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Article
Publication date: 1 December 2006

Antonio C. Caputo and Pacifico M. Pelagagge

To develop a decision support system (DSS) and improved management criteria for operating dispenser‐based single‐piece automatic order picking systems (AOPS) in…

Abstract

Purpose

To develop a decision support system (DSS) and improved management criteria for operating dispenser‐based single‐piece automatic order picking systems (AOPS) in distribution centers, able to reduce the need for manual decision making based on personal experience or subjective judgement.

Design/methodology/approach

Simulation was utilized to analyze the relationships between stochastic demand, setup parameters and performances of an AOPS. A set of rules was then defined to cost‐effectively select the values of setup parameters. A DSS was built incorporating the heuristic rules to dynamically update the equipment setup.

Findings

Manual management of an AOPS can be poorly efficient even if largely practiced. Significant economic benefits may result from rule‐based equipment setup instead of the traditional manual decision approach. This was verified resorting to a case study referring to the distribution center of a leading pharmaceuticals distributor in Italy. Major performances improvements resulted regarding manual operation by an experienced logistic manager, including a 40 per cent reduction of the cost per picked order line.

Practical implications

The proposed DSS is able to monitor the system behaviour over a specified time window and automatically set the values of the state variables for the next period. It is able to automatically define the set of items to be allocated on to the machine, to select the number of storage locations allocated to each item and set reorder levels and maximum picking quantities for each item, thus greatly simplifying the task of the logistic manager. Utilization of this DSS enables one to maintain a high level of picking automation efficiency while drastically cutting the required support personnel, thus significantly improving profit margins of high‐volume high‐rotation distribution centers.

Originality/value

The paper addresses, with original methodology, a practically relevant issue which is neglected in the literature. The paper is aimed at distribution centers managers seeking to improve the performances of AOPS and reduce their operating costs.

Details

Industrial Management & Data Systems, vol. 106 no. 9
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 14 August 2017

Torsten Franzke, Eric H. Grosse, Christoph H. Glock and Ralf Elbert

Order picking is one of the most costly logistics processes in warehouses. As a result, the optimization of order picking processes has received an increased attention in…

Abstract

Purpose

Order picking is one of the most costly logistics processes in warehouses. As a result, the optimization of order picking processes has received an increased attention in recent years. One potential source for improving order picking is the reduction of picker blocking. The purpose of this paper is to investigate picker blocking under different storage assignment and order picker-route combinations and evaluate its effects on the performance of manual order picking processes.

Design/methodology/approach

This study develops an agent-based simulation model (ABS) for order picking in a rectangular warehouse. By employing an ABS, we are able to study the behaviour of individual order pickers and their interactions with the environment.

Findings

The simulation model determines shortest mean throughput times when the same routing policy is assigned to all order pickers. In addition, it evaluates the efficiency of alternative routing policies–storage assignment combinations.

Research limitations/implications

The paper implies that ABS is well-suited for further investigations in the field of picker blocking, for example, with respect to the individual behaviour of agents.

Practical implications

Based on the results of this paper, warehouse managers can choose an appropriate routing policy that best matches their storage assignment policy and the number of order pickers employed.

Originality/value

This paper is the first to comprehensively study the effects of different combinations of order picker routing and storage assignment policies on the occurrence of picker blocking.

Details

The International Journal of Logistics Management, vol. 28 no. 3
Type: Research Article
ISSN: 0957-4093

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Article
Publication date: 1 July 2002

Charles G. Petersen

In today’s competitive global economy, the focus is on faster delivery of small more frequent orders of inventory at a lower total cost. This often precludes the use of…

Abstract

In today’s competitive global economy, the focus is on faster delivery of small more frequent orders of inventory at a lower total cost. This often precludes the use of full pallet picking in warehouses so firms commonly use manual picking of cases and broken‐cases. Many firms increase the efficiency of their warehouses by using zone picking. Zone picking requires that a worker only pick those stock‐keeping units (SKUs) stored within their picking zone. In this paper we examine the configuration or shape of these picking zones by simulating a bin‐shelving warehouse to measure picker travel where SKUs are assigned storage locations either using random or volume‐based storage. The results show that the size or storage capacity of the zone, the number of items on the pick list, and the storage policy have a significant effect on picking zone configuration. In addition, we found that the absence of a back cross aisle also affected picking zone configuration. These results offer solutions to managers looking to implement improvements in distribution center operations.

Details

International Journal of Operations & Production Management, vol. 22 no. 7
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 1 February 1989

MARC GOETSCHALCKX and JALAL ASHAYERI

Two researchers suggest a new approach to the most fundamental warehousing operation of all.

Abstract

Two researchers suggest a new approach to the most fundamental warehousing operation of all.

Details

Logistics World, vol. 2 no. 2
Type: Research Article
ISSN: 0953-2137

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Article
Publication date: 19 July 2013

Eric H. Grosse and Christoph H. Glock

The purpose of this paper is to study the prevalence of human learning in the order picking process in an experimental study. Further, it aims to compare alternative…

Abstract

Purpose

The purpose of this paper is to study the prevalence of human learning in the order picking process in an experimental study. Further, it aims to compare alternative learning curves from the literature and to assess which learning curves are most suitable to describe learning in order picking.

Design/methodology/approach

An experimental study was conducted at a manufacturer of household products. Empirical data was collected in the order picking process, and six learning curves were fitted to the data in a regression analysis.

Findings

It is shown that learning occurs in order picking, and that the learning curves of Wright, De Jong and Dar‐El et al. and the three‐parameter hyperbolic model are suitable to approximate the learning effect. The Stanford B model and the time constant model led to unrealistic results.

