New Tool for Aiding Warehouse Design Process

New Tool for Aiding Warehouse Design Process Chackelson C 1, Errasti A, Santos J Abstract Warehouse design is a highly complex task, due to both the large number of alternative designs and the strong interaction between all the factors involved. Although some design methodologies and tools have been proposed, the process leading to the identification of the specific design solutions is not clear in literature. This paper addressed the steps followed for developing, improving and validating a new tool that contributes to bridging that gap by supporting visualization and selection of design alternatives. Delphi method has been used, and experts suggestions and comments have been taken into account in order to guarantee the practical applicability of the proposed tool. Also, high-performance design solutions have been gathered to be used as a guideline during design process. Keywords: Warehouse Design, Configuration Tool, Delphi Method 1 Introduction Warehouses play a key role aiding to supply chain effectiveness by supporting the firm s customer service policies, meeting changing market conditions, reducing total logistics cost, and providing customers with a mix of products (Lambert et al. 1998,Baker and Canessa. 2009). Nowadays, warehouse design has become important and complex due to the increasing number items managed in the warehouse, the reduction in delivery times (e.g. 24-48 hours), the increasing of customization in orders, and the reduction in order size (Rushton et al. 2010,Errasti et al. 2010). In addition, due to the high number of existing possibilities and strong interactions between variables it is very difficult, and perhaps not even possible, to identify the optimum solution (Baker and Canessa. 2009). Although the elements and alternatives that need to be taken into account have been 1 Claudia Chackelson Lurner ( e-mail: cchackelson@tecnun.es) Tecnun, Engineering School at University of Navarra, Paseo Manuel Lardizábal, 13, 20018 San Sebastián, Spain * This work has been partially funded by Ministerio de Ciencia e Innovación (DPI2011-26653). 526

addressed (Goetschalckx and Ashayeri. 1989,De Koster et al. 2007), the process leading to the identification of a specific design solution is not clear (Dallari et al. 2009). So far, there is no consensus on the exact nature of the tools and techniques that need to be used in each design step (Gu et al. 2010), and the final design decisions are made based on intuition, experience and judgment. Thus, the most complex task when designing warehouses is to select one of the thousands of feasible design solutions. In consequence, a systematic procedure to narrow design alternatives is needed in order to guide the design process. Taking this statement into account, this work proposes a graphic tool for aiding warehouse design process, helping managers to visualize, select and evaluate different alternatives. The paper is structured as follows. Section 2 exposes a state of the art where main design decisions and complexity considerations are exposed. Section 3 presents a graphic tool that restructured all these alternatives in a novel way, and Section 4 describes a Delphi study carried out to improve and validate this new tool. Finally, Section 5 presents practical applicability of presented tool, and Section 6 includes principal conclusions and future research. 2 State of the Art According to Rouwenhorst et al., two main problems have been identified when designing a warehouse: dealing with the selection of systems and, and dealing with the design of the process flow and the selection of warehouse systems (Rouwenhorst et al. 2000). These decisions include: Prepare possible layouts (warehouse zones). Define storage systems. Level of automation. Storage. Define material handling. Determine operating procedures and methods. Receiving. Put-away. Storage. Order picking. Shipping. Receiving involves accepting material, unloading, verifying quantity and condition of the material and documenting this information as required. Put away means removing the goods from the receiving dock, transporting them to a storage area, locating in a specific place and identifying where the material has been placed. Storage is the retention of products for future use or shipment. Order Picking means extracting products from storage in response to a specific customer or- 527

der, moving them to a packing area where the goods are placed into an appropriate container, label with customer shipping requirements and moved the material to a shipping area. Shipping involves checking quantity and condition of the material and documents and loading (De Koster et al. 2007). The flow of items through the warehouse is normally divided in these five processes (Rouwenhorst et al. 2000). According to Rouwenhorst et al., literature provides useful tools for some steps, but it tends to concentrate on a small numbers of specific areas within the total warehouse design problem (Rouwenhorst et al. 2000). In real warehouses, designers use a variety of tools during the design process. Baker and Canessa gathered the most commonly used, highlighting the following ones (Baker and Canessa. 2009): Database and spreadsheet models for data analysis CAD for preparing possible designs and zoning Spreadsheet models for considering types Simulation software and formal spreadsheet models for selecting operations In order to reveal warehouse design opportunities, Frazelle detailed that the Warehouse Activity Profiling (Frazelle. 2002) needs to be measure. It allows knowing the complexity of undertaking the warehouse processes by considering the following profile components: Storage unit vs. receiving and shipping units. Zoning criteria (family, client, value, temperature, chemical, activity). Lines per order. Volume per order. Storage unit inventory. Storage unit. 3 Development Phase The design alternatives related to preparing possible layouts, considering possible types and characteristics, and determining operating procedures and methods have been restructured in a star-shaped tool. This format has been selected because it allows the simultaneous visualization of several design alternatives, as well as the comparison of different design configurations. The developed tool was based on the Order Picking Complexity Diagram created by Goetschalckx and Ashayeri (Goetschalckx and Ashayeri. 1989), in order to show the most important aspect that need to be designed. Goetschalckx and Ashayeri diagram has been extended for the five warehouse processes (receiving, put-away, storage, order picking, and shipping), including also new operational/technological options implemented by companies nowadays. The first version of this tool, named Warehouse Design Alternatives Diagram, has been developed 528

