AN APPROACH OF ORDER-PICKING TECHNOLOGY SELECTION

Transcription

1 AN APPROACH OF ORDER-PICKING TECHNOLOGY SELECTION Dragan Đurđević Momčilo Miljuš Belgrade University Faculty of Tansport and Traffic Engineering Vojvode Stepe 305, Belgrade, Serbia ABSTRACT The benefits resulting of storage function still justify the substantial costs arising from them. Therefore, the storage system has two fundamental and conflicting objectives - reducing operation costs and increase service level. Solving this type of task can be set up as: an issue of design problem and control problem. This paper considers the problems of designing the warehouse, primarily on warehouses with the dominant orderpicking function (a typical distribution warehouses). Reason is that this function generates significantly the cost of warehouse but also determines the service level for their customers. As a result, a design of such warehouses is primarily focused on resolving of order-picking technology selection. This problem, despite its importance, is not adequately present in the literature. This paper proposes an approach that could be used to support the selection of case picking technology in the design of the warehouse. Keywords: warehouse design, case order-picking, technology selection 1 INTRODUCTION AND LITERATURE OVERVIEW Warehouses are an essential part of logistics processes and supply chains. There are a lot of reasons which support existence of warehouse and they are very well described in available literature [1]. In supply chains there are various types of warehouses, among them distribution warehouse is specific one. According to Berg [2], a distribution warehouse is a warehouse in which products from different suppliers are collected (and sometimes assembled) for delivery to a number of customers. The main function of distribution warehouse is to store products and fulfill external customer orders, typically composed of the large number of order lines (where each order line specifies a quantity of one particular product). The key objectives of such warehouses are to, be able quickly to fill orders with the minimum amount of effort and costs. That is the main task of order picking (OP) function and procedure of designing such warehouses should mostly focus to solving this function. From that reason, the choice of appropriate concept of order picking systems (OPS) has great impact on realization of this function and performances of entire warehouses. In many projects, order picking requires most of the operative personnel and offers the best opportunities for saving costs and improving performances. It is therefore advisable to plan the OPS first, and to develop the storage and transport systems afterwards. [3]. When selecting OPS, designer has to choose the applicable technological concepts provided a decision to introduce order pick area (OPA) by specifying the type of the space and the selection of technology inside that area (an equipment(s) type/number and suitable operational policies). Numerous design and cost parameters, combined with an endless variety of equipment types, make it difficult to specify an OPS. So, this problem, despite its importance, is not adequately present in the literature. Certain aspects (for example choice of type of OPA, 1

