Can we work more safely and healthily with robot partners? A human‐friendly robot–human‐coordinated order fulfillment scheme

Abstract This work addresses the issue of intelligent robot–human‐coordinated parts‐to‐picker order fulfillment carried out in a human‐friendly manner. One unique feature proposed approach involves integrating real‐time data‐driven stochastic‐dynamic model with fatigue accumulation function. The optimal solutions help achieve coordination between human pickers and robots, such that robots can agilely adapt to coordinated pickers’ efficiency conditions. Specifically, method estimates instantaneous performance robot queue lengths, which are then fed back real time as indexes adjust robots’ speeds handling racks moving them pickers. Using data provided by giant electronic commerce (e‐commerce) company, our analyses demonstrate robot–picker system permits alleviating picker's without much influence on picking efficiency. In particular, accumulated be reduced 53.74% at expense lowering picker 14.79% if is applied focal firm study case. Through scenario design sensitivity analysis, additional findings managerial insights, including rules behaviors for different operational scenarios provided. They facilitate development “human‐friendly” robot‐human‐coordinated order‐fulfillment systems logistics operations.