Travel Time in a Warehouse: Process. Improvement at The Toro Company. John Cinealis

Transcription

1 1 Travel Time in a Warehouse: Process Improvement at The Toro Company by John Cinealis A Research Paper Submitted in Partial Fulfillment of the Requirements for the Master of Science Degree In Technology Management Approved: 3 Semester Credits,~:lidv~~ Dr. Thomas Lacksonen The Graduate School University of Wisconsin-Stout December, 2010

2 2 The Graduate School University of Wisconsin-Stout Menomonie, WI Author: Cinealis, John C. Title: Travel Time in a Warehouse: Process Improvement at The Toro Company Graduate Degree: MS Technology Management Research Adviser: Thomas Lacksonen, Ph.D. Month/Year: November, 2010 Number of Pages: 33 Style Manual Used: American Psychological Association, 6 th edition Abstract Order filing is estimated to account for 60% of total warehouse operating expenses. This cost can be reduced by reducing the amount of travel time. The Toro Company distribution center in Plymouth Wisconsin is no exception to this expense. This project focuses on blades and bedknives, and the time that it takes to stock, replenish, and order pick them. Blades and bedknives are class A parts when using ABC analysis at The Toro Company. The objective of the study was to reduce the travel time on blades and bedknives. The current process was calculated to obtain a time in seconds of the above three processes related to order filling. The testing resulted in the creation of a new forward picking and surplus area with 30 new primary locations and 150 new surplus locations. The results of this project could be adapted at

3 3 other distribution centers. Space was a constraint in this project; but a larger scale offering could be applied to an entire warehouse. This project contributed to the long term success of the distribution center for The Toro Company.

4 4 Table of Contents... Page Abstract... 2 List of Tables... 6 Chapter I: Introduction... 7 Goals of the Study Statement of the Problem Chapter II: Literature Review Past Reviews Picking and/or Layout Considerations Storage Considerations Case and Pallet Picking Fixed or Random Location Storage Dedicated Storage Forward Picking Order Picking Batching Routing and Sequencing Sorting Chapter III: Methodology Data Required Assumptions Methods... 20

5 5 Chapter IV: Results Reducing Travel Times Financial Chapter V: Conclusions and Recommendations Limitations Recommendations References... 31

6 6 List of Tables... Page Table 1: Current Process Fiscal Year Table 2: New Forward Picking Area Table 3: Financial Result Comparison... 27

7 7 Chapter I: Introduction Distribution Centers all over the world are looking for ways to save money and increase productivity. With the many operations that go on in a day; one seems to separate itself as a large cost. It is estimated that order picking or order filling accounts for more than 60% of warehouse operating expenses (Collins, 2008). One way to reduce this cost is to reduce travel time. The less movement and time spent traveling from one location to the next, the more productive an employee becomes. Since 1914, The Toro Company has transformed the way professionals and homeowners care for their outdoor environments. Through the decades, The Toro Company has become a global leader in turf maintenance equipment and precision irrigation systems, serving customers from golf course superintendents, grounds and sports field managers to landscape and irrigation contractors, agricultural growers, and homeowners (About Us, 2010). Plymouth, Wisconsin is home to the only distribution center in North America of The Toro Company. Inside the building are more than 90,000 stock keeping units spread out over 10 acres. In the fiscal year 2009, the Plymouth warehouse shipped 2.5 million lines to customers and had just fewer than 100,000 inbound receipts. With that kind of volume, little changes can lead to big savings. For this project, efforts were concentrated on blades and bedknives and the three warehouse operations that are associated with them. The first process is receiving and stocking. The second process is the replenishment of the primary bins from a surplus location and the third process is the order filling function. Since there are many different types of terminology for storage locations, clarification on what primary and surplus bins