based on literature review. However, as this tool aims to be helpful during real design processes, improvement and validation with practitioners was needed. In order to adjust the page limit, this document only includes Warehouse Design Alternatives Diagram final version (see Fig 1). 4 Improvement and Validation Phase With the aim of improving and validating the new tool, Delphi method was selected. It is an iterative process used to collect the judgments of experts using a series of questionnaires interspersed with feedback (Skulmoski et al. 2007). A group of ten experts was selected, taking into account the four requirements for expertise exposed by Adler and Ziglio: knowledge and experience with the issues under investigation; capacity and willingness to participate; sufficient time to participate; and effective communication skills (Adler and Ziglio. 1996). A two-roundquestionnaire was needed in order to reach consensus. Questionnaires were principally oriented to verify the tool applicability and adequacy, order and clarity of the concepts included, as well as to include missing alternatives. The result of this process has been a new version of Warehouse Design Alternatives Diagram (see Figure 1), which includes design alternatives related to preparing possible layouts, considering possible types and characteristics, and determining operating procedures and methods for the warehouse processes (receiving, put-away, storage, order picking, and shipping). Design alternatives are presented in a star-shaped Diagram and clustered into the following classes: System characteristics and technology alternatives: Order data exchange, Physic reception/shipping, Logic reception/shipping, Loading pattern, Search and verify location. Organizational and operating policies: Origin and type of product, Track load type, Stock control, Storage strategy, Zoning, SKUs (Stock Keeping Units), Worker zone assignment, Order release mode, Routing, Batching and sorting. Shared decisions Reception Shipping: Stock holding, Docks and zones scheduling, Outsourcing. Shared decisions Put-away Storage Picking: Automation Level, Handling, Outsourcing. At least two s were included for each of these alternatives, organizing them from less sophisticated alternatives in the stars center to most sophisticated ones in the outside. Although the design alternatives are shown separately for each warehouse activity, share decisions and combined solutions are color-coded. Fig. 1 shows the final version of Warehouse Design Alternatives Diagram, including an explanation for the code of colors used to identify shared decisions for two or 529

