Elsevier

Computers & Industrial Engineering

Volume 111, September 2017, Pages 527-536
Computers & Industrial Engineering

Analysis of economic and ergonomic performance measures of different rack layouts in an order picking warehouse

https://doi.org/10.1016/j.cie.2016.07.001Get rights and content

Highlights

Abstract

Manual order picking ranks among the most time- and cost-intensive activities in warehouses, and it has frequently been studied in the past. The aim of existing studies was to improve the operational efficiency of order picking processes mainly by developing planning models that help to reduce the time that is needed for order picking. As order picking is still performed manually with technical support in most warehouses, human workers play an important role for order picking performance. Although it is recognized that manual material handling activities in warehouses expose workers to a high risk of developing musculoskeletal disorders, integrated planning approaches that consider both economic and ergonomic objectives in order picking design are still rare. This paper contributes to closing this research gap by developing economic and ergonomic performance measures for the case where orders are picked from pallets, half-pallets and half-pallets equipped with a pull-out system. The comprehensive analysis of the different rack layouts shows that there are opportunities to replace the traditional pallet storage system by half-pallets with a pull-out system on the lower rank to improve both ergonomics and economic performance.

Introduction

Warehouses are important elements of each supply chain. Warehousing processes need to be managed efficiently to achieve short order throughput times, high product availability and quick deliveries, which are important dimensions of customer service. Even though warehousing processes can be automated in general, most companies, in particular small and medium-sized enterprises, still rely on manual materials handling to ensure high levels of flexibility and to avoid investments (Richards, 2014).

A very important activity in warehouses that is performed manually for the most part is order picking, which is commonly referred to as the process of retrieving items from storage locations to fulfill customer orders. Several studies confirmed that order picking is one of the most time- and cost-intensive warehousing activities (e.g., De Koster et al., 2007, Frazelle, 2002, Rushton et al., 2014, Tompkins et al., 2010). Repetitive materials handling activities in order picking, such as continuous lifting/handling of heavy loads, expose workers to a high risk of developing injuries due to a gradual and cumulative deterioration of the musculoskeletal system, also referred to as musculoskeletal disorders (MSDs). The fact that MSDs are a pressing problem in order picking is frequently reflected in occupational illness figures (Grosse et al., 2015, Lavender et al., 2012). In the UK, for example, the total number of MSD cases in 2013/14 accounted for over 43% of all work-related illness cases (Buckley, 2014). In the European transport and storage sector, MSDs accounted for over 62% of all work-related health problems in 2007 (Eurostat, 2009a), and about 40% of the reported occupational illnesses cases in warehouses in the US in 2014 (BLS, 2015). In total, 100 million Europeans are meanwhile affected by MSDs (Lidgren, Gomez-Barrena, Duda, Puhl, & Carr, 2014). The still increasing financial burden of MSDs is up to 2% of the gross national product (GNP) in the European Union (Schneider & Irastorza, 2010).

In the EU, 40% of the total workforce, i.e. 80 million individuals, are exposed to factors that can adversely affect physical health (Eurostat, 2009b). In order picking, these factors and related risks for developing MSDs are mainly determined by the design of the operations system (cf. Neumann & Village, 2012). Examples of order picking design aspects that physically affect human work are the height and depth of racks, the weight of handled items or the light level (Grosse et al., 2015). As to the rack layout, the design (or the choice of a specific rack) determines both the time to pick items from storage positions and the energy expenditure that is needed for workers to fulfill these task. Especially picking from pallets often requires workers to twist, bend, kneel and stretch, which increases the risk of developing MSDs (Bureau of Labor Statsitics, 2015, Denis et al., 2006).

A recent study showed that decision support models for order picking have mainly focused on improving economic goals (such as reducing order picking time), and that they neglected the interaction between the design of the order picking system and human factors, leading to a significant research gap (Grosse et al., 2015). By integrating ergonomic performance measures into decision support models for order picking, it is possible to reach economic performance goals and to design the order picking process in such a way that health risks resulting from order picking are minimized. Improving ergonomics in order picking may not only contribute to a positive work-life-balance for workers, but also improve performance goals by reducing illness cases and absence from work (Grosse et al., 2015).

The paper at hand addresses this research gap and develops a mathematical model that can be used to evaluate how the layout of storage racks and the way products are stored on racks in the warehouse impact both economic and ergonomic performance measures. The focus of this study is on a situation where items are picked from pallets, half-pallets and/or half-pallets equipped with a pull-out system. Due to the interdisciplinary character of this paper, the model proposed here can be used as a decision support tool to assess the best combination of the rack alternatives, which contributes to reducing order picking time and costs as well as worker illness caused by poor working postures. Moreover, the reported numerical analysis shows an application of the model with the aim of deriving general guidelines for managerial decision making in case stored products have different characteristics.

The remainder of the paper is structured as follows. The following section discusses literature related to order picking and human factors. Section 3 describes the problem under study, and a mathematical model for an integrated analysis of economic and ergonomic performance measures of different rack layouts is developed in Section 4. The model is evaluated in a numerical analysis in Section 5. Implications of the results and recommendations are derived in Section 6, and the paper concludes in Section 7.

