Analysis of economic and ergonomic performance measures of different rack layouts in an order picking warehouse
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: ), 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: ) and/or the products have a large volume (here: ). 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.
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