2 technology selection in OPA etc) connected with deciding OPA concept selection were subjects in papers [4, 5, 6, 7, 8, 9, 10]. Gudehus [4] dealt with problem of separating OPA and reserve area (RA) by analyzing different aspects which follows this decision. In conclusion of his paper, Gudehaus characterizes problem of separating OPA and RA as complex problem, hard to be solved in common case and labels it as problem that needs future research. Yoon and Sharp [5] overview decision about OPA in context of defining system structure made eight functional departments areas: receiving area, palette reserve area, case picking area, piece picking area, sorting area A and B, unitizing area consolidation and shipping area, mutually connected by twenty potential flows with proper load types. As central, direct question they ask the question: which products for which orders will flow through warehouse in which certain way? But, in suggested design procedure they do not give explicit answer to these questions and to question of deciding certain system structure decision of OPA. Suzuki S. [6] also dealt with decisions about OPA type, presenting graphic method as help (support) for making decisions in design process. In this paper he analyzes and makes connections between orders, units and amount of product being separated. Based on graphical presentations of these connections, it is possible to make decision whether it is necessary to provide separate functional area for each type of order picking (related to type of order picking unit) or should they be integrated with others. Problem with using this approach is related to data availability (detail level) in early designing phases when these decisions are being made. Paper [7] deals with significance of data (about product and orders) and their appropriate analysis in design process for making key decisions (introducing OPA, decisions on order picking strategy, storing technology and others). Hassan [8] presents one method for warehouse layout design which consists of 14 mutually depending steps. Basically, in suggested method, certain questions that deal with OPA problem are discussed. These questions are related to introducing appropriate system structure by defining storage areas (which would correspond to basic warehouse functions like receiving, storing, packing, sorting, shipping) and to question of separating storage area to reserve area (RA) and OPA. He mentions that separating storage area is being done to increase efficiency of operations and reducing of handling tasks, and is led by several factors like: demand, size and unit load type. Problem of OPA technology choice, as one of specific problems of this group, is basically question of choosing OPA type. Problem of decision between two basic OPS types - Man-to-goods vs. Goods-to-man, is mainly described by White [9] and he gives the aspects which can influence the choice. Major issues affecting the design of an OPS are material properties, economic constraints, environmental constraints, system requirements, operating strategies and transaction data [5]. Dallari et al. [10] gives one interesting approach to choosing type of OPS. They give recommendations for choice of OPS technological shape based on results by OPS analysis performed in over 68 warehouses of different distribution centers (DC) in Italy built in period from Conducted analysis shows that following parameters have critical impact on choice of OPS technology: amount of activity (defined by number of order lines on daily basis), products unit number and average order size. Based on analysis conducted over these parameters, authors have created matrix of deciding as a tool for making decision of choosing OPA technology, which they suggest to designers. Having previous in mind, the aim of this paper is that for specific order picking task (OPT), from group of potential, suggests access to choice of appropriate OPS configurations for case picking as dominant shape of order picking unit in DC warehouses. Suggested access would be support to designers of warehouse systems in concept design phase. Respecting previous, this paper is structured in following way: after introduction (chapter 1), chapter 2 is devoted on defining characteristics of OPT; chapter 3 is focused on overview of potential 2

3 OPS alternatives; chapter 4 presents proposed approach to OPS concept selection; and finally it is ended with contain (chapter 5). 2 DEFINING CHARACTERISTICS OF ORDER PICKING TASKS While designing an OPS [11], a designer must consider the following question: which picking system best meets a given set of objectives? Some of the objectives a designer is required to optimize include maximizing throughput or minimizing cost, space, response time, or error-rate, or a combination thereof. To answer this question, the designer typically follows the standard engineering design process, which involves the following: define the problem, analyze the problem, generate alternatives, evaluate the alternatives, select the preferred design and implement the design. The design process for warehouse (focused on OPS) can be divided into two major phases: concept and detailed design. Concept design phase makes the basic foundations of future system by defining (generating) variant technology concepts (typically 2-5), which are developed in detailed design phase (by making specific project decisions and procedures) until final solution. Process of defining alternative concepts consider choice of acceptablesuitable from bigger group of possible solutions. Choice of variant acceptable OPS concepts depends on their ability to realize order picking task (OPT). Therefore is important, as the first step and preliminary part, to identify all relevant characteristics of OPT and then to formulate OPT in adeqauate manner. Well formulated OPT is necessary precondition for successful realization of concept phase. OPT consists of more components demands, with specific qualitative and/or quantitative characteristics. The qualitative and quantitative requirements for OPS can be derived from the products, orders, system demands and limits. These demands, each by itself, with its specific characteristics, can be seen in big number of variants. Theoretically speaking, number of possible combinations, or potential OPT variants is very big. In concrete project, it is not useful, nor reasonable to include all OPT potential combinations into analysis. From that reason, analysis is limited to characteristic OPT, that contains typical and realistic demand combinations in function from warehouse type where OPS is being developed (in this case distributive warehouses). According to such choice, here is given the overview of necessary data (which are possible to get in this design phase) with their basic parameters:: Assortment number of different products Inventory level by products (maximum, medium, minimal, the characteristics of the products, such as size, weight, quantity per carton, quantity per pallet, fragility, temperature needed for storage, value, FIFO requirements etc., the sales volume of each product, and how this volume is distributed (many requests for small quantities or just a few requests for large quantities), the number of orders per day, the sizes of the orders in terms of number of lines with data about number of products, total weight, total cubic volume, the methods of receiving products and shipping orders (full pallet quantities on full trucks, or mixed pallets on less-than-truckload (LTL) carriers, or cartons on package carrier trucks such as UPS or Federal Express), the costs and availability of labor, the costs and availability of land and buildings, order lead time, throughput capacity, service level, assortment oscillations/trends, change of demands' characteristics and so on. 3

