approach enables experts to consider different weights for risk factors and uncertainty in the risk assessment process and provides them with a reliable ranking with high separability. Implementing the introduced approach for a real case study in the automotive parts industry has been compared with FMEA and other existent versions of the used methods demonstrating its reliable prioritization. (C) 2021 Elsevier B.V. All rights reserved.