Potential of Smart Glasses in Manual Order Picking Systems

Gajšek, Brigita; Herzog, Nataša Vujica

doi:10.12783/dtssehs/ise2018/33645

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…Accordingly, order picking operations are intensively studied in the literature by focusing mainly on travel time minimization, hence the maximization of order picking productivity [5][6]. However, ergonomics is relatively less mentioned in academic studies [7] even though order pickers are exposed to high ergonomic disorders due to abnormal postures, excessive force, and task repetition [6][7]. Moreover, operational models did not include human factors sufficiently [10].…”

Section: Introductionmentioning

confidence: 99%

Minimization of metabolic energy expenditure in collaborative order picking

TUTAM

2023

JSR-A

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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.

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Section: Introductionmentioning

confidence: 99%

Minimization of metabolic energy expenditure in collaborative order picking

TUTAM

2023

JSR-A

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Potentials and challenges of augmented reality smart glasses in logistics and supply chain management: a systematic literature review

Rejeb

Keogh

Leong

et al. 2021

International Journal of Production Research

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Investigating the Performance of the Order-Picking Process by Using Smart Glasses: A Laboratory Experimental Approach

2022

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Background: Order picking process is critical for accurate and efficient order fulfilment. Pick-by-vision is a promising technology that may support order picking process, however there is still a limited amount of research concerning the impact of this technology on the performance of order-picking. The purpose of this paper is to investigate certain operational and technical parameters that affect the performance of pick-by-vision technology in item-level order picking via a series of laboratory tests. Methods: A systematic literature review is conducted for the identification of parameters that affect pick-by-vision performance. Subsequently, the analytical hierarchy process is adopted to rank these parameters, concerning their impact on order picking. Then, the design of experiment and NASA task load index methodology are implemented for assessing pick-by-vision efficiency and perceived workload. Results: The results reveal the parameters that significantly affect the performance of the pick-by-vision system, as well as the best configuration of parameters for the implementation of the proposed system in real environments. Conclusions: The results obtained are encouraging, showing how pick-by-vision technology can support order picking efficiency. Furthermore, practical implications are presented that deal with the organizational culture, process re-engineering, staff resistance to change, and motivation for maintaining the new way of executing order-picking processes.

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Potential of Smart Glasses in Manual Order Picking Systems

Cited by 3 publications

References 10 publications

Minimization of metabolic energy expenditure in collaborative order picking

Minimization of metabolic energy expenditure in collaborative order picking

Potentials and challenges of augmented reality smart glasses in logistics and supply chain management: a systematic literature review

Investigating the Performance of the Order-Picking Process by Using Smart Glasses: A Laboratory Experimental Approach

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