Academic literature on the topic 'Warehouses Design'
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Journal articles on the topic "Warehouses Design"
1
Phan, Mai Ha, Ha Quang Thinh Ngo, Tien Trung Kieu, and Linh Y. Thai. "Redesigning Finished Product Warehouse Layout - A Case Study." Applied Mechanics and Materials 902 (September 2020): 103–13. http://dx.doi.org/10.4028/www.scientific.net/amm.902.103.
Full textAbstract:
System engineering methods are often used to design complex systems like airplanes. However, this method is also useful to propose solutions to redesign logistics systems such as warehouses and transport systems. This paper will apply system engineering in analyzing the late order problem at a pesticide company, thereby surveying stakeholders needs for warehouse re-designing. The functional analysis in the warehouse will be carried out in the concept analysis section to propose warehouse’s layout redesign alternatives that based on the demand of storage capacity and throughput. The authors also used the AHP method to select the final design layout. The detailed design section builds the operation process for the warehouse as well as the codification for commodity storage slots along with these tables forms that support for warehouse management. These solutions increase warehouse performance as well as the utilization in warehouses when applied in practice. Therefore, the system engineering method should be used in warehouse’s redesign
2
Di Tria, Francesco, Ezio Lefons, and Filippo Tangorra. "A Framework for Evaluating Design Methodologies for Big Data Warehouses." International Journal of Data Warehousing and Mining 14, no. 1 (January 2018): 15–39. http://dx.doi.org/10.4018/ijdwm.2018010102.
Full textAbstract:
This article describes how the evaluation of modern data warehouses considers new solutions adopted for facing the radical changes caused by the necessity of reducing the storage volume, while increasing the velocity in multidimensional design and data elaboration, even in presence of unstructured data that are useful for providing qualitative information. The aim is to set up a framework for the evaluation of the physical and methodological characteristics of a data warehouse, realized by considering the factors that affect the data warehouse's lifecycle when taking into account the Big Data issues (Volume, Velocity, Variety, Value, and Veracity). The contribution is the definition of a set of criteria for classifying Big Data Warehouses on the basis of their methodological characteristics. Based on these criteria, the authors defined a set of metrics for measuring the quality of Big Data Warehouses in reference to the design specifications. They show through a case study how the proposed metrics are able to check the eligibility of methodologies falling in different classes in the Big Data context.
3
Mankour, Ikram, and Khadidja Yachba. "Comparative Study for Facilities Location Problem in Supply Chain Design." International Journal of Swarm Intelligence Research 13, no. 1 (January 1, 2022): 1–16. http://dx.doi.org/10.4018/ijsir.304718.
Full textAbstract:
The interest in supply chains has increased in the last few years. The supply chain optimization aims to reduce the delays and costs generated between suppliers and customers. The researchers focus primarily on the supply chain design to transport products to clients. This paper attempts to find an optimal warehouse location using a metaheuristic method. The goal is to select the optimum warehouse location. FLP-GA (Facility Location Problem - Genetic Algorithms) is the proposed approach based on genetic algorithms that reduce the number of warehouses to be opened, the overall costs, and the distances between them from a set of customers and candidate warehouses. The authors compared the approach with three other methods. This approach can select a reduced number of warehouses with minimal cost.
4
Kato, Takumi, and Ryota Kamoshida. "Multi-Agent Simulation Environment for Logistics Warehouse Design Based on Self-Contained Agents." Applied Sciences 10, no. 21 (October 27, 2020): 7552. http://dx.doi.org/10.3390/app10217552.
Full textAbstract:
We propose a multi-agent simulation environment for logistics warehouses. Simulation is a crucial part of designing industrial systems, such as logistics warehouses. A warehouse is a multi-agent system (MAS) that consists of various autonomous subsystems with robots, material-handling equipment, and human workers. It is generally difficult to analyze the performance of a MAS thus, it is important to model a warehouse and conduct simulations to design and evaluate the possible system configurations. However, the cost of modeling warehouses and modifying the models is high because there are various components and interactions compared to conventional multi-agent simulations. We proposed a self-contained agent architecture and message architecture of a multi-agent simulation environment for logistics warehouses to reduce the simulation-model development and modification costs. We quantitatively evaluated our environment in terms of development costs by comparing such costs of our environment and a widely used multi-agent simulation environment.
5
Bimonte, Sandro, Omar Boussaid, Michel Schneider, and Fabien Ruelle. "Design and Implementation of Active Stream Data Warehouses." International Journal of Data Warehousing and Mining 15, no. 2 (April 2019): 1–21. http://dx.doi.org/10.4018/ijdwm.2019040101.
