Assessing risk through composite FMEA with pairwise matrix and Markov chains

Purpose: Failure mode and effect analysis (FMEA) is an analysis technique for identifying and eliminating known and/or potential failures and problems from products, processes or systems. Notwithstanding its diffusion, traditional FMEA has several limitations. Lately, scientific research has been focused on improving said limitations, yet the process is still ongoing. The purpose of this paper is to support developments in this area. Design/methodology/approach: The paper improves the conventional FMEA by using the method of pairwise comparison to establish the relative importance of the input factors in risk priority number calculation, and Markov chains to calculate risk distributions in the long term. Findings: The functioning and usefulness of the proposed methodology is demonstrated through an application to the construction industry, one of the world’s biggest industrial sectors, dogged by a high rate of work-related injuries and casualties. Originality/value: Having demonstrated the applicability of the novel methodology to a real domain, the paper contributes to the process of overcoming traditional FMEA limitations.