8 8 mean at the Toro Company may be needed at this time. The primary bin is a floor or lower shelf location where the order filler goes to pick the order. The warehouse management system releases all orders to be picked from the primary locations when stock exists. The surplus locations are non-dedicated locations that have the surplus from what does not currently fit into the primary bin. All replenishment orders are directed to the surplus locations to fill the primary bins. The order filler would not pick out of a surplus location. The entire process starts on the receiving docks. Once a receipt has been done, it is the job of the stocker to put these parts away. The primary bins for the blades and bedknives are spread out in the warehouse and all of the surplus locations for these parts are located at the other end of the building. When a receipt is done for these items, the stocker will pick up these parts from the dock and drive to the primary bin and fill it as much as possible. Any remaining stock or possibly the entire skid will then be driven all the way to the back of the building for surplus storage. The stocker then drives back to the dock and starts the process all over again. The original thought process many years ago had a few theories that led to this decision. The first theory was that it would be easier to locate lost blades and bedknives that were located together if the stocker missed a receipt or a scan. The second theory was that it was safer to have all of these items in one area because there was not much forklift or foot travel in case of an accident. Neither one of these theories make much sense today. The first theory is reactive, where the storing of the blades and bedknives in the far back of the warehouse is an excuse to make them easier to find if a mistake is made. The second theory is based on supervision not trusting the load limitations on the racking

9 9 and just feeling better with the blades and bedknives out of the way. There has never been an issue or an accident in the 18 years Toro has been in this building involving these two items in any of our locations. The second process is the replenishment of the primary bins. When the primary bin gets to a predetermined stock level, SAP will issue a replenishment order to fill the bin back to the desired quantity. When the replenishment driver receives the order, the order sends them to the far end of the building to pick up the replenishment quantity from the surplus location. The driver then has to drive to the primary bin, fill it appropriately, and then return the remaining stock left on the skid back to the far end of the building to complete the transaction. The third process is the order filling process. Toro has two different types of orders, but the basic process for filling them is very similar. The two types are stock orders and direct ship orders. Stock orders are large orders that our distributors place weekly to replenish their stock, and a direct ship order would be a dealer or repair shop that is ordering the parts for a current job. The stock orders ship weekly and the direct ship orders go out daily via United Parcel Service. Blades and bedknives have some weight and volume to them and because of that they are packed on the bottom of the boxes. This makes the boxes easier to pack and prevents damage to other parts. The current process has the order filler walking to the primary locations that contain the blades and bedknives first. As mentioned before, these primary locations are spread out in the building making it time consuming when starting orders that contain blades and bedknives. Once the order filler has the blades and bedknives on the bottom of the box, they then proceed to complete the order. Our SAP system batches the orders by

10 10 location, so you should be able to walk up one aisle and then down the next in sequential order. The obvious problem here is that the blades and bedknives are currently not close to one another and the order filler is wasting time searching for these picks before they even start to complete the remaining portion of the order. Goals of the Study The goals of the project are to reduce travel time, increase productivity, and reduce labor costs. Productivity will be measured by time. The current travel time minus the new projected time for each process will be converted into labor hours, which will then be converted into in a dollar amount showing the annual savings. Statement of the Problem There is excess travel time storing and retrieving blades and bedknives.

11 11 Chapter II: Literature Review A literature review was completed focusing on three topics in the field of warehousing. The three topics include past warehouse design, storage considerations, and order picking methods. The one clear result from the literature review was that there is no approach that is conclusive for all warehouses. Every warehouse is designed differently and has different strategies. Past Reviews As important as warehouses are, a number of reviews of the literature have concluded that relatively little has been written in academic journals on the systematic approach that should be taken by warehouse designers (Baker & Canessa, 2007). A search of the literature shows that very few papers deal with the general warehouse design problem (Ashayeri & Gelders, 1985, p. 285); In general, however, there is not a procedure for systematically analysing the requirement and designing a warehouse to meet the operational need using the most economic technology (Rowley, 2000, p. 3); A sound theoretical basis for a warehouse design methodology still seems to be lacking (Rouwenhorst, Reuter, Strockrahm, van Houtman, Mantel, & Zijm 2000, p. 515); A comprehensive and science-based methodology for the overall design of warehousing systems does not appear to exist (Goetschalckx, McGinnis, Bodner, Govindaraj, Sharp, & Huang 2002, p. 1).