Full textAbstract:
In the era of Big Data, more and more stream data is available. In the same way, Decision Support Systems (DSS) tools, such as data warehouses and alert systems, become more and more sophisticated, and conceptual modeling tools are consequently mandatory for successfully DSS projects. Formalisms such as UML and ER have been widely used in the context of classical information and data warehouse systems, but they have not been investigated yet for stream data warehouses to deal with alert systems. Therefore, in this article, the authors introduce the notion of Active Stream Data Warehouse (ASDW) and this article proposes a UML profile for designing Active Stream Data Warehouses. Indeed, this article extends the ICSOLAP profile to take into account continuous and window OLAP queries. Moreover, this article studies the duality of the stream and OLAP decision-making process and the authors propose a set of ECA rules to automatically trigger OLAP operators. The UML profile is implemented in a new OLAP architecture, and it is validated using an environmental case study concerning the wind monitoring.
6
Suhanov, Valeriy, and Oleg Lankin. "Logical design of information support for distributed information systems of critical application." Modeling of systems and processes 14, no. 2 (July 26, 2021): 67–73. http://dx.doi.org/10.12737/2219-0767-2021-14-2-67-73.
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The article deals with new information technologies for building a data warehouse in a distributed information system of critical application. The existing principles of creating data warehouses, as well as the outlined ways to improve them, are always associated with the collection, storage and use of information that is recorded at a certain point in time, while they store data corresponding to the last time count. This approach to the development and application of data warehouses can be called static, since it does not store or display the behavior of objects at past points in time. However, the objects that are included in the data warehouse have pronounced dynamic properties and therefore must be displayed dynamically. The way out of this situation is the creation of analytical data warehouses, which will provide an opportunity to more effectively solve traditional and qualitatively new tasks in the system under consideration.
7
Da Cunha Reis, Augusto, Cristina Gomes de Souza, Nayara Nogueira da Costa, Gustavo Henrique Cordeiro Stender, Pedro Senna Vieira, and Nélio Domingues Pizzolato. "Warehouse design: a systematic literature review." Brazilian Journal of Operations & Production Management 14, no. 4 (December 8, 2017): 542. http://dx.doi.org/10.14488/bjopm.2017.v14.n4.a10.
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Abstract: This study proposes improving the understanding of the main aspects involved in the design of warehouses by the construction of a framework that reveals the state-of-art. The initial research bibliography generated a framework, which was structured in three dimensions: inputs; design and implementation; and outputs. The validation of framework was accomplished through a systematic review of the literature, covering 68 articles published in the period 1999- 2015. This study covered the main aspects highlighted in the academic literature that influence the design of warehouses. Additionally, an overview of the publications based on a theoretical/empirical and a quantitative/qualitative approach was pointed out. This paper aims to contribute to both industry and academic. On the one hand, the framework aggregates value for professionals by permitting the rapid identification of variables, which must be considered in warehouse design. On the other hand, by systematizing the warehouse design area, researchers are able to identify gaps that may generate future studies.
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Chen, Chen, Jian Mao, and Xingwen Gan. "Design of Automated Warehouse Management System." MATEC Web of Conferences 232 (2018): 03049. http://dx.doi.org/10.1051/matecconf/201823203049.
Full textAbstract:
Aiming at the low degree of automation in production enterprises, real-time tracking and automatic access to warehouses are realized by developing warehouse management software. The paper first analyzes the system requirements, and then gives the overall design plan, through C#, MySQL and TCP. IP communication protocol, compiled a set of warehouse management system software. The actual application shows that the automation level and management efficiency of production enterprises are improved.
9
Phyllis, Chepkonga. "Determination of Performance Indicators for Warehouse Evaluation: A Case of Medium Sized Warehouses in Nakuru Town." Journal of Procurement & Supply Chain 5, no. 2 (November 11, 2021): 32–38. http://dx.doi.org/10.53819/81018102t5034.
Full textAbstract:
Evaluation of warehouse processes is required for decision making purposes and the improvement of warehouse operations. To evaluate warehouse processes, it is essential to identify key indicators in the warehouse operations. This research was intended to identify the significant indicators of warehouse performance that would support management decision making on the improvement of warehouse operations. In this research 20 indicators were identified in four warehouse activities based on Frazelle model. The most important indicators in each warehouse were then determined. The study was conducted through a descriptive design using a survey of 3 medium warehouses in Nakuru. The study employed purposive sampling to select the sample and sample elements. The sample size of 10 warehouse management officers were used in the study. Structured questionnaire was adopted as data collection instrument. The research findings indicated that most important performance indicators for receiving is productivity, for storage is space utilization, for order picking is cycle time and for shipping is productivity. Process improvement steps were proposed based on benchmarking among warehouses handling similar goods. It was noted that different types of warehouses require different indicators. The study concluded that measurement of warehouse processes is important and enables operations improvements and cost reduction. Keywords: Warehouse procedures, warehouse performance, warehouse improvement, medium sized warehouses, Nakuru town, Kenya
10
van Geest, Maarten, Bedir Tekinerdogan, and Cagatay Catal. "Smart Warehouses: Rationale, Challenges and Solution Directions." Applied Sciences 12, no. 1 (December 27, 2021): 219. http://dx.doi.org/10.3390/app12010219.