4 This shows clearly that OPT is complex multidimensional value, among whose components (demands) are present all significant interaction relations that must be respected. Because of that, OPT description can't and shouldn't be only sum of partially determined characteristics, but should also include synergistic impact of important OPT components which are obtained by using appropriate analytic procedures and methods, as it has been presented in [12]. Here is very important to say that it is necessary to conduct process of certain data subgroup for making appropriate design decisions in order to obtain authoritative information for further design phases. 3 OVERVIEW OF POTENTIAL VARIANT OPS CONCEPTS In concept phase of warehouse design, designer has to choose the applicable technological concepts OPS by making, first of all, decisions that deals of three aspects of problems: space, technology and organization. These decisions specify OPA type, technology in OPA and order picking alternatives. The mentioned decisions are in high level of correlation and dependence, and only their specific combinations are potentially feasible alternatives. For need of overview of potential alternatives, this paper gives separate overview and description of alternative OPA shapes, alternative OPA technologies and order picking strategies. 3.1 Alternative OPA concepts Concept of warehouse solution-structure based on specialization of warehouse areas for their primary activities, assumes that certain areas in warehouse are shaped only for storing function (preserving good reserve area (RA)) with aim of more efficient utilization of storing space, while physically separated OPA are shaped as special, which provides preconditions for more efficient order picking. Implementing and OPA design is motivated by expected positive effects from items concentration (which is object of order picking) and order picking processes realization on smaller space (higher density of order picking). This approach in development of warehouse layout provides that order-picking process could be realized in more efficient way, mostly by: reducing unproductive movements of order picker, easier and faster locating of ordered items, easier process management, which all together contribute on reducing service time per order. Besides named positive effects, these OPA solutions are followed by increased requirements for storage space and materials handling requirements (on replenishment from RA to OPA) and additional costs when specialized technology/equipment is involved. This paper assumes following OPA and RA correlation (Figure 1): (V1) OPA integrated with RA (V2) OPA is located in lower levels of RA- vertical separation (V3) OPA dislocated from RA. (V1) OPA integrated with RA as organizational shape assumes that order picking activities (defined by order) for palettes and cases unit loads are realized in the same warehouse space (in the aisle). (V2) Vertical separation - OPA is located in lower levels of RA - is organizational shape which assumes that certain parts of warehouses lower level in storage area are dedicated especially for case picking, while items replenishment in order-picking level is realized from RA. Such technology requires that width of such aisle should be designed to provide simultaneous storing/retrieving and order-picking activities. In lower level of palette racks, in accordance with characteristics of order picking activities and aiming to increase picking density in OPA, it is possible to apply other technologies: shelves for manual handling, gravity-flow racks, etc. 4