12 12 Picking and/or Layout Considerations In a paper written by Roodbergen and Vis (2006), they evaluated the relationship between the layout of the order picking area and the average length of a picking route for areas consisting of one block. They used analytical formulas to calculate the average route length for two different routing policies. The results obtained using these formulas depend on the number of aisles, the aisle length, the depot location, the number of picks per route and some physical parameters of the racks. The conclusion they arrived at is similar to others in that the optimal layout is sensitive to the routing policy used in the optimization. Roodbergen and Vis (2006) were able to prove efficiency losses of up to 18% when optimizing the layout for a routing policy other than the one used for the actual operation. Generally speaking, the warehouse layout is based on a rectangular shape. Roodbergen and dekoster (2001) put cross aisles between the originally parallel aisles, and compare the result with that without cross aisles. They found a significant reduction of average picking distance between the two cases. Ratliff and Rosenthal (1983) study the picking problem in a rectangular warehouse, where there are only pathways at the two ends of an aisle. Caron, Marchet, and Perego (1998) find that the warehouse layout has a significant effect on picking travel distance. They prove that the layout design has an effect of more than 60% on the total travel distance, and also find the relationship between warehouse layout and picking travel distance. Vaughan and Petersen (1999) develop a heuristic algorithm to obtain an optimum quantity on cross aisles in order to generate an optimal performance, whereas Roodbergen and de Koster (2001) compare the average travel time between normal layout and a cross aisle layout and prove that the warehouse with cross aisles

13 13 will have a shorter average travel time. The plan is to use a single cross aisle in or about the center of the new forward picking area. Both of the aisle ends will be open to allow travel between the aisles. Storage Considerations Storage is concerned with the organization of goods held in the warehouse in order to achieve high space utilization and facilitate efficient material handling (Gu, Goetschalckx, & McGinnis, 2007). Goods in storage can be organized into different departments. The drivers of department organization may be physical characteristics of the goods. The four storage plans being researched are pallet storage vs. case storage, fixed versus random, dedicated storage for a specific customer, and a forward picking area for fast picking. Case and Pallet Picking Case picking operations tend to have less diversity in product characteristics than piece picking operations, with fewer SKUs and higher picks per SKU (Piasecki, 2001). Rather than product stored on static shelving, case-pick operations will have the product stored in pallet racks or in bulk in floor locations. The simplest picking method is to use a pallet jack and pick cases out of bulk floor locations, however many operations will find that going to very narrow aisle pallet racking and using man-up order selectors or turret trucks will provide high storage density and high pick rates. Full-pallet picking is also known as unit-load picking (Piasecki, 2001). The systematic methods for full-pallet picking are much simpler that either piece pick or case pick, however, the choices in storage equipment, storage configurations, and types of lift trucks used are many. Orders are picked one at a time. The order picker will use

14 14 some type of lift truck, retrieve the pallet load and stage it in a shipping area in a staging lane designated for that order, or just pick and load directly into an outbound trailer or container. Fixed or Random Location Storage When storing product in a warehouse, two of the most common methods are fixed location storage and random storage. Fixed storage locations are where a permanent location is assigned for each part in the warehouse (Blackstone, pp. 51). Although more space is needed to store parts than in a random location storage system, fixed locations become more familiar to the employees. Random location storage areas involve a technique where parts are placed in any storage location that is empty when they arrive (Blackstone, pp. 114). Although this method will require some type of a locator file to identify part locations, it often requires less storage space than the fixed location storage method. Using fixed locations is common in the picking area, but it isn t recommended in the reserve storage area in most industries. The fixed method results in empty locations or wasted storage space. However, the random storage method maximizes the use of empty locations and results in higher space utilization. Jarvis and McDowell (1991) focus on rectangular warehouses, which include cross aisle in the end position and assume every item has the same picking time. The picking time is proportional to the picking distance, so they use fixed storage method to calculate the expected picking time. Jeroen and Gademann (2000) explain that classified storage policy is based on customer requirement proportion, and give ways to classify storage location and product effectively. Classified storage is also commonly known as ABC analysis. Class A parts represent 80% of the value, but only 20% of the parts. Class B

