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• W25778673 abstract "Topa verpakking is a specialist in the field of packaging and shipping. The distribution center of Topais established in Lelystad. The distribution center had some rough changes during the last years.These changes resulted in a new layout and new processes. The question arises by the managementof Topa if the right choices have been made. This research has focused on the main warehouseactivities, receiving, storing, picking and shipping. Objective of this research was to expose thecurrent bottlenecks and their performance and find solutions to improve the efficiency.The problem definition of this research is: “How can non value adding activities be reduced toimprove the efficiency in the distribution center of Topa verpakking? “. The word efficiency is definedas doing the thing right which is usually measured as the output per unit input.Four bottlenecks were exposed after observing the current situation, interviewing employees andanalyzing data from the ERP system.Bottleneck 1: The receiving processThe sequences of the activities of the receiving process and the responsibility of two departmentscauses a lot of waiting time. Waiting time can be classified as waste in a process, a non value addingactivity. The main problem is that stickers with the locations number on it are printed in a late phaseof the process. This causes a delay in the whole process, a pallet can be stored in the locations onlywhen the sticker is attached. The whole process is mapped with the tool Value Stream Map. The KPI(Key Performance Indicator) of this process is defined as the average total throughput time of a truckloading. Time is measured from the arrival of a supplier until the pallet is stored in the location. Thecurrent average total throughput time of the receiving process is 138 minutes for one truck loading.A real life simulation was done for testing a desired situation. The stickers are printed in an earlyphase of the process and attached when possible. The storing of the pallets determines the rhythmand speed of the total process. The real life simulation of the desired situation has shown to be veryeffective. The total throughput time decreases to 88 minutes per truck load.KPI Current situation New situation ImprovementAverage totalthroughput time inthe receivingprocess138 minutes pertruck88 minutes per truck 50 minutesper truck36.24 %Bottleneck 2: The forward-reserve problemTopa has divided the warehouse in two different areas, the reserve area and the fast pick area. Thefast pick area is used to speed up the order picking process for popular and small products. Thereserve area is used for the bulk storage, picking big order quantities and less popular products. Theallocation of SKUs (Stock Keeping Unit) to the fast pick area is done by plain thinking. An update ofthis allocation has never been done since the implementation. SKUs that have become popular arestill picked from the reserve area and SKUs that have become less popular are still picked from thefast pick area. This problem results in labor intensive work in the reserve area and no advantage ofsavings of picking SKUs in the fast pick area rather than in the reserve area.A literature study is done to find a suitable solution to allocate SKUs to the fast pick area. The modelof Bartholdi & Hackman, 2010 described in their book “Warehouse & Distribution Science” isapplicable for the case of Topa. It describes a heuristic and model to determine which SKUcontributes net benefit of being picked from the fast pick area rather than from the reserve area.The model of Bartholdi & Hackman is applied to the case of Topa. This resulted in an improvement of66 minutes per day for a reach truck driver and an improvement of 133.9 picking hours per year ofpicking SKUs rather from the fast pick area.KPI Current situation New situation ImprovementEach picking time byreach truck drivers232 minutes per day 166 minutes per day 66 minutes per day28.45 %Net benefit 1059.7 hours per year 1193.6 hours per year 133.9 hours per year12.63 %Bottleneck 3: The storage strategy in the reserve areaTopa has chosen in the past to implement a class based storage strategy. Products are categorized inclassed regarding their popularity. The change of popularity resulted that SKUs are allocated in thewrong zones. The class based strategy has not been updated since the implementation. Themanagement of Topa implemented the storage strategy without any thorough calculations andawareness of the travel distance and travel time for storing and picking the SKUs.A literature study is done to determine the most suitable storage strategy in the reserve area.Random storage and different rules for class based storage are applied to the case of Topa. Studieshave shown that an ABC classification regarding the 66.6-10 rule is the best option for Topa. The66.6-10 rule means that 66.6% of the picks are caused by 10% of the products, these SKUs areallocated to zone A. The SKUs that are responsible for 66.6%-90% are classified in zone B and the restin zone C.The new storage strategy improves the efficiency with a decrease of the total travel time by 19.9%.An implementation plan is made with Excel lists with the SKU classification and blue prints of the newlayouts.KPI Current situation New situation ImprovementTotal travel time inreserve area926.8 hours in 2009 742.8 hours in 2009 184 hours per year19.9 %Bottleneck 4: The storage strategy in the fast pick areaDedicated storage strategy is used in the fast pick area in the current situation. SKUs are assigned tofixed locations regarding their popularity. The popularity is determined regarding customer demand.The allocations of SKUs to fixed locations has never been updated since the implementation of thisarea. SKUs are also assigned to locations without awareness of travel distance.The current order picking equipment, storage space caused a lot of inefficiency in the fast pick area.A literature study was done to find a solution for the storage strategy in the fast pick area.Furthermore practical solutions have to be found to speed up the process. Dedicated storagestrategy is shown to be the most suitable storage strategy in the fast pick area in combination withan allocation of the SKUs based on activity (popularity plus the number of restocks) regarding thetravel distance to a location. Applying this method results in a decreasing of the travel distance by52.84% in 2009. The order pick time in the fast pick area will decrease from 2 minutes and 40seconds to 1 minute and 40 seconds when a new order picking vehicle is purchased that can also pickfrom the first level. The capacity in the fast pick area increases due to the elimination of the safetystock. SKUs from the 2nd to 6th locations are therefore stored on a ground or first level location.KPI Current situation New situation ImprovementTotal travel distancein the fast pick area2.803.776 meter in20091.322.260 meter in 2009 1.481.516 meter per year52.84 %Average travel time2nd till 6th location inthe fast pick area9 minutes per location 1 minute and 40seconds per location7 minutes and 20 secondsper location81.5 %Average travel timeper ground and firstlevel location in thefast pick area2 minutes and 40seconds1 minute and 40seconds1 minute47.5 %This research can conclude that the efficiency can be improved for the distribution center of Topa byimplementing the recommendations that are given. An implementation plan is made to implementthe recommendations and to maintain the efficiency." @default.
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• W25778673 date "2010-01-01" @default.
• W25778673 modified "2023-09-27" @default.
• W25778673 title "Warehouse efficiency at Topa verpakking" @default.
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