5 (V3) OPA dislocated fromra is organizational concept based on separated RA and OPA in space manner. This concept provides preconditions for higher performances achievement in OPA and RA. This alternative warehouse concept generates additional demands for: warehouse space, investment into efficient order-picking technologies and material handling requirements (on replenishment from RA to OPA). I/O OPA integreted with RA (V1) OPA=RA RA RA OPA I/O OPA and RA - vertical separation (V2) OPA 3.2 Alternative technology in OPA I/O I/O OPA dislocated from RA (V3) Figure 1: Alternative shapes of OPA There is great number of various types of OPS in usage, which are classified by different criteria in literature [12, 13, 14], and according to need of concrete research. This paper gives overview of typical order picking technologies, suitable for case picking. Starting from technological aspect (linked to movement of order picker in process of order picking) the most used is classification of OPS to: Man-to-goods Goods-to-man Automatic Man-to-goods is system where order picker in realization of OPT walks to warehouse locations with goods (most often in OPA) to pick suitable number of goods units. Since the order picking activity is executed in working aisle, this class of OPS is also known as»in-theaisle«system (80% of all OPS in Western Europe are based on this system [14]). The movement, based on type of used technology in OPS systems can be: horizontal (on the floor), but also both horizontal and vertical (the examples are cherry picker and man-on-board in case of order picking in high racks when order picked on handling equipment can realize both types of movements). Typical technological types of this OPS can be shown by different combination of for warehouse and handling technologies, as shown in Table 1 [15]. Warehouse technology Pallet storage technology (pallet racks) picking height low high Table 1: Subtypes of OPS in the aisle walk Walk and pick with order picking carts or order picking on the pallet on pallet jack movement Order picking truck without lifting mechanized Order picking lift truck for picking in vertical locations cherry picker Man-on board 5

6 Basically, here could be recognized two systems: (i) systems where order picker picks goods from lower level rack (standard height up to 2m), moving along storage aisles on foot or on equipment (example: systems where good picking is realized on pallet jack or walkie forklift truck), and (ii) systems which have high-rack structures where order picker goes to location of good needed to be picked. Typical representatives of these systems are OPS based on cherry picker and man-on board. Beside mentioned technological types of this system, in this group is also type Pick-to Roller Conveyor. In this alternative, empty pallet are inducted onto a pallet roller conveyor at beginning of case pick line. Pallets pass by order pickers stationed at zones along the pick line. Order picker picks units of good in his zone and put them on pallet. This technology of OPS is closely linked with usage of certain method of order picking, pick and pass [15]. Goods-to-Man is realized when materials to be picked is on time transferred from storage area and placed on picking point, where ordered items are usually picked from pallet. Rest of items (on pallet as storage unit) is returned to storage area. Generally, those systems involve higher automated systems as AS/RS (Automated Storage and Retrieval Systems). Automated Case Picking systems [12] can be used to fully automate the putaway and retrieval of individual cases. In some systems, cases are housed in gravity flow racks. A shuttle table and a telescoping conveyor are attached to a vertical mast that travels on rails along the picking/putaway face. For putaway, a transport conveyor feeds individual cases to the telescoping conveyor. The cases travel up and along the telescoping conveyor to the putaway location. The shuttle table rides up the mast and horizontally with the mast to the putaway location. The telescoping conveyor feeds cases to the shuttle table, which in turn inserts cases in a gravity flow rack lane (Figure 2). The picking process is the putaway process in reverse. This technology is usually involved when OPA is dislocated from RA. Figure 2: Automated case dispensing system Tier (or Layer) Picking [12] are used to mechanically extract an entire layer of cases from a pallet. A variety of mechanical approaches for layer picking are available, including (1) vacuum suction and conveyor singulation of the top layer, (2) four-sided clamping and conveyor singulation, and (3) layer stripping conveyors, which literally lift up the front edge of the top layer and strip it away from the remaining layers. The advantage of layer picking is the total elimination of human handling of the cases and high case-handling capacity. Layer pickers can typically only be justified when customers tend to order in high-volume, layer quantities and when the cost of labor is high. 6