15 15 parts represent 15% of the value, and 30% of the parts. Class C parts represent 5% of the total value, and 50% of the parts. ABC analysis is being currently used in the warehouse to classify parts and will continue for this project. Peterson and Schmenner (1999) investigate the heuristic picking path, and the storage assignment policy that is based on picking quantity. Dedicated Storage Dedicated storage is an area in a warehouse that contains product for a specific customer or a certain storage class. This can be primary bins, surplus bins, or a combination of both. The blades and bedknives in the new area will be class A parts. Very little was found on this topic in professional journals. Gu, Goetschalckx and McGinnis (2007) consider a dedicated storage strategy a design problem and discuss it as that. Rosenblatt and Eynan (1989) suggest that the assignment basis of classified storage methods is mainly on turn over rate. Their conclusions suggest that as the number of classified items increase, the travel time is expected to be reduced, and a better improvement is found when the number of classified items is kept below ten. The current number of classifications used in the warehouse today is eight. Forward Picking Forward picking areas are a type of dedicated storage, most commonly referred to as a warehouse inside of a warehouse. In this warehouse, you keep your most popular stock keeping units in smaller quantities so travel is reduced by having the order picker in one area. The trade-off is that the forward pick area must be replenished from a bulk storage or reserve area elsewhere in the warehouse (Bartholdi & Hackman, 2008). A typical forward pick area for small parts is an aisle or more of carton flow

16 16 racks through which runs a conveyor. The biggest question most companies have is how much space do I need for each stock keeping unit? Hackman and Rosenblatt (1990) were the first to describe a mathematical model to allocate space in a forward pick area. They used a fluid model that treats the volume of each SKU as continuously divisible and incompressible. The project is going to be a combination of a forward picking area with fixed surplus. The fixed surplus is a better fit for this project over random because of the replenishment and stocking processes. Without keeping these surplus locations fixed; the travel time for the two processes would not change. Order Picking There are many different order picking methods that can be used in a warehouse. Examples include, single-order picking, batching and sort-while-pick, batching and sorting after-pick, single order picking with zoning, and batching with zoning (Yoon and Sharp, 1996). Regardless of which method you use, all of them will consist of some or all of the following basic steps: batching, routing and sequencing, and sorting (Gu, et al. 2007). Batching The batching problem is part of the planning for ordering picking (Gu, et al. 2007). Orders are received and released for fulfillment based on either a time window or a picking wave. The time required to pick a batch should not exceed the time window or the pick wave duration. If zone picking is used, the batch should provide a balance between the zones to achieve high picker utilization and minimizing pick time. Every effort needs to be made to ensure that each zone arrives at the sort stations at

17 17 approximately the same time. A delay at this of the process creates a bottleneck as you cannot sort until all zones have arrived. Routing and Sequencing The routing and sequencing decision in order picking operations determines the best sequence and route of locations for picking and/or storing a given set of items (Gu, et al. 2007). The goal is to minimize the total material handling costs. It sounds pretty simple, but really is not. Problems arise when there are more than one location for a product, cross aisle locations, and restricted warehouse travel paths. The Toro Company warehouse has cross aisles after every forty-eight feet or racking and the routing will take the order filling in a path up on aisle and back down the other until the order is completed. Each warehouse will have to determine the most efficient routing and match their warehouse management system to it. Sorting Sorting is required when multiple orders are picked together (Gu, et al. 2007). It can be performed in one of two places; during the picking process or after the picking process. Sort-while-pick is exactly as it sounds where the order filler will sort the parts into totes or boxes when picked. Sort-after-pick is where there is a downstream sorting station where the picks are matched to the order. A sort-after-pick operation is pretty easy to identify as most of them will have some sort of a conveyor system leading to a sort station and probably some sort of exit conveyors. The warehouse for the Toro Company uses a sort-after-pick system and will continue to for this project. Orders are batched into twenty-four deliveries at one time and then are sent out to different zones to be transported to the sorting stations by

