Developing a fuzzy analytic hierarchy process (AHP) model for behavior-based safety management

Abstract

Safety management (SM) is a very important element within an effective manufacturing organization. One of the most important components of SM is to maintain the safety of work systems in the workplace. Safety of work systems is a function of many factors which affect the system, and these factors affect the safety of work systems simultaneously. For this reason, measuring work system safety needs a holistic approach. In this study, the work safety issue is studied through the analytic hierarchy process (AHP) approach which allows both multi-criteria and simultaneous evaluation. Another limitation faced in SM is the inability to measure the variables exactly and objectively. Generally, the factors affecting work system safety have non-physical structures. Therefore, the real problem can be represented in a better way by using fuzzy numbers instead of numbers to evaluate these factors. In this study, a fuzzy AHP approach is proposed to determine the level of faulty behavior risk (FBR) in work systems. The proposed method is applied in a real manufacturing company. In the application, factors causing faulty behavior are weighted with triangular fuzzy numbers in pairwise comparisons. These factors are evaluated based on the work system by using these weights and fuzzy linguistic variables. As a result of this evaluation FBR levels of work systems are determined and different studies are planned for work systems according to the FBR levels. In this way, faulty behavior is prevented before occurrence and work system safety is improved.