7 3.3 Order Picking Strategies During OPS concept development one of important factor is to decide in which way should user order be fulfilled by OPS. In practice we can see three basic types: discrete picking, batch picking and zone picking. Discrete picking (or single order picking strategy) is realized when one order picker fulfill only one order on time, passing through warehouse and picking ordered items, which are then sent to packing or shipping area. In situations of orders with lot of lines (what is typical for DC warehouses), it is possible to create efficient order picking cycle in warehouse. Batch picking strategy is based on grouping (collecting) of set of orders into a number of sub-sets, and transformation into specific order-list (batch order). In this strategy, each order picker simultaneously is picking items due to orders for more customers. So, it is obvious that the main advantage of batch strategy is traveling time reduction per line (unit). However, using this strategy could result with lowering of order's integrity and generating additional manipulation tasks, as it is later sorting (except when sort-while-pick method is used), etc. That is the reason why benefits of time per line reduction have to be compared with additional sort costs and possible errors when this strategy is used. Generally, this strategy is acceptable when huge number of orders (with less then five lines per order) is realized. Zone picking is method based on principle that each order picker has "its own" storage zone (part of OPA), where he is picking ordered items. Typically, it is used in warehouses where different shapes and technologies are present. Segments of orders are picked in different zones. When picking of partial parts of orders in different zones is finished, it is necessary to integrate (or sort) partial parts of picked items before order have to be delivered from warehouse. In practice, different combinations of mentioned tree basic strategies could be applied [15]. Using these strategies are connected to different OPT characteristic combinations (discussed in chapter 2). 4 AN APPROACH TO ORDER PICKING SYSTEM CONCEPT SELECTION While development of OPS variable concepts in technological design of warehouse, designer must decide between two concepts V1 versus V2 (see Chapter 3). The answer to this question usually depends on various factors that could be on different level of complexity and mutual dependence. Knowing that we speak about order picking processes in DC, for simplification we can say that primary factors with impact on warehouse functioning are number of items storing (and picking) and demanded throughput productivity of warehouse. From that reason, for practical solution of given problem (and assumed warehouse concept) the most suitable is to use comparing costs of this alternatives in function of these factors as criteria. Not using detail analysis of big number of variables that impact expenses and other warehouse performances (which is good in this design phase), here are given characteristic expenses which can be observed as basic during these analysis. Those are: costs of used space, costs of working force, costs of necessary storage equipment and their exploitation. Of course, the other costs could be also added (depending on different performances involved). In order to overview mutual impacts in warehouse system in this design phase, it is suitable to analyze changes of these costs as function of different variables [4]. Here, analyze is based on defined (given) warehouse throughput (expressed in units loads/time unit) and product assortment change in warehouse. With increase of assortment, both concepts clearly show that required space for RA is growing. 7

8 With (V2) concept, by increasing assortment it is necessary to place greater number of palettes with different products in OPA, which proportionally extends OPA in storage area. Increased length of OPA for given throughput impacts on the engagement of warehouse resources. Greater requirements could be realized by increase of intensity of work of existing working force/equipment or by increase of their number in system, with direct consequences to this group of costs. Increase of OPA in this concept also has worse density in storage zone as consequence, meaning decrease of use of available area/volume, which can significantly increase exploitation costs. Further more, expected consequence of more intense engagement of people/equipment is increase of possible interference of their work in usually dynamic zone, which can have increased possibility of errors, damages of goods and/or equipment as consequence, and by that directly decreased service level, or quality of demand services which is followed by increase of related costs. Respecting mentioned influence on partial costs, function of total cost depending on number of items in warehouse (for given throughput) can be shown by diagram (dashed line) (Figure 3) In (V3) concept of warehouse design, where OPA is physically separated from RA (see Figure 1), following effects are present: (i) RA utilization level could be much better because it is not connected to OPA working technology; (ii) concentrating equipment (or using specialized equipment), personnel and tasks in separated OPA, provides better conditions for optimizing OPT and higher flexibility regarding increasing number or items and increase of service level; (iii) disadvantage of this concept is in additional costs due to forming physically separated technological subsystem (OPA) (greater investment in additional space and/or equipment) and costs for realization additional material flow realisation between RA and OPA. Having those in mind, costs of these concept (for given throughput Pi) can be shown by diagram (dotted line in Figure 3). Costs (V2) Pi (V3) Pi BP Pi,a assortment Figure 3: Cost dependency for (V2) and (V3) on the assortment (for defined throughput Pi) For any concrete problem, to given warehouse throughput, there is value of variable (assortment) which represents break point till which it is more rational to implement (V2), and with further increase of assortment more rational is (V3). It is obvious that very complex group of values makes impact to certain value costs: unit costs of working force, price of building/renting object/space, equipment engagement (buying, renting, leasing etc), energy costs and many others (tax policy, financing/credit terms...). That is the reason why each concrete warehouse project, for conditions in which his realization is presented, is separate 8