18 18 conveyor. Twenty-four deliveries take the order picker approximately one hour to pick. Each warehouse will have to determine which method or combination of methods to use based on their warehouse layout.

19 19 Chapter III: Methodology Excess travel time in a warehouse is not a unique problem to the Toro Company. Warehouses all over the world are looking for ways to reduce costs and increase productivity. With an estimated 60% of warehouse costs directly related to order filling; a huge opportunity for savings presents itself. Reducing the travel time will reduce those costs. The objectives of this project were to: 1. Reduce travel time by moving the product closer to the order pickers. 2. Increase productivity by having both dedicated primary and surplus locations in a forward picking area. 3. Reduce labor costs by being more productive and traveling fewer distances. Reducing the travel time was necessary to maintain the company s competitive advantage and remain profitable. This chapter presents the methods used to achieve the three objectives of this project. Data Required The first step of the project was to identify which blades and bedknives make sense to move to reach our goals for all three processes. The needed reports were obtained through the warehouse management system. The reports used were the previous thirty six months of history for trips to bins, inbound receipts, and replenishments. The three reports included the top one hundred marketing plan parts, the top one hundred stock order parts, and the top one hundred inbound receipts. Familiarity and experience in the warehouse gave high confidence that these reports would contain common blades and bedknives, which turned out to be accurate. Space was a major constraint for this project. A complete reorganization of the warehouse or a

20 20 layout change was not an option and is not in the scope of this project. Using the limited space available, 30 new primary locations and 150 new surplus locations were created. With the current process identified and measured; the new forward picking area needed to be created. To determine the current travel time, calculations were made using past history and standard work methods with distance traveled, to measure the time it took to stock, replenish. An estimate for the cost of the new racking was obtained. The last piece of data needed was a dollar amount to figure out labor savings. Twenty-five dollars per hour was used, which includes the hourly wage along with the benefit package. Assumptions Three assumptions were made for this project while collecting data. The first assumption is that the forklifts for the stocking and replenishment measurements are following the predetermined travel paths in the warehouse. The second assumption is that the forklifts travel at the same speed. The third assumptions are that the load and unload times for the processes will remain unchanged. Methods The data collected needed to be organized and a list of the top thirty blades and bedknives was determined from this data. The determination was made based on which blades and bedknives appeared in all three reports. With the list determined, the next step was to calculate the current travel time in seconds of the different processes and distance traveled. The calculation of time is based on past history and standard work methods. Distance traveled was measured using a walking wheel. The first measurement determined was the round trip travel time in seconds of stocking the

21 21 blades and bedknives. The measurement was taken from the center of the receiving dock to the center of the current storage area and then back to the center of the receiving dock. The next measurement taken was the replenishment time. For replenishments, the time measured was the distance between the average location of the 30 primaries and the average surplus locations of these parts. The final measurement that was taken was the order picking process. The time measurement for the order picking function was taken using the center of the pack stations to the center of the average primary locations of the 30 blades and bedknives. The second set of data needed was a time estimate in seconds from the same starting points to the new forward picking area. Past history and standard work methods were used for this calculation as well. The starting points were the same as before, but the ending locations were now the new racking that contained the blades and bedknives. An economic analysis was done comparing the current process with the new project. The recommendation is to go ahead with the project as soon as possible.

