Ergonomic Glove Design by Using an Integrated Approach

Abstract

Hand injuries in work accidents frequently occur in firm. The use of gloves as personal protective equipment is recommended by experts to reduce or prevent hand injuries. While these gloves increase the safety of employees against hand injuries, it is aimed not to have a negative impact on their performance. This study has determined 15 criteria for an ergonomic glove that will not decrease the performance of the employees, taking into consideration the literature research and expert opinions. The most suitable ergonomic glove was chosen among five alternative gloves by taking the opinions of three experts. This study aims to select the most suitable glove using the interval type-2 fuzzy (IT2F) number based TOPSIS approach. IT2F number is proposed to reduce the loss of information in expert opinions. Type-1 fuzzy number is shown with a single membership degree. IT2F number consists of two membership degrees unlike type-1 fuzzy number. The part between these two membership degrees expresses the expert opinion. The judgments of three experts were collected by employing the IT2F number and hand dexterity criterion was defined as the most significant criterion for an ergonomic glove. This paper also uses Bayesian network to analyze the customer satisfaction level based on four performance indicators. The biggest exchange for high customer satisfaction of alternative 1 is caused from finger root circumference between four performance indicators. This study ensures to the literature a new perspective by proposing multi-criteria decision making technique and Bayesian network to form an ergonomic glove.