113 resultados para Warehouses


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Mode of access: Internet.

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Vol. 52-53 include Wartime Warehousing Industry Conference, 1st-2d

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Mode of access: Internet.

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Logistics distribution network design is one of the major decision problems arising in contemporary supply chain management. The decision involves many quantitative and qualitative factors that may be conflicting in nature. This paper applies an integrated multiple criteria decision making approach to design an optimal distribution network. In the approach, the analytic hierarchy process (AHP) is used first to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, the goal programming (GP) model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. In this paper, two commercial packages are used: Expert Choice for determining the AHP priorities of the warehouses, and LINDO for solving the GP model. © 2007 IEEE.

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This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional costbased approach.

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Warehouse is an essential component in the supply chain, linking the chain partners and providing them with functions of product storage, inbound and outbound operations along with value-added processes. Allocation of warehouse resources should be efficient and effective to achieve optimum productivity and reduce operational costs. Radio frequency identification (RFID) is a technology capable of providing real-time information about supply chain operations. It has been used by warehousing and logistic enterprises to achieve reduced shrinkage, improved material handling and tracking as well as increased accuracy of data collection. However, both academics and practitioners express concerns about challenges to RFID adoption in the supply chain. This paper provides a comprehensive analysis of the problems encountered in RFID implementation at warehouses, discussing the theoretical and practical adoption barriers and causes of not achieving full potential of the technology. Lack of foreseeable return on investment (ROI) and high costs are the most commonly reported obstacles. Variety of standards and radio wave frequencies are identified as source of concern for decision makers. Inaccurate performance of the RFID within the warehouse environment is examined. Description of integration challenges between warehouse management system and RFID technology is given. The paper discusses the existing solutions to technological, investment and performance RFID adoption barriers. Factors to consider when implementing the RFID technology are given to help alleviate implementation problems. By illustrating the challenges of RFID in the warehouse environment and discussing possible solutions the paper aims to help both academics and practitioners to focus on key areas constituting an obstacle to the technology growth. As more studies will address these challenges, the realisation of RFID benefits for warehouses and supply chain will become a reality.

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In recent years the increased interest in introducing radio frequency technology (RFID) in warehousing was observed. First adopters of RFID reported numerous benefits, which included: reduced shrinkage, real-time tracking and better accuracy of data collection. Along with the academic and industrial discussion on benefits which can be achieved in RFID enabled warehouses there are reports on issues related to adoption of RFID technology in warehousing. This paper reviews results of scientific reports of RFID implementation in warehouses and discusses the adoption barriers and causes of not achieving full potential of the technology. Following adoption barriers are identified and set in warehousing context: lack of forseeable return on investment (ROI), unreliable performance of RFID systems, standarisation, integration with legacy systems and privacy/security concerns. As more studies will address these challenges, the realisation of RFID benefits for warehouses will become reality.

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This paper explores the use of the optimization procedures in SAS/OR software with application to the contemporary logistics distribution network design using an integrated multiple criteria decision making approach. Unlike the traditional optimization techniques, the proposed approach, combining analytic hierarchy process (AHP) and goal programming (GP), considers both quantitative and qualitative factors. In the integrated approach, AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, a GP model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. To facilitate the use of integrated multiple criteria decision making approach by SAS users, an ORMCDM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear programming models based on the selected GP model. An example is given to illustrate how one could use the code to design the logistics distribution network.

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In the contemporary customer-driven supply chain, maximization of customer service plays an equally important role as minimization of costs for a company to retain and increase its competitiveness. This article develops a multiple-criteria optimization approach, combining the analytic hierarchy process (AHP) and an integer linear programming (ILP) model, to aid the design of an optimal logistics distribution network. The proposed approach outperforms traditional cost-based optimization techniques because it considers both quantitative and qualitative factors and also aims at maximizing the benefits of deliverer and customers. In the approach, the AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to some critical customer-oriented criteria. The results of AHP prioritization are utilized as the input of the ILP model, the objective of which is to select the best warehouses at the lowest possible cost. In this article, two commercial packages are used: including Expert Choice and LINDO.