22 22 Chapter IV: Results The results of this project are mostly hypothetical, based on quantitative data that included distance measurement, time measurements, and some basic calculations to produce consistent data. The time measurement metric for order filling was the result of using past history and standard work measurements for employees based on an eight hour shift. It is known that an employee can travel 2.14 feet per second or feet per minute. This calculates into miles per hour. The stocking and replenishment time metrics are based on the known speed of 6 miles per hour for the forklift. The distance metric was taken using a distance measuring wheel. The expected result of the project related to each of the goals is discussed below. Reducing Travel Times The first objective of this project was to reduce travel times. A reduction in travel times was achieved by creating a new forward picking area for the top thirty blades and bedknives. The space available for this project measured thirty feet wide by seventy feet long. The racking was in eight foot sections by four feet in depth. Eight sections of racking were used, making a total of sixty four feet in length with a four foot depth. The first set of racking installed was put up against the wall. The second section of racking was two sections back to back, equaling a total depth of eight feet. Both of the above racking sections were sixty four feet in length each. Between the single and double sections was an eight foot aisle. On the other side of the double section was a ten foot main aisle, which already existed. The three warehouse operations relating to blades and bedknives had an immediate decrease in travel times. Those three operations are receiving and stocking,

23 23 replenishment, and the order filling process. Using the current process to stock blades and bedknives, a forklift driver had to travel an average distance of 2076 feet round trip. This average distance takes 235 seconds to complete. The new forward picking area reduced both of those measurements to an average distance traveled of 449 feet roundtrip for the stocking, and 51 seconds to complete. In the fiscal year of 2008, 1562 receipts were made of the thirty selected blades and bedknives. The second warehouse operation relating to the blades and bedknives is the replenishment process. The current process requires a forklift driver to travel an average distance of 1129 feet round trip. The total time to complete the process is 128 seconds. The new forward picking area reduced these numbers as well. The new process reduced the average forklift driver travel distance to 18 feet. The time was reduced to 2 seconds per replenishment. In the fiscal year of 2008, 1204 replenishments were made on the thirty selected blades and bedknives. The third and final warehouse operation is the order filling process. The current process has the order filler traveling an average of 353 feet for a total time of 165 seconds. This process also saw a reduction in travel times because of the new forward picking area. Average travel distance was reduced to 71 feet. The reduced time metric is 33 seconds. In the fiscal year of 2008, 20,991 trips to the primary bins were made of the thirty selected blades and bedknives. Financial The financial results were based on the current processes versus the new processes for the top thirty blades and bedknives. Total labor hours for the fiscal year 2008 from the current process were hours. The total number of eight hour shift

24 24 needed to perform the three warehouse operations was Using a labor cost of $25.00 per hour per employee; the total cost for the fiscal year 2008 for these thirty blades and bedknives was $27, The new forward picking area produced annual financial savings as well. The number of labor hours needed to perform the three warehouse operations was reduced to This translated into eight hour shifts. The total labor cost for the new forward picking area is estimated to be $5, A summary of the above information is provided below. Table 1 is the current process. Table 2 is the new forward picking area, and Table 3 is the financial savings comparing the two processes. There were two costs associated with the project; the racking and the labor hours. The cost for the racking was $12,090. The labor cost includes hours for the assembly of the racking and the relocating of the parts from the current locations to the new forward picking area. The total labor was 80 hours. Using the same rate of $25.00 per hour for labor, $ was the total labor cost. The total cost of the project added up to $14,090. In engineering economy terms, year zero has the cost and year one and beyond have the returns. In this case, the rate of return is calculated as annual savings divided by total cost. The rate of return is 158%. The results of the project show a significant reduction in travel time, travel distance, and labor costs. Productivity should increase due to a reduction in distance traveled. The goals of the project were to reduce travel time, increase productivity, and reduce labor costs.

