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“Warehouse efficiency at Topa verpakking”

Stouwdam, Gerben (2010) “Warehouse efficiency at Topa verpakking”.

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Abstract:Topa verpakking is a specialist in the field of packaging and shipping. The distribution center of Topa is 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 management of Topa if the right choices have been made. This research has focused on the main warehouse activities, receiving, storing, picking and shipping. Objective of this research was to expose the current 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 to improve the efficiency in the distribution center of Topa verpakking? “. The word efficiency is defined as 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 and analyzing data from the ERP system. Bottleneck 1: The receiving process The sequences of the activities of the receiving process and the responsibility of two departments causes a lot of waiting time. Waiting time can be classified as waste in a process, a non value adding activity. The main problem is that stickers with the locations number on it are printed in a late phase of the process. This causes a delay in the whole process, a pallet can be stored in the locations only when 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 truck loading. Time is measured from the arrival of a supplier until the pallet is stored in the location. The current 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 early phase of the process and attached when possible. The storing of the pallets determines the rhythm and speed of the total process. The real life simulation of the desired situation has shown to be very effective. The total throughput time decreases to 88 minutes per truck load. KPI Current situation New situation Improvement Average total throughput time in the receiving process 138 minutes per truck 88 minutes per truck 50 minutes per truck 36.24 % Bottleneck 2: The forward-reserve problem Topa has divided the warehouse in two different areas, the reserve area and the fast pick area. The fast pick area is used to speed up the order picking process for popular and small products. The reserve area is used for the bulk storage, picking big order quantities and less popular products. The allocation of SKUs (Stock Keeping Unit) to the fast pick area is done by plain thinking. An update of this allocation has never been done since the implementation. SKUs that have become popular are still picked from the reserve area and SKUs that have become less popular are still picked from the fast pick area. This problem results in labor intensive work in the reserve area and no advantage of savings 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 model of Bartholdi & Hackman, 2010 described in their book “Warehouse & Distribution Science” is applicable for the case of Topa. It describes a heuristic and model to determine which SKU contributes 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 of 66 minutes per day for a reach truck driver and an improvement of 133.9 picking hours per year of picking SKUs rather from the fast pick area. KPI Current situation New situation Improvement Each picking time by reach truck drivers 232 minutes per day 166 minutes per day 66 minutes per day 28.45 % Net benefit 1059.7 hours per year 1193.6 hours per year 133.9 hours per year 12.63 % Bottleneck 3: The storage strategy in the reserve area Topa has chosen in the past to implement a class based storage strategy. Products are categorized in classed regarding their popularity. The change of popularity resulted that SKUs are allocated in the wrong zones. The class based strategy has not been updated since the implementation. The management of Topa implemented the storage strategy without any thorough calculations and awareness 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. Studies have shown that an ABC classification regarding the 66.6-10 rule is the best option for Topa. The 66.6-10 rule means that 66.6% of the picks are caused by 10% of the products, these SKUs are allocated to zone A. The SKUs that are responsible for 66.6%-90% are classified in zone B and the rest in 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 new layouts. KPI Current situation New situation Improvement Total travel time in reserve area 926.8 hours in 2009 742.8 hours in 2009 184 hours per year 19.9 % Bottleneck 4: The storage strategy in the fast pick area Dedicated storage strategy is used in the fast pick area in the current situation. SKUs are assigned to fixed 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 this area. 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 storage strategy is shown to be the most suitable storage strategy in the fast pick area in combination with an allocation of the SKUs based on activity (popularity plus the number of restocks) regarding the travel distance to a location. Applying this method results in a decreasing of the travel distance by 52.84% in 2009. The order pick time in the fast pick area will decrease from 2 minutes and 40 seconds to 1 minute and 40 seconds when a new order picking vehicle is purchased that can also pick from the first level. The capacity in the fast pick area increases due to the elimination of the safety stock. SKUs from the 2nd to 6th locations are therefore stored on a ground or first level location. KPI Current situation New situation Improvement Total travel distance in the fast pick area 2.803.776 meter in 2009 1.322.260 meter in 2009 1.481.516 meter per year 52.84 % Average travel time 2nd till 6th location in the fast pick area 9 minutes per location 1 minute and 40 seconds per location 7 minutes and 20 seconds per location 81.5 % Average travel time per ground and first level location in the fast pick area 2 minutes and 40 seconds 1 minute and 40 seconds 1 minute 47.5 % This research can conclude that the efficiency can be improved for the distribution center of Topa by implementing the recommendations that are given. An implementation plan is made to implement the recommendations and to maintain the efficiency.
Item Type:Essay (Master)
Clients:
Topa Thermal Packaging
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
Link to this item:http://purl.utwente.nl/essays/60724
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