Storage Location Assignment: Using the Product Structure to Reduce Order Picking Times
01 Jan 1994-pp 147-159
TL;DR: In this article, a strategy for prestructuring components and information for the picking work in storehouses is described, and a storage location assignment strategy emanating from the product structure is proposed, and exemplified by using empirical data from a case study.
Abstract: The stock location assignment problem is concerned and a strategy for prestructuring components and information for the picking work in storehouses is described. This classification is derived from the product structures transformed to support a holistic perception aimed at the material handler/picker. The results imply a more efficient material handling through reorganizing the components in the storage system, in order to support the work from the picker's point of view. A storage location assignment strategy emanating from the product structure is proposed, and is exemplified by using empirical data from a case study. The result from this case study was a reduction in picking information of more than 75%, which in turn greatly reduced the amount of information to the picker.
Citations
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TL;DR: In this paper, a literature overview on typical decision problems in design and control of manual order-picking processes is given, focusing on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning.
1,603 citations
TL;DR: The purpose is to provide a bridge between academic researchers and warehouse practitioners, explaining what planning models and methods are currently available for warehouse operations, and what are the future research opportunities.
847 citations
TL;DR: The results of the study indicate that the key to effective implementation of a storage assignment system is to match the types of warehouse storage system and the variety of items in the customer order.
Abstract: Determining the proper storage locations for potentially thousands of products is one major task that faces the warehouse manager during the design of a new warehouse or the refurbishment of existing facility. There are many factors affects the storage assignment. For example, order picking method, size and layout of the storage system, material handling system, product characteristics, demand trends, turnover rates and space requirements. Selecting appropriate storage assignment policies (i.e. random, dedicated or class-based) and routing methods (i.e. transversal, return or combined) with regards to above factors is a possible solution to tackle this problem. However, the efficiency of these policies is interdependent. This paper aims to present a simulation study of a real case regarding storage assignment problem of a manual-pick and multi-level rack warehouse. Performance of the case is measured in terms of travel distance and order retrieval time. The results of the study indicate that the key to effective implementation of a storage assignment system is to match the types of warehouse storage system and the variety of items in the customer order. Also, the use of key performance indicator should clearly reflect the needs of the warehouse.
185 citations
23 Sep 2005
TL;DR: In this paper, a logistieke keten dienen producten fysiek to worden verplaatst van de ene locatie naar de andere, van producenten naar eindgebruikers.
Abstract: textBinnen een logistieke keten dienen producten fysiek te worden verplaatst van de ene locatie naar de andere, van producenten naar eindgebruikers Tijdens dit proces worden producten gewoonlijk opgeslagen op bepaalde plaatsen (magazijnen) voor een bepaalde periode Orderverzameling – het ophalen van producten uit de opslaglocatie in het magazijn naar aanleiding van een specifieke klantorder – is het meest kritieke magazijnproces Het is een arbeidsintensieve operatie in handmatig bestuurde systemen, en een kapitaalintensieve operatie in geautomatiseerde systemen Een niet optimaal functionerend orderverzamelingsproces kan leiden tot onbevredigende service en hoge operationele kosten voor het magazijn, en dientengevolge voor de hele keten Om efficient te kunnen functioneren dient het orderverzamelingsproces robuust te zijn ontworpen en optimaal te worden bestuurd
Dit proefschrift heeft als doel analytische modellen te ontwerpen die het ontwerp en de besturing van efficiente orderverzamelingsprocessen ondersteunen Verschillende methoden worden voorgesteld voor het schatten van de route langs de locaties van de te verzamelen producten, het bepalen van de optimale grenzen van zones in het magazijn die bestemd zijn voor opslag, de indeling van het magazijn, het aantal producten die tegelijk (in een ronde) worden verzameld (de batch size) en het aantal zones in het magazijn die worden ingericht voor het verzamelen en gereedmaken van orders De methoden worden getest middels simulatie experimenten en worden inzichtelijk gemaakt met behulp van rekenexperimenten
182 citations
TL;DR: It turns out that DMSA outperforms random assignment as the number of put away products and the proportion ofPut away products with high turnover rates increase.
Abstract: Among distribution centre operations, order picking has been reported to be the most labour-intensive activity. Sophisticated storage assignment policies adopted to reduce the travel distance of order picking have been explored in the literature. Unfortunately, previous research has been devoted to locating entire products from scratch. Instead, this study intends to propose an adaptive approach, a Data Mining-based Storage Assignment approach (DMSA), to find the optimal storage assignment for newly delivered products that need to be put away when there is vacant shelf space in a distribution centre. In the DMSA, a new association index (AIX) is developed to evaluate the fitness between the put away products and the unassigned storage locations by applying association rule mining. With AIX, the storage location assignment problem (SLAP) can be formulated and solved as a binary integer programming. To evaluate the performance of DMSA, a real-world order database of a distribution centre is obtained and used to compare the results from DMSA with a random assignment approach. It turns out that DMSA outperforms random assignment as the number of put away products and the proportion of put away products with high turnover rates increase.