25 25 Table 1 Current Process Fiscal Year 2008 Receiving Total time for stocking from dock in seconds 235 Number of receipts 1562 Hours of labor Replenishment Total travel time to replenish a bin (average) in seconds 128 Number of replenishments 1204 Hours of labor Trips to Bin Total travel time to pick a part (average) in seconds 165 Number of trips Hours of labor

26 26 Table 2 New Forward Picking Area Receiving Total time for stocking from dock in seconds 51 Number of receipts 1562 Hours of labor Replenishment Total travel time to replenish a bin (average) in seconds 2 Number of replenishments 1204 Hours of labor 0.67 Trips to Bin Total travel time to pick a part (average) in seconds 33 Number of trips Hours of labor

27 27 Table 3 Financial Result Comparison Current Process Total labor hours for these 30 parts Total 8 hour shifts needed Total labor cost $27,672 New Forward Picking Area Total labor hours for these 30 parts Total 8 hour shifts needed 26.9 Total labor cost $5,380 Total hours saved Total 8 hour shifts available for other work Total labor dollars saved annually $22,291

28 28 Chapter V: Conclusions and Recommendations The Toro Company distribution center in Plymouth Wisconsin needed a way to reduce costs and increase productivity to remain competitive. While this problem is not new to any facility in operation today, an opportunity presented itself with some unexpected space being made available inside the warehouse. The goals of the project were to reduce travel time, increase productivity, and reduce labor costs. All three of the project goals were met. The change in the location of the primary and secondary storage locations for the top thirty blades and bedknives reduced travel times. The results show an anticipated decrease in all three of the order filling processes. The stocking time, the replenishment time, and the pick time all were reduced. The second goal was to increase productivity. Table 3 from the previous page, shows an eighty percent reduction in labor hours needed to complete the same tasks using the processes compared to the previous one. The third goal that was achieved was the reduction of labor costs. Using Table 3 again, the results show an annual savings of $22,292. Limitations The space available for this project was a major limitation for this project. A complete reorganization of the warehouse or a layout change was not an option and is not in the scope of this project. Using the limited space available, 30 new primary locations and 150 new surplus locations were created. Another limitation was the data available to increase the scope of the project. The project could not measure multiple lines on a delivery. An example of this would be if a delivery had more than the blade or bedknive on it; the other part or parts were not able to be measured in the data. The

29 29 data only accounted for trips to bins and single line picks. For this project, the analysis for both the old and new processes was done using the single line picks making the results relevant. Recommendations All of the improvements and gains produced in the project could easily be applied to other warehouses. The Toro Company will continue to improve on the current project when more available space becomes available and by using a different set of data. In the area that was used, the project was limited due to space constraints. The current distribution center consists of ten acres and contains 90,000 stock keeping units. A report was run showing all of the past thirty six month history on all 90,000 stock keeping units. Of those 90,000 stock keeping units, 6,432 represented 75% of all of the warehouse picks for the fiscal year of A reorganization of the warehouse to arrange these 6,432 together could produce huge gains in productivity. The project did not take into account other parts that may be ordered with blades and bedknives. Different blades and bedknives will require certain screws that are unique to their replacement. A further step in the project may be to run some reports for common parts that are sold with these thirty blades and bedknives. It would not necessarily improve the stocking and replenishment processes; but it may benefit the order filling productivity. The project also did not account for the potential increase in sales of the thirty blades and bedknives. In other words, there is no excess capacity in the secondary locations available. If the 150 surplus locations were to be filled to capacity and another shipment was received; the blades and bedknives would be stocked in the far back

30 30 corner of the warehouse where the old process had them going. This would negate the gains in the stocking and replenishment processes. One solution to this would be to have more frequent deliveries creating a more lean approach. This discussion and recommendations could also be used by any organization that warehouses products. This project produced the blueprint for a small sample size of products which could be implemented into any size warehouse. The methods used in this project could be translated into new warehouse set ups and also fully functioning warehouses. The data used for a new warehouse would be the forecast as opposed to past data.

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