Comparing order picking assisted by head-up display versus pick-by-light with explicit pick confirmation

Wu, Xiaolong; Haynes, Malcolm; Zhang, Yixin; Jiang, Ziyi; Shen, Zhenzhong; Guo, Anhong; Starner﻿﻿, Thad; Gilliland, Scott

doi:10.1145/2802083.2808408

Cited by 19 publications

(3 citation statements)

References 2 publications

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“…This popular technique relies on a multidimensional construct to derive an overall workload score based on a weighted average of ratings on six subscales: mental demand, physical demand, temporal demand, effort, frustration, and performance [34]. By studying the available literature [16,20,21,[35][36][37], it follows that this methodology is the most appropriate to assess the perceived workload with great success. Considering the implementation steps of this methodology, the adoption of NASA TLX requires the source of load and the magnitude of loads [38].…”

Section: Perceived Workload Evaluationmentioning

confidence: 99%

Investigating the Impact of Completion Time and Perceived Workload in Pickers-to-Parts Order-Picking Technologies: Evidence from Laboratory Experiments

Chondromatidis,

Gialos,

Zeimpekis

et al. 2024

Logistics

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Background: Despite the general impression that digital order-picking supportive technologies can manage a series of emerging challenges, there is still a very limited amount of research concerning the implementation and evaluation of such technologies in manual picker-to-goods order-picking systems. Therefore, this paper aims to evaluate the performance of three alternative picker-to-goods technologies (i.e., Pick-by-Radio Frequency (RF) Scanner, Pick-to-light, and Pick-by-vision) in terms of completion time and perceived workload. Methods: The Design of Experiments (DoE) methodology is adopted to investigate order-picking technologies in terms of completion time. More specifically, a full factorial design has been used (23 × 3 full factorial design) for the assessment of the aforementioned order-picking technologies via laboratory testing. Furthermore, for the comparative assessment of the reviewed order-picking technologies in terms of workload, the NASA Task Load Index (NASA-TLX) is embraced by system users. Results: The results reveal that the best picker-to-goods technology in terms of order-picking completion time and perceived workload under certain laboratory setup is light picking when combined with few items per order line and many order lines per order. Conclusion: The paper successfully identified the best picker-to-goods technology, however it is important to mention that the adoption of such order-picking technology implies certain managerial implications that include training programs for employees to ensure they are proficient in using such technologies, upfront costs for purchasing and implementing the order picking system, and adjustments to existing workflows.

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Section: Perceived Workload Evaluationmentioning

confidence: 99%

Investigating the Impact of Completion Time and Perceived Workload in Pickers-to-Parts Order-Picking Technologies: Evidence from Laboratory Experiments

Chondromatidis,

Gialos,

Zeimpekis

et al. 2024

Logistics

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“…Nichtsdestotrotz erzielen die Pick-by-Vision Methoden sehr gute Resultate und weisen in acht der neun Studien geringere Fehlerquoten auf. Nur bei der Studie von Wu et al (2015) ist die Fehlerquote 0,5 % höher als bei dem Pick-by-Light System. Hinsichtlich der Kommissionierdauer ist die Methode Pick-by-Vision in 67 % der Studien schneller als die verglichenen Verfahren.…”

Section: Kommissionierungunclassified

State-of-the-Art von Smart Glasses zur Unterstützung von Logistikprozessen

Hüer

Zobel²,

Birkel

et al. 2020

Smart Glasses

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Im Projekt GLASSHOUSE wird der praktische Einsatz von Smart Glasses als innovativer Technologietreiber im Dienstleistungsbereich der Logistik untersucht. Zu Beginn des Projekts sind noch nicht viele praktische Untersuchungen dieser Technologie in der zu untersuchenden Domäne erfolgt oder veröffentlicht. Um dennoch einen anfänglichen Wissens-und Kenntnisstand als Ausgangsbasis für weiterführende Untersuchungen benutzen zu können, wurde ein State-of-the-Art der Erkenntnisse aus Praxis und Wissenschaft mit der Anwendung von Smart Glasses im Logistiksektor erhoben. In diesem Beitrag werden Vorgehen und Ergebnisse dieser Initialuntersuchung präsentiert, gefolgt von einer Herleitung praktischer Anwendungsfälle für Smart Glasses entlang der logistischen Wertschöpfungskette.

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“…In terms of average task time, Ref. [17][18][19] reveal that the pick-by-HUD method was faster than the pick-by-light and the pick-by-paper methods. Likewise, the pick-by-HUD method was more accurate than all other methods considered.…”

Section: Introductionmentioning

confidence: 99%

A Joint Comparative Analysis of Routing Heuristics and Paperless Picking Technologies Using Simulation and Data Envelopment Analysis

Fontin

Lin

2020

Applied Sciences

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Recent literature demonstrates that warehouse order picking performance is reflected in the logistics performance of downstream retailers. Warehouse solutions and policies significantly contribute to the improvement of distribution and delivery to retailers. This paper therefore reports an analysis of the joint performance of routing policies and picking technologies, and provides insights into the best ways to combine routing strategies and paperless solutions in order to optimize cost efficiency. We follow a multistage approach that combines mixed integer linear programming algorithms, data envelopment analysis (DEA), and ranking and selection. The results show that traversal-voice picking and midpoint-voice picking combinations are equally distributed over the most efficient subsets and that superior technology can enhance picking efficiency only to a certain level. The study provides guidelines for logistics managers on ways to combine warehouse solutions and policies in order to better streamline the operations. It offers an original framework to analyze the joint performance of picking routing and picking solutions by considering the effect of picking errors.

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Comparing order picking assisted by head-up display versus pick-by-light with explicit pick confirmation

Cited by 19 publications

References 2 publications

Investigating the Impact of Completion Time and Perceived Workload in Pickers-to-Parts Order-Picking Technologies: Evidence from Laboratory Experiments

Investigating the Impact of Completion Time and Perceived Workload in Pickers-to-Parts Order-Picking Technologies: Evidence from Laboratory Experiments

State-of-the-Art von Smart Glasses zur Unterstützung von Logistikprozessen

A Joint Comparative Analysis of Routing Heuristics and Paperless Picking Technologies Using Simulation and Data Envelopment Analysis

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