Docks and zones scheduling Commands Book of Proceedings of the 7 th International Conference on Industrial Engineering and more warehouse processes, and to distinguish system characteristics and technology alternatives from organizational and operating policies. Reception Put-away Stock-holding Logic reception/ Reading CROSS-DOCKING by order (NO STOCK AND NO MANIPULATION) Artificial vision CROSS-DOCKING by article (NO STOCK BUT WITH MANIPULATION) Product Package Internal Origin and type (Packing list) External CLIENT (reverse of product STORAGE SUPPLIER logistic) (direct logistic) Outsourcing INTERNAL EXTERNAL (Packing list) Own handling Artificial vision Rented handling INFORMATIC RECEPTION INDEPENDENT (electronic EDI) PRE-RECEPTION Physic Order data reception exchange COMBINED DOCK AND ZONES Stock Balanced docks and zones control Balanced and workers Automation Level Routing OPTIMAL PARTS TO PICKER AS/RS S-shape SKUs Miniload Return VLM Mid-point REPACKAGING NEEDED Carrousel Largest-gap Worker zone Shuttles Combined SAME SKU FOR assignment PICKER TO PARTS HEURISTICS RECEPTION AND Conventional STORAGE Narrow aisle Push-back Dynamic Storage ONE ZONE Pallet truck One worker Hand truck Reach trucks Outsourcing Various Pallet jack Counterbalanced lift trucks Waking stacker Order picker INTERNAL WALKING VEHICLES EXTERNAL Compact shuttle Automation Level AGVs RIDING VEHICLES Conveyors Own handling DIRECT Cranes AUTOMATED VEHICLES Full Rented handling NO ½ SKUs TECHNOLOGY DISCRETE PARTS TO PICKER ¼ AIDED Handling PALLET DIRECTED AS/RS Search and TECHNOLOGY AIDED Miniload Put-to-light CONTINUOUS VLM CONTAINER verify location Carrousel RFID PUT-AWAY Shuttles BOX INDEPENDENT KIT (single command) Put-away PICKER TO PARTS Order release principles Conventional UNIT Families mode Narrow aisle Turnovers JOINT PUT-AWAY AND Push-back Safety PICKING (dual or Dynamic UNIQUE ZONE FORWARD Clients multiple command) PICK AREA CLASS-BASED DEDICATED PICKING Continuous CLOSEST OPEN LOCATION Zoning INDEPENDENT Periodic RANDOM (single command) Automation Level FAMILY GROUPING FEFO, LIFO, FIFO criterion Outsourcing Loading Pattern Logic shipping / Reading Artificial vision INTERNAL EXTERNAL Own handling Rented handling WITH ADVANCE SOFTWARE (loading sequence and unloading time) (Packing list) NO SOFTWARE WITH BASIC SOFTWARE (volume and loading pattern ) Physic shipping SHIPPING INDEPENDENT CROSS-DOCKING by article (NO STOCK BUT WITH MANIPULATION) STORAGE CROSS-DOCKING by order (NO STOCK AND NO MANIPULATION) Mono-destination Multi-destination LESS-THAN- CONTAINER LOAD FULL TRACK (Packing list) Artificial vision INFORMATIC (electronic EDI) PRE-RECEPTION Stock-holding Track load type Order data exchange Storage strategy CLASS-BASED Clients COI volume Turnovers Diagonal Semicircle Within-aisle Across-aisle Organizational and Operating Policies System Characteristics and Technology Level Shared Decisions Put-away Storage - Picking Shared Decisions Reception - Shipping Worker zone assignment Outsourcing Search and verify location TECHNOLOGY AIDED Pick-to-light Pick-to-voice Batching and sorting PARTS TO PICKER AS/RS Miniload VLM Carrousel Shuttles PICKER TO PARTS Conventional Narrow aisle Push-back ONE ZONE Dynamic One worker Various Pick-and-pass Pick-and-sort Sort-while-pick Navigation picking system Shipping Order Picking INTERNAL Own handling Rented handling EXTERNAL NO TECHNOLOGY AIDED BY ZONE BY ARTICLE BY ORDER S-shape Return Mid-point Largest-gap Combined HEURISTICS DISCRETE CONTINUOUS Order release mode OPTIMAL Routing SAME SKU FOR STORAGE AND SHIPPING UNIQUE STORAGE AND PICKING ZONE Hand truck Pallet jack Waking stacker WALKING VEHICLES Pallet truck Reach trucks Counterbalanced lift trucks Order picker Compact shuttle RIDING VEHICLES AGVs Conveyors Cranes AUTOMATED VEHICLES Handling REPACKAGING NEEDED Discrete replenishment Continuous replenishment Picking zone without storage Picking zone with storage FORWARD PICK AREA SKUs Picking zoning Fig. 1 Warehouse Design Alternatives Diagram 530

In multi-zone warehouses, the graphic tool should be duplicated as many times as zones have been defined. This is because it could not be appropriate to integrate all the logistic flows or all the stored items into a unique storage system, nor to use the same handling. 5 Practical Applicability of Warehouse Design Alternatives Diagram So far, Warehouse Design Alternatives Diagram is useful to visualize design alternatives, and to identify sheared decisions that need to be made simultaneously for more than one warehouse process. It allows mapping AS IS systems for existing warehouses, helping to identify redesign opportunities. However, the main objective of this tool is to support warehouse design, so not only alternatives visualization is important, but also selection and evaluation (mapping TO BE systems). With this aim in mind, Warehouse Activity Profiling components suggested by Frazelle (Frazelle. 2002) have been used to classify warehouses according to a of complexity. Storage unit vs. receiving and shipping units (1) and Zoning criteria (2) are useful to identify the necessity of defining multiple zones. Then, each zone could be designed as an independent warehouse using Lines per order (3), Volume per order (4), Storage unit inventory (5), and Storage unit (6) to select possible types and characteristics, and operating procedures and methods. To do so, Lines per order (3), Volume per order (4), Storage unit inventory (5), and Storage unit (6) were classified in three s each: Table 1 Complexity classification based on Warehouse Activity Profiling components (Frazelle. 2002) Lines per day Volume per order line (items per line) Storage unit inventory Storage unit Less than 100 Less than 10 Less than 100 Units or small items 100-1000 10-50 100-1000 Cases More than 1000 More than 50 More than 1000 Pallets Taking this into account, 81 (3 4 ) possible s of complexity could be defined and used to classify design solutions. In this context, a group of design solutions that provides high-performance in terms of productivity and quality were collected and stratified measuring complexity, with the aim of using them as a guideline during design process. To do so, experts that participated in the completed Delphi panel ware asked to collaborate by providing design solutions that could be catalogued as best practices. This contribution helps to develop a record of highperformance design solutions, classified based on Warehouse Activity Profiling 531