Section snippets

Literature review

In manual order picking systems, order pickers walk or drive along the aisles of the warehouse to retrieve items from shelves or pallets (Dallari, Marchet, & Melacini, 2009). The literature on manual order picking has mainly focused on economic performance measures, such as the minimization of travel time/distance or the reduction of order throughput times (De Koster et al., 2007, Grosse et al., 2016a). To achieve these goals, researchers have developed decision support models that can be

Problem description

The paper at hand considers a warehouse that uses racks for storing items, where each rack has a zone that order pickers can easily access without requiring additional technical devices (such as forklift trucks, ladders etc.). This zone has often been referred to as the forward zone (Bartholdi & Hackman, 2014). In practice, such a zone would usually not be higher than two meters. Above this lower-level pick zone, a reserve area could be available that provides additional storage space to be

Model development

The development of the models for evaluating the five rack layouts is split up into two parts, namely the proposal of an economic model (cost) and the proposal of an ergonomic model (human energy expenditure); all notations used are listed in Table 1. For developing the objective functions of the economic and ergonomic models, we split up the pick process into different tasks that are then evaluated both from an economic and an ergonomic point of view. In the economic evaluation, we also

Numerical analysis of different scenarios

The economic and ergonomic models introduced in the previous section are now used to compare the performance of the five proposed rack configurations (Fig. 1). In the following analysis, we study the impact of different product characteristics, in terms of pick frequency, item volume and weight, on the economic and ergonomic performance of the rack configurations. This parametrical analysis helps evaluating which rack configuration should be used for which type of product, also considering the

Economic comparison

A closer analysis of Fig. 3 shows that for products that are only picked a couple of times per month (here: Qi=10), the best rack configuration from a cost perspective is always the one with two half-pallets. Storing products on traditional pallets, in turn, becomes more economical when the product is picked with a higher frequency (here: Qi=500) and/or the products have a large volume (here: VCi=0.125). Clearly, using full pallets in this case helps to avoid frequent pallet replenishments,

Conclusion

Due to the large amount of manual material handling, the order picking zone represents one of the most critical areas of a warehouse both with respect to time, quality, and health risks. This makes an integrated economic and ergonomic assessment of order picking tasks necessary. This paper proposed an approach to analyze different technical design options for order picking racks (namely traditional pallets, half-pallets, and half-pallets equipped with a pull-out system) from an economic as well

Acknowledgments

The authors want to thank the anonymous referees for their valuable suggestions that helped to improve an earlier version of this paper.

References (59)

  • M.M. Ayoub

    Problems and solutions in manual materials handling: The state of the art

    Ergonomics

    (1992)
  • J.J. Bartholdi et al.

    Warehouse and distribution science

    (2014)
  • D. Battini et al.

    Order picking system design: The storage assignment and travel distance estimation (SA&TDE) joint method

    International Journal of Production Research

    (2015)
  • D. Battini et al.

    A comparative analysis of different paperless picking systems

    Industrial Management & Data Systems

    (2015)
  • D. Battini et al.

    Ergonomics in assembly line balancing based on energy expenditure: A multi-objective model

    International Journal of Production Research

    (2015)
  • F. Bindi et al.

    Similarity-based storage allocation rules in an order picking system: An application to the food service industry

    International Journal of Logistics Research and Applications

    (2009)
  • Y.A. Bozer et al.

    Order batching in walk-and-pick order picking systems

    International Journal of Production Research

    (2008)
  • P. Buckley

    Musculoskeletal disorders in Great Britain 2014, health and safety executive

    (2014)
  • Bureau of Labor Statsitics

    Nonfatal occupational injuries and illnesses requiring days away from work

    (2015)
  • F. Caron et al.

    Routing policies and COI-based storage policies in picker-to-part systems

    International Journal of Production Research

    (1998)
  • C. Chackelson et al.

    Evaluating order picking performance trade-offs by configuring main operating strategies in a retail distributor: A design of experiments approach

    International Journal of Production Research

    (2013)
  • F. Dallari et al.

    Design of order picking system

    International Journal of Advanced Manufacturing Technology

    (2009)
  • J. De Vries et al.

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

    International Journal of Production Research

    (2015)
  • J. De Vries et al.

    Aligning order picking methods, incentive systems, and regulatory focus to increase performance

    Production and Operations Management

    (2016)
  • J. De Vries et al.

    Safety does not happen by accident: antecedents to a safer warehouse

    Production and Operations Management

    (2016)
  • Eurostat

    European business – facts and figures

    (2009)
  • Eurostat

    8.6% of workers in the EU experienced work-related health problems

    (2009)
  • C. Finnsgård et al.

    Factors impacting manual picking on assembly lines: An experiment in the automotive industry

    International Journal of Production Research

    (2013)
  • E. Frazelle

    World-class warehousing and material handling

    (2002)
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