Performance optimisation of pick and transport robot in a picker to parts order picking system: a human-centric approach

Abstract

Picker to parts order picking (OP) systems are one of the most labour-intensive warehouse operations, accounting for 55% of warehouse expenses in the e-commerce industry. For this reason, the e-commerce industry has invested in fully automated and robotised warehouses. However, these warehouse solutions are very expensive. Furthermore, with the advent of Industry 5.0 with a human-centric focus, the OP system's automation should be designed and implemented in ways to improve the working conditions of the order pickers rather than replacing them completely. A pick and transport robot (PTR) is a solution for OP systems which is compatible with Industry 5.0. An example of such a solution is Grab™ by SOLWR. Previous studies have barely investigated the human factor effects of using PTRs in OP systems while optimising the performance of the systems. This research develops a mathematical model to optimise the performance of a picker to parts OP system using PTRs in terms of productivity, quality, and the well-being of the order pickers. The developed model is tested by using data from a case company. The results of this study support managerial decisions by achieving a better knowledge of how to set up such PTR solutions.