Designing lifting task in shoe industry using genetic algorithm

We present an application of a genetic algorithm (GA) based method to the design of hide-unloading job, an asymmetric lifting task in shoe industry of Agra, India. In India, which has the second largest shoe industry in the world, it is labor intensive and concentrated in the small and cottage industry sector with Agra being a major production hub. Due to awkward postures and high load handling in hide-unloading, workers are exposed to ergonomic hazards. The design of hide-unloading job in the present work with an aim to reduce the risk to back injury in the purview of revised NIOSH equation. We carry out our study in four shoe manufacturing firms in Agra. The study was conducted on a total of 20 workers, 5 from each firm. It is observed that workers assume different awkward postures mainly due to bulky and unstable load handling. The potency of the study is to present multiple optimal solutions to the design problem using GA while meeting safety and productivity requirements in a given workplace environment conditions. Multiple optimal solutions provide greater agility to ergonomist to implement the recommended design solutions.