Practical implications

The results imply that human learning should be considered in planning the order picking process, for example in designing the layout of the warehouse or in setting up work schedules.

Originality/value

The paper is the first to study learning effects in order picking systems, and one of the few papers that use empirical data from an industrial application to study learning effects.

Details

Journal of Manufacturing Technology Management, vol. 24 no. 6
Type: Research Article
ISSN: 1741-038X

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Article
Publication date: 1 October 2005

Charles G. Petersen, Charles Siu and Daniel R. Heiser

PurposeWith the current interest in all aspects of supply chain management, the demands on warehousing have changed significantly within the past few years. In an attempt…

Abstract

PurposeWith the current interest in all aspects of supply chain management, the demands on warehousing have changed significantly within the past few years. In an attempt to meet this challenge, warehouses have become more concerned with proper slotting and storage techniques. This paper seeks to evaluate slotting measures and storage assignment strategies in a simulated manual bin‐shelving (low level picker‐to‐part) warehouse in terms of travel distance and the fulfillment time to complete an order.Design/methodology/approachThe approach utilises Monte Carlo simulation of a manual bin‐shelving pick area.FindingsThe results illustrate that popularity, turnover, and cube‐per‐order index (COI) performed best among slotting measures. Several new storage assignment strategies utilizing the concept of “golden zone” picking, which slots high demand stock‐keeping units (SKUs) at the height between the picker's waist and shoulders, were introduced. Results from the simulation study show that the golden zone storage assignment strategies generated significant savings in order fulfillment time compared to storage policies that ignore the golden zone concept.Originality/valueProvides an evaluation of slotting measures and storage assignment strategies that generated significant savings in order fulfillment time.

Details

International Journal of Operations & Production Management, vol. 25 no. 10
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 1 August 2004

Charles G. Petersen, Gerald R. Aase and Daniel R. Heiser

Class‐based storage (CBS) partitions stock‐keeping units (SKUs) into storage classes by demand and randomly assigns storage locations within each storage class area. This…

Abstract

Class‐based storage (CBS) partitions stock‐keeping units (SKUs) into storage classes by demand and randomly assigns storage locations within each storage class area. This study compares the performance implications of CBS to both random and volume‐based storage (VBS) for a manual order picking warehouse. In addition, this study considers the effect of the number of storage classes, the partition of storage classes, and the storage implementation strategy applied in the warehouse. The simulation results show that CBS provides savings in picker travel over random storage and offers performance that approaches VBS. Other operational issues having an impact on warehouse performance are examined. The results offer managers insight for improving distribution center operations.

Details

International Journal of Physical Distribution & Logistics Management, vol. 34 no. 7
Type: Research Article
ISSN: 0960-0035

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Article
Publication date: 14 May 2018

Martina Calzavara, Alessandro Persona, Fabio Sgarbossa and Valentina Visentin

In order-picking activities, the performance of the system can be influenced by different variables such as the order to be fulfilled, the distance to be covered or the…

Abstract

Purpose

In order-picking activities, the performance of the system can be influenced by different variables such as the order to be fulfilled, the distance to be covered or the experience of operators. Usually, this kind of activity is performed by operators rather than machines to assure flexibility. Consequently, their fatigue accumulation can decrease the performance of the overall system. The purpose of this paper is to define the kind of device to be used in an order-picking context, to obtain data which can be utilized for the evaluation of the level of fatigue and to improve the performance of the picking system.

Design/methodology/approach

The paper presents a comparison between existing fatigue methods which can be applied in a picking context. In addition, an analysis of the physiological literature for the evaluation of a new device for the monitoring of fatigue level is carried on and its practical use is shown.

Findings

The proposed research identifies in the heart rate monitor the device that, thanks to its advantages, can be the best one to be used in an industrial context for monitoring the physical fatigue of operators.

Originality/value

This study considers the importance of human factors in picking activities such as physical fatigue of operators and the need to have validated tools to monitor and to define the level of fatigue accumulation in each activity of different rate and duration.

Details

Industrial Management & Data Systems, vol. 118 no. 4
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 1 February 1989

Klaus Baumeister

Researchers at IPA have designed an orderpicking robot with an intelligent multi‐part gripper

Abstract

Researchers at IPA have designed an orderpicking robot with an intelligent multi‐part gripper

Details

Industrial Robot: An International Journal, vol. 16 no. 2
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 14 June 2019

Fabio Sgarbossa, Martina Calzavara and Alessandro Persona

Vertical lift module (VLM) is a parts-to-picker system for order picking of small products, which are stored into two columns of trays served by a lifting crane. A…

Abstract

Purpose

Vertical lift module (VLM) is a parts-to-picker system for order picking of small products, which are stored into two columns of trays served by a lifting crane. A dual-bay VLM order picking (dual-bay VLM-OP) system is a particular solution where the operator works in parallel with the crane, allowing higher throughput performance. The purpose of this paper is to define models for different operating configurations able to improve the total throughput of the dual-bay VLM-OP system.

Design/methodology/approach

Analytical models are developed to estimate the throughput of a dual-bay VLM-OP. A deep evaluation has been carried out, considering different storage assignment policies and the sequencing retrieval of trays.

Findings

A more accurate estimation of the throughput is demonstrated, compared to the application of previous models. Some use guidelines for practitioners and academics are derived from the analysis based on real data.

Originality/value

Differing from previous contributions, these models include the acceleration/deceleration of the crane and the probability of storage and retrieve of each single tray. This permits to apply these models to different storage assignment policies and to suggest when these policies can be profitably applied. They can also model the sequencing retrieval of trays.

Details

Industrial Management & Data Systems, vol. 119 no. 6
Type: Research Article
ISSN: 0263-5577

Keywords

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