Optimization Design of Operational Postures for Intelligent Warehouse Pickers – An Empirical Study Based on Human Factors Engineering

Against the backdrop of the rapid development of e-commerce logistics, human factor efficiency issues in the order picking of intelligent warehouses have become increasingly prominent. This study takes intelligent warehouse centers in Chengdu as research objects, based on the theoretical framework of human factors engineering, and conducts in-depth analysis of key problems in pickers’ operational postures through systematic literature research and on-site empirical investigations. It proposes a dual-dimensional solution integrating shelf system optimization and intelligent tool integration. The research finds that bending movements account for 33% of existing picking processes, leading to a high incidence of occupational injuries such as lumbar muscle strain reaching 67%. The core reasons include unreasonable shelf heights, insufficient tool adaptability, and redundant operational processes. Through the comprehensive application of golden working zone planning, lifting picking trolleys, and gesture control technology, it is expected to reduce bending movements by 50% and improve operational efficiency by nearly 20%. This provides a replicable practical path for human factor optimization in intelligent warehouses. The research results not only have practical significance for reducing occupational injury risks but also enrich the application paradigm of human factors engineering in the logistics field from a theoretical perspective.