Full textAbstract:
Smart warehouses aim to increase the overall service quality, productivity, and efficiency of the warehouse while minimizing costs and failures. In recent years, several studies have proposed and discussed different types of smart warehouses, identified key challenges, and proposed several solution directions for coping with these challenges. The objective of this article is to identify, evaluate, and synthesize the relevant studies discussing the design of smart warehouses and the transition to these new types of warehouses. We applied a systematic literature review (SLR) protocol to select primary studies. The SLR resulted in the identification of the domains in which smart warehouses are applied, key motivations for adopting smart warehouses, current distinctive characteristics of smart warehouses, currently adopted technologies for realizing smart warehouses, and challenges and strategies for transitioning to smart warehouses. To the best of our knowledge, no SLR paper has been published yet on smart warehouses, and therefore, this is timely research as organizations are nowadays transitioning to smart warehouses.
Dissertations / Theses on the topic "Warehouses Design"
1
Romero, Moral Óscar. "Automating the multidimensional design of data warehouses." Doctoral thesis, Universitat Politècnica de Catalunya, 2010. http://hdl.handle.net/10803/6670.
Full textAbstract:
Les experiències prèvies en l'àmbit dels magatzems de dades (o data warehouse), mostren que l'esquema multidimensional del data warehouse ha de ser fruit d'un enfocament híbrid; això és, una proposta que consideri tant els requeriments d'usuari com les fonts de dades durant el procés de disseny.Com a qualsevol altre sistema, els requeriments són necessaris per garantir que el sistema desenvolupat satisfà les necessitats de l'usuari. A més, essent aquest un procés de reenginyeria, les fonts de dades s'han de tenir en compte per: (i) garantir que el magatzem de dades resultant pot ésser poblat amb dades de l'organització, i, a més, (ii) descobrir capacitats d'anàlisis no evidents o no conegudes per l'usuari.
Actualment, a la literatura s'han presentat diversos mètodes per donar suport al procés de modelatge del magatzem de dades. No obstant això, les propostes basades en un anàlisi dels requeriments assumeixen que aquestos són exhaustius, i no consideren que pot haver-hi informació rellevant amagada a les fonts de dades. Contràriament, les propostes basades en un anàlisi exhaustiu de les fonts de dades maximitzen aquest enfocament, i proposen tot el coneixement multidimensional que es pot derivar des de les fonts de dades i, conseqüentment, generen massa resultats. En aquest escenari, l'automatització del disseny del magatzem de dades és essencial per evitar que tot el pes de la tasca recaigui en el dissenyador (d'aquesta forma, no hem de confiar únicament en la seva habilitat i coneixement per aplicar el mètode de disseny elegit). A més, l'automatització de la tasca allibera al dissenyador del sempre complex i costós anàlisi de les fonts de dades (que pot arribar a ser inviable per grans fonts de dades).
Avui dia, els mètodes automatitzables analitzen en detall les fonts de dades i passen per alt els requeriments. En canvi, els mètodes basats en l'anàlisi dels requeriments no consideren l'automatització del procés, ja que treballen amb requeriments expressats en llenguatges d'alt nivell que un ordenador no pot manegar. Aquesta mateixa situació es dona en els mètodes híbrids actual, que proposen un enfocament seqüencial, on l'anàlisi de les dades es complementa amb l'anàlisi dels requeriments, ja que totes dues tasques pateixen els mateixos problemes que els enfocament purs.
En aquesta tesi proposem dos mètodes per donar suport a la tasca de modelatge del magatzem de dades: MDBE (Multidimensional Design Based on Examples) and AMDO (Automating the Multidimensional Design from Ontologies). Totes dues consideren els requeriments i les fonts de dades per portar a terme la tasca de modelatge i a més, van ser pensades per superar les limitacions dels enfocaments actuals.
1. MDBE segueix un enfocament clàssic, en el que els requeriments d'usuari són coneguts d'avantmà. Aquest mètode es beneficia del coneixement capturat a les fonts de dades, però guia el procés des dels requeriments i, conseqüentment, és