An interventionist strategy for warehouse order picking: Evidence from two case studies

Giannikas, Vaggelis; Lu, Wenrong; Robertson, Brian; McFarlane, Duncan

doi:10.1016/j.ijpe.2017.04.002

Cited by 57 publications

(48 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Very different application cases are discussed in research approaches, from fruit picking in agriculture to online retail order picking in e-commerce. In general, the important message herein is the fact that individual product characteristics and requirements shape many of the typical design elements of order picking systems, especially the efficient level of automation [27][28][29][30][31][32][33][34][35].…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Order Picking and E-Commerce: Introducing Non-Parametric Efficiency Measurement for Sustainable Retail Logistics

Klumpp

Loske

2021

JTAER

View full text Add to dashboard Cite

Order picking is a crucial but labor- and cost-intensive activity in the retail logistics and e-commerce domain. Comprehensive changes are implemented in this field due to new technologies like AI and automation. Nevertheless, human worker’s activities will be required for quite some time in the future. This fosters the necessity of evaluating manual picker-to-part operations. We apply the non-parametric Data Envelopment Analysis (DEA) to evaluate the efficiency of n = 23 order pickers processing 6109 batches with 865,410 stock keeping units (SKUs). We use distance per location, picks per location, as well as volume per SKU as inputs and picks per hour as output. As the convexity axiom of standard DEA models cannot be fully satisfied when using ratio measures with different denominators, we apply the Free Disposal Hull (FDH) approach that does not assume convexity. Validating the efficiency scores with the company’s efficiency assessment, operationalized by premium payments shows a 93% goodness=of-fit for the proposed model. The formulated non-parametric approach and its empirical application are promising ways forward in implementing empirical efficiency measurements for order picking operations within e-commerce operations.

show abstract

Section: Theoretical Frameworkmentioning

confidence: 99%

Order Picking and E-Commerce: Introducing Non-Parametric Efficiency Measurement for Sustainable Retail Logistics

Klumpp

Loske

2021

JTAER

View full text Add to dashboard Cite

show abstract

“…By far, order picking is the area, where most research in terms of AR application in logistics can be found. Due to its operational complexity and economical relevance (more than 50% of warehousing costs incurred in picking area) [12], it is also the field where huge potential of process optimization in logistics exists. Previous research mainly focused on how an operator could be aided by using AR [13], what is the most effective way to indicate a storage location to a picker [14].…”

Section: Identification Of Ar Application In Inhouse Logisticsmentioning

confidence: 99%

Application of Augmented Reality (AR) Technologies in inhouse Logistics

Wang

Wang²,

Song

et al. 2020

E3S Web Conf.

View full text Add to dashboard Cite

As a new information technology, mobile augmented reality (AR) technology has attracted more and more attention in recent years. Mobile AR uses mobile terminal, with the help of entity object recognition, obtains virtual information through calculation or in database, and superimposes virtual information on live video to realize the "enhancement" of virtual information to reality. In order to explore the application of AR technology in inhouse logistics, this paper analyses the principle and technical characteristics of AR technology. By analysing the application status of AR technology in inhouse logistics, the application advantages of AR technology in inhouse logistics are obtained. This paper summarizes 36 cases of AR technology application in inhouse logistics, summarizes and analyses the application prospect of AR technology in inhouse logistics. The functions of AR technology in the process of receiving, storage, sorting, transportation, inventory and planning are put forward. It provides theoretical guidance for the practical application of AR technology in inhouse logistics., 0 Web of Conferences https://doi.org/10.

show abstract

“…In a dynamic order pick system, order throughput time is more convenient to evaluate performances. As in our case a non-dynamic order pick system is assumed and both performance measures are highly correlated, total order pick time is minimized in this study as this mostly results in the smallest order throughput time as well (Giannikas et al, 2017).…”

Section: Performance Measuresmentioning

confidence: 99%

Increasing order picking efficiency by integrating storage, batching, zone picking, and routing policy decisions

Gils

Ramaekers

Braekers

et al. 2018

International Journal of Production Economics

View full text Add to dashboard Cite

In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. The main objectives of this research are to determine which order picking planning problems are related, to explain why and how individual planning problems are related, and to identify excellent performing policy combinations in several practical situations. Previous research shows contradictory findings on which planning problems are related. This paper is the first that explicitly analyzes and statistically proves the relations between storage, batching, zoning, and routing by a full factorial ANOVA. The value of combining the four main order picking planning problems is shown with a real-life case study as well as for multiple generalized warehouse designs. The results of the study clearly indicate that warehouses can achieve significant benefits by considering storage, batching, zone picking, and routing policies simultaneously. Awareness of the influence of an individual planning problem on the overall order picking performance is required to manage warehouse operations, resulting in a reduced order pick time.

show abstract

An interventionist strategy for warehouse order picking: Evidence from two case studies

Cited by 57 publications

References 58 publications

Order Picking and E-Commerce: Introducing Non-Parametric Efficiency Measurement for Sustainable Retail Logistics

Order Picking and E-Commerce: Introducing Non-Parametric Efficiency Measurement for Sustainable Retail Logistics

Application of Augmented Reality (AR) Technologies in inhouse Logistics

Increasing order picking efficiency by integrating storage, batching, zone picking, and routing policy decisions

Contact Info

Product

Resources

About