components, and associated with the productivity and the quality of real processes that had implemented these solutions. To document design solutions provided by experts, Warehouse Design Alternatives Diagram has been used (Fig. 2 shows an example). Fig. 2 Example of high-performance design solutions provided by warehouse design experts, mapped using Warehouse Design Alternatives Diagram. 6 Conclusions and Future Work Warehouse design alternatives were restructured in star-shaped graphic tool denominated Warehouse Design Alternatives Diagram. This tool is useful for both characterizing the AS IS system and collecting high-performance design solutions in order to guide selection of TO BE system. Thus, it helps visualization of design alternatives, showing not only the decisions that need to be made for warehouse processes (receiving, put-away, storage, order picking, and shipping), but also including interactions among different factors involved. Delphi method has been selected to improve and validate the first version of Warehouse Design Alternatives Diagram, guaranteeing its practical applicability. A collection of best practices classified according to complexity has been identified as an interesting contribution to warehouse design procedures, as it 532

could be useful as a guideline for warehouse designers. In this context, Warehouse Design Alternatives Diagram has been use to map these design solutions. However, the major complexity when collecting these high-performance design solutions is that there are 81 different complexity s and thousands of design solutions (combination of all design alternatives). In this context, the time needed to collect all this information is extremely long. This is the reason why, initially, only a few design solutions have been gathered. Future work will look for adding new design solutions for not addressed complexity s, new technological advances, and more productive operating procedures and methods. The mail objective will be to gather best practices in order to guide practitioners, no matter which of complexity presents the warehouse they plan to (re)design. Although Warehouse Design Alternatives Diagram does not provide an automated solution whereby the optimum combination of and operations is produced according to the requirements and characteristics of processes, it is a valuable tool because it enriches the experience of a single practitioner with the experience of warehouse design experts. 7 References Adler, M., & Ziglio, E. (1996). Gazing into the oracle: the Delphi method and its application to social policy and public health. Jessica Kingsley Pub: London. Baker, P., & Canessa, M. (2009). Warehouse design: A structured approach. European Journal of Operational Research, 193, 425-436. Dallari, F., Marchet, G., & Melacini, M. (2009). Design of order picking system. The International Journal of Advanced Manufacturing Technology, 42, 1-12. De Koster, R., Le-Duc, T., & Roodbergen, K. (2007). Design and control of warehouse order picking: A literature review. European Journal of Operational Research, 182, 481-501. Errasti, A., Chackelson, C., & Arcelus, M. (2010). Estado del arte y retos para la mejora de sistemas de preparación en almacenes-estudio Delphi. Dirección y Organización, 78-85. Frazelle, E. (2002). World-class warehousing and material handling. McGraw-Hill Professional. Goetschalckx, M., & Ashayeri, J. (1989). Classification and design of order picking. Logistics Information Management, 2, 99-106. Gu, J., Goetschalckx, M., & McGinnis, L. F. (2010). Research on warehouse design and performance evaluation: A comprehensive review. European Journal of Operational Research, 203, 539-549. Lambert, D. M., Stock, J. R., & Ellram, L. M. (1998). Fundamentals of logistics management. Irwin/McGraw-Hill Chicago, IL. Rouwenhorst, B., Reuter, B., Stockrahm, V., Van-Houtum, G. J., & Mantel, R. J. (2000). Warehouse design and control: Framework and literature review. European Journal of Operational Research, 122, 515-533. Rushton, A., Croucher, P., & Baker, P. (2010). The handbook of logistics & distribution management. (4th ed.). Kogan Page. Skulmoski, G. J., Hartman, F. T., & Krahn, J. (2007). The Delphi method for graduate research. Journal of information technology education, 6, 1. 533