Browsing by Author "SAHLE MEKTA ZENEBE"

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    ORDER PICKING PERFORMANCE IMPROVEMENT IN FAST MOVING GOODS DISTRIBUTION WAREHOUSE
    (Hawassa University, 2022-10-06) SAHLE MEKTA ZENEBE
    Warehouses are the areas where goods are stocked in the supply chain. All material handling activities, such as receiving, storage, order picking, accumulation, sorting and consolidation, and shipment of goods, are addressed by warehousing. Order-picking is the most resource-intensive activity in warehousing and it defines the level of service provided to consumers. So, it must be flawless and quick. Shorter order picking travel distance is one of the key performance measures for order picking. The goal of this study was to improve order picking performance through minimization of order picking travel distance in the ALLE Bejimla Hawassa branch. The current assignment of each good was known through direct recording. Following that, consumers' movements were tracked to know how items were picked from their storage. Using measuring tape, the dimensions of each bay and aisle were known, and the data was utilized to calculate order picking travel distance. Based on the multiplicative value of order frequency and minimum ordering weight, items are classified as high value, medium value and low value. Fourteen items have higher value of ordering frequency times weight. For first-class items, order picking travel distance was calculated for a single order and multiplied by order frequency. The Hungarian method and item popularity heuristics were then used to determine the best bay assignment for each item. According to the existing assignment 995.4 meters walking is required to pick most popular items per single order scheme. This distance is minimized to 617.2 meters, 788.7 meters, 805.7 meters and 766 meters using assignment model approach, optimal storage strategy approach, equal time storage strategy and equal space storage strategy respectively. Using monthly flow of items, the fractional volume was calculated. The number of restocks was also calculated for various storage strategies, and the optimal allocation strategy led to fewer restocks