Studying Order Picking in an Operating Automobile Manufacturing Plant

Baumann, Hannes; Starner﻿﻿, Thad; Zschaler, Patrick

doi:10.1109/iswc.2012.24

Cited by 9 publications

(6 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Currently, a number of modern technological tools are gaining ground in the warehousing sector. Examples are pick by vision (Schwerdtfeger et al 2011), which makes use of head-mounted displays to support pickers with augmented reality, pick by tablet (Baumann, Starner, and Zschaler 2012), which uses a tablet computer with relevant information for the picker attached to the pick cart, and pick by point (Rudow 2012), which uses a moving beamer to project a point at the appropriate picking locations. However, this paper focuses on three of the more mature and most widely used technological tools: RF-terminal picking, PbV and PtL.…”

Section: Literature Review 21 Order Pickingmentioning

confidence: 99%

Exploring the role of picker personality in predicting picking performance with pick by voice, pick to light and RF-terminal picking

Vries

Koster

Stam

2015

International Journal of Production Research

View full text Add to dashboard Cite

Order pickers and individual differences between them could have a substantial impact on picking performance, but are largely ignored in studies on order picking. This paper explores the role of individual differences in picking performance with various picking tools (pick by voice, RF-terminal picking and pick to light) and methods (parallel, zone and dynamic zone picking). A unique realistic field experiment with 101 participants (academic students, vocational students and professional pickers) is employed to investigate the influence of individual differences, especially the Big Five personality traits, on picking performance in terms of productivity and quality. The results suggest that (PbV) performs better than RF-terminal picking, and that Neuroticism, Extraversion, Conscientiousness and the age of the picker play a significant role in predicting picking performance with voice and RF-terminals. Furthermore, achieving higher productivity appears to be possible without sacrificing quality. Managers can increase picking performance by incorporating the insights in assigning the right pickers to work with a particular picking tool or method, leading to increased picking performance and reduced warehousing costs.

show abstract

Section: Literature Review 21 Order Pickingmentioning

confidence: 99%

Exploring the role of picker personality in predicting picking performance with pick by voice, pick to light and RF-terminal picking

Vries

Koster

Stam

2015

International Journal of Production Research

View full text Add to dashboard Cite

show abstract

“…However, according to participant preferences, HUD (including the backpack) was no less comfortable than light, and was significantly more comfortable than paper. Previous work has shown that pickby-HUD in real-world warehouses can be used by workers continuously over weeks without difficulty [3]. Improvements in miniaturization (i.e., Google Glass) may further improve comfort of pick-by-HUD.…”

Section: Critiquing Different Systemsmentioning

confidence: 99%

“…Another study showed how to improve pick speed and accuracy with pick-by-HUD by associating colors with shelves and shapes with bins [7]. Although pick-by-light has been compared qualitatively to pick-by-HUD in the field in a commercial facility [3], pick-by-HUD has not been quantitatively evaluated against pick-by-light in a controlled study. The same field study introduced the idea of using a display mounted on the picker's mobile cart to show the needed picking chart, but no quantitative evaluation was performed.…”

Section: Introduction and Related Workmentioning

confidence: 99%

A comparison of order picking assisted by head-up display (HUD), cart-mounted display (CMD), light, and paper pick list

Guo

Raghu

Xie

et al. 2014

Proceedings of the 2014 ACM International Symposium on Wearable Computers

Self Cite

View full text Add to dashboard Cite

Wearable and contextually aware technologies have great applicability in task guidance systems. Order picking is the task of collecting items from inventory in a warehouse and sorting them for distribution; this process accounts for about 60% of the total operational costs of these warehouses. Current practice in industry includes paper pick lists and pick-bylight systems. We evaluated order picking assisted by four approaches: head-up display (HUD); cart-mounted display (CMD); pick-by-light; and paper pick list. We report accuracy, error types, task time, subjective task load and user preferences for all four approaches. The findings suggest that pick-by-HUD and pick-by-CMD are superior on all metrics to the current practices of pick-by-paper and pick-by-light.

show abstract

“…Results can be very contrary. Some users would not want to use HMD for a whole workday, while others can use them continuously over weeks [21]. The growing number of studies certainly have a positive impact on clarifying the unexplored.…”

Section: Discussionmentioning

confidence: 99%

Potential of Smart Glasses in Manual Order Picking Systems

Gajšek¹,

Herzog²

2020

dtssehs

View full text Add to dashboard Cite

Full automation of order picking "man-to-goods" workplaces still will not be rational in the near future. Humans will stay central actors and as such, they will determine system's effectiveness and efficiency. Order picking activities are labour intensive and time-consuming. Smart glasses are one of the possibilities to relieve order-picker's hands, resulting in reduced time consumption. In the paper, we review scientific literature on use of smart glasses in manual order picking system and outline the opportunities for future research.Available scientific papers on smart glasses topic deal with unique environments characterized by layout, equipment, process, specific combination of technologies etc. Most authors agree that their findings cannot be generalized. There are no studies in the literature on the effects of multiple-hour use of smart eyeglasses on the eyes.Warehouse systems are mostly not identical, even employees have different characteristics and attentiveness to technology. It is proposed to test each system before implementation and try to combine technologies for best results. Different systems tends to different goals, for example fast service or zero errors. The production system's outputs are also very likely influenced by software and user interface design, which indicates the need for additional research. The growing number of studies certainly have a positive impact on clarifying the unexplored. The area of smart glasses currently represents a great research potential.

show abstract

Studying Order Picking in an Operating Automobile Manufacturing Plant

Cited by 9 publications

References 3 publications

Exploring the role of picker personality in predicting picking performance with pick by voice, pick to light and RF-terminal picking

Exploring the role of picker personality in predicting picking performance with pick by voice, pick to light and RF-terminal picking

A comparison of order picking assisted by head-up display (HUD), cart-mounted display (CMD), light, and paper pick list

Potential of Smart Glasses in Manual Order Picking Systems

Contact Info

Product

Resources

About