9 problem, demands detail cost calculations for presented alternatives, and complete knowledge of impact of used technology of warehouse design to values for these calculations involved. 5 CONCLUSION Decision about OPS, according its importance, is very significant problem of warehouse design. In early design phase decision about OPS concept (space, technological and organizational factors) is necessary to be well done. Due to impact of great number of factors and potential development possibilities of this system, realization of such task requires appropriate methodology approach. Literature treats some segments of this problem, which can't fully serve to designer in conceptual designing phase, and that is in particular related to deciding type of OPA. From these reasons, paper presents way for overcoming these problems. The approach is based on connecting OPT characteristics with alternative OPA solutions. In that aim is given overview of relevant data which are used to obtain OPT characteristics and potentially usable OPS concepts. This paper propose the approach which starting from real OPS tasks (for given throughput expressed in unit load per time unit) enables to designer in conceptual phase to make decision of alternative OPA concept selection, respecting costs changes as function of assortment size, as variable. Obvious, in concrete case, the analysis of these dependencies can include other combination of parameters or their wider range, depending on task complexity, which is the direction of further researches in this area. REFERENCES 1. T. N. Lambert, J. R. Stock, and L. M. Ellram, Fundamentals of logistics management, McGraw- Hill, Singapore, 1998, pp J. van der Berg, et al, Models for warehouse management: Classification and examples, International Journal of Production Economics, 59, 1999, pp T. Gudehus, H. Kotzab, Comprehensive Logistics, Springer-Verlag, Berlin Heidelberg, 2009, pp T. Gudehus Lagern und Kommissionieren, Fordern und Heben, 24. Nr.15,1974,. pp C. S. Yoon, G.P. Sharp, A structured procedure for analysis and design of order pick systems, IIE Transactions, 28,1996, pp S. Suzuki, Order pattern graph assists order picking systems design, Proceedings of the 9th International Conference on Automation in Warehousing, IFS Publications, San Francisco, California, October 13-15, 1988, pp L. F. McGinnis, S. Mulaik, Your data and how analyze it, In Proceedings of the 2000 Industrial Engineering Solutions Conference, Cleveland, OH, M. Hassan, A framework for the design of warehouse layout. Facilities, 20, 13/14, 2002, pp J. White, Modern Material Handling, September, 1979, pp F. Dallari, G. Marchet, M. Melcini, Design of order picking systems, International Journal of Advanced Manufacturing Technology, 42, 2009, pp P. J. Parikh, R. D. Meller, "Selecting Between Batch and Zone Order Picking Strategies in a Distribution Center", Transportation Research Part E: Logistics and Transportation Review, 44E(5), 2008, pp

10 12. E. H. Frazelle, World-Class Warehousing and Material Handling, McGraw/Hill, New York, 2002, pp T. Gudehus, Grundlagen der Kommissionertechnik, Verlag W. Girardet, Essen, Germany, (1973). 14. M. B. M. De Koster, T. Le-Duc, KJ. Roodbergen, "Design and Control of Warehouse Order Picking: A Literature Review" European Journal of Operational Research, 182, 2007, pp D. Đurđević, M. Miljuš, Tendencies of order picking development and influence on warehouse design, The International Journal of TRANSPORT & LOGISTICS 13/07, 2007, pp