167 citations
References
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TL;DR: The purpose is to provide a bridge between academic researchers and warehouse practitioners, explaining what planning models and methods are currently available for warehouse operations, and what are the future research opportunities.
847 citations
Posted Content•
TL;DR: This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes, focusing on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning.
Abstract: textOrder picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.
305 citations
TL;DR: The results of the study indicate that the key to effective implementation of a storage assignment system is to match the types of warehouse storage system and the variety of items in the customer order.
Abstract: Determining the proper storage locations for potentially thousands of products is one major task that faces the warehouse manager during the design of a new warehouse or the refurbishment of existing facility. There are many factors affects the storage assignment. For example, order picking method, size and layout of the storage system, material handling system, product characteristics, demand trends, turnover rates and space requirements. Selecting appropriate storage assignment policies (i.e. random, dedicated or class-based) and routing methods (i.e. transversal, return or combined) with regards to above factors is a possible solution to tackle this problem. However, the efficiency of these policies is interdependent. This paper aims to present a simulation study of a real case regarding storage assignment problem of a manual-pick and multi-level rack warehouse. Performance of the case is measured in terms of travel distance and order retrieval time. The results of the study indicate that the key to effective implementation of a storage assignment system is to match the types of warehouse storage system and the variety of items in the customer order. Also, the use of key performance indicator should clearly reflect the needs of the warehouse.
185 citations
23 Sep 2005
TL;DR: In this paper, a logistieke keten dienen producten fysiek to worden verplaatst van de ene locatie naar de andere, van producenten naar eindgebruikers.
Abstract: textBinnen een logistieke keten dienen producten fysiek te worden verplaatst van de ene locatie naar de andere, van producenten naar eindgebruikers Tijdens dit proces worden producten gewoonlijk opgeslagen op bepaalde plaatsen (magazijnen) voor een bepaalde periode Orderverzameling – het ophalen van producten uit de opslaglocatie in het magazijn naar aanleiding van een specifieke klantorder – is het meest kritieke magazijnproces Het is een arbeidsintensieve operatie in handmatig bestuurde systemen, en een kapitaalintensieve operatie in geautomatiseerde systemen Een niet optimaal functionerend orderverzamelingsproces kan leiden tot onbevredigende service en hoge operationele kosten voor het magazijn, en dientengevolge voor de hele keten Om efficient te kunnen functioneren dient het orderverzamelingsproces robuust te zijn ontworpen en optimaal te worden bestuurd
Dit proefschrift heeft als doel analytische modellen te ontwerpen die het ontwerp en de besturing van efficiente orderverzamelingsprocessen ondersteunen Verschillende methoden worden voorgesteld voor het schatten van de route langs de locaties van de te verzamelen producten, het bepalen van de optimale grenzen van zones in het magazijn die bestemd zijn voor opslag, de indeling van het magazijn, het aantal producten die tegelijk (in een ronde) worden verzameld (de batch size) en het aantal zones in het magazijn die worden ingericht voor het verzamelen en gereedmaken van orders De methoden worden getest middels simulatie experimenten en worden inzichtelijk gemaakt met behulp van rekenexperimenten
182 citations
TL;DR: It turns out that DMSA outperforms random assignment as the number of put away products and the proportion ofPut away products with high turnover rates increase.
Abstract: Among distribution centre operations, order picking has been reported to be the most labour-intensive activity. Sophisticated storage assignment policies adopted to reduce the travel distance of order picking have been explored in the literature. Unfortunately, previous research has been devoted to locating entire products from scratch. Instead, this study intends to propose an adaptive approach, a Data Mining-based Storage Assignment approach (DMSA), to find the optimal storage assignment for newly delivered products that need to be put away when there is vacant shelf space in a distribution centre. In the DMSA, a new association index (AIX) is developed to evaluate the fitness between the put away products and the unassigned storage locations by applying association rule mining. With AIX, the storage location assignment problem (SLAP) can be formulated and solved as a binary integer programming. To evaluate the performance of DMSA, a real-world order database of a distribution centre is obtained and used to compare the results from DMSA with a random assignment approach. It turns out that DMSA outperforms random assignment as the number of put away products and the proportion of put away products with high turnover rates increase.
167 citations