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* Supported partially by the Bulgarian National Science Fund under Grant MM-1405/2004

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Through participant observation, held in the administrative region east of Natal / RN, this research aimed to understand about the daily life of men and women living on the streets in the city. How they relate to the space where they live? In this relationship, which uses and survival strategies triggered by this social segment? These were some of the questions that guided this research, in order to highlight the specificities of this way of life and the possible consequences that such a situation could reverberate. In this sense, there was an effort to keep up with people on the streets, their itineraries and seize their narratives. Along the search path - which took place intermittently between the years 2011-2015 - attended spaces of occupation and traffic of this population group in the street, as well as insert me and got involved in events, forums, seminars, meetings and subject of joints on the streets as a political movement (MNPR / RN). They are considered in this study as people on the street to those who occupy the street as their main space of survival and ordering of daily life: in the streets sleep, feed themselves, meet the physiological and hygienic needs, and is where draw sustenance. The street is taken in this research in its broadest sense, including all possible places relatively protected from the cold, rain and exposure to violence, thus includes both open and public spaces: as squares and parks; but also closed and private places: hostels, abandoned warehouses, prisons, etc. It was observed that in none of these spaces guys on the street are established in a fixed manner, in contrast, they experience the roaming, which in part is due to urban systems - which tends to stigmatize them and delete them places - and the very need to survive, because while living in the street differentiated practices are triggered, and these differ from the dominant mode of sedentary life.

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Through participant observation, held in the administrative region east of Natal / RN, this research aimed to understand about the daily life of men and women living on the streets in the city. How they relate to the space where they live? In this relationship, which uses and survival strategies triggered by this social segment? These were some of the questions that guided this research, in order to highlight the specificities of this way of life and the possible consequences that such a situation could reverberate. In this sense, there was an effort to keep up with people on the streets, their itineraries and seize their narratives. Along the search path - which took place intermittently between the years 2011-2015 - attended spaces of occupation and traffic of this population group in the street, as well as insert me and got involved in events, forums, seminars, meetings and subject of joints on the streets as a political movement (MNPR / RN). They are considered in this study as people on the street to those who occupy the street as their main space of survival and ordering of daily life: in the streets sleep, feed themselves, meet the physiological and hygienic needs, and is where draw sustenance. The street is taken in this research in its broadest sense, including all possible places relatively protected from the cold, rain and exposure to violence, thus includes both open and public spaces: as squares and parks; but also closed and private places: hostels, abandoned warehouses, prisons, etc. It was observed that in none of these spaces guys on the street are established in a fixed manner, in contrast, they experience the roaming, which in part is due to urban systems - which tends to stigmatize them and delete them places - and the very need to survive, because while living in the street differentiated practices are triggered, and these differ from the dominant mode of sedentary life.

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Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples.

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Zur Gewährleistung einer kundenindividuellen, flexiblen Produktion, welche auch kleine Losegrößen kostengünstig produzieren kann, werden zukünftig Fabriken der Prozessindustrie nicht nur modular sondern darüber hinaus mobil sein. Zur Erreichung dieses Zieles werden neben Produktionselemente, auch sämtliche Logistikkomponenten in Containern zu Modulen zusammengefasst. Hierfür ist es notwendig Lager, aber auch komplexe Verpackungsmaschinen, zu konzipieren welche sich zusammen mit Produktionsmodulen, nach dem Plug-and-Produce-Prinzip, zu kompletten Produktionslinien verknüpfen lassen. Die Steuerung und Organisation erfolgt nach den Gedanken von Industrie 4.0.

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In diesem Beitrag wird eine neue Methode zur Analyse des manuellen Kommissionierprozesses vorgestellt, mit der u. a. die Kommissionierzeitanteile automatisch erfasst werden können. Diese Methode basiert auf einer sensorgestützten Bewegungsklassifikation, wie sie bspw. im Sport oder in der Medizin Anwendung findet. Dabei werden mobile Sensoren genutzt, die fortlaufend Messwerte wie z. B. die Beschleunigung oder die Drehgeschwindigkeit des Kommissionierers aufzeichnen. Auf Basis dieser Daten können Informationen über die ausgeführten Bewegungen und insbesondere über die durchlaufenen Bewegungszustände gewonnen werden. Dieser Ansatz wird im vorliegenden Beitrag auf die Kommissionierung übertragen. Dazu werden zunächst Klassen relevanter Bewegungen identifiziert und anschließend mit Verfahren aus dem maschinellen Lernen verarbeitet. Die Klassifikation erfolgt nach dem Prinzip des überwachten Lernens. Dabei werden durchschnittliche Erkennungsraten von bis zu 78,94 Prozent erzielt.