Minimization of metabolic energy expenditure in collaborative order picking

Year 2023, Issue: 055, 132 - 145, 31.12.2023

Mahmut Tutam

https://doi.org/10.59313/jsr-a.1354278

Abstract

Order picking is one of the most repetitive, labor-intensive, and physically demanding operations in warehouses. Picking hundreds of orders daily requires high metabolic energy expenditure and is characterized by poor ergonomics posing high risks for musculoskeletal disorders. In traditional order picking, the order picker walks around racks in a warehouse throughout the day. Alternatively, it is aimed at minimizing inefficient time and musculoskeletal strains with ride-on order picking by allowing the order picker to stand on an operator’s platform of an order-picking truck and ride the truck between stop locations. However, the order picker has to step down from the platform at each stop location and step up onto the platform before riding the truck to the next stop location. Therefore, riding the truck with frequent stops leads to more metabolic energy expenditure and musculoskeletal disorders than walking, although it is faster. Benefiting advantages of both traditional and ride-on order picking, a relatively new order picking truck (collaborative order picking truck) is deployed in warehouses to reduce inefficient walking time and ergonomic riding disorders. In collaborative order picking, the order picker can walk from a stop location directly to the next pick location while the truck moves to the next stop location autonomously or ride the truck to the next stop location in case of having a large distance between stop locations. This paper develops an optimization model to minimize total metabolic energy expenditure in collaborative order picking by finding the shortest route and the best collaboration decision (walk or ride). Based on the Monte Carlo simulation, the metabolic energy expenditure with collaborative order picking is analyzed. Our results indicate metabolic energy savings with collaborative order picking up to 200% and 83% compared to traditional and ride-on order picking, respectively.

Keywords

Order picking, Collaborative Robot, Optimal Routing, Ergonomics, Metabolic Energy Expenditure

Supporting Institution

The Scientific and Technological Research Council of Türkiye

Project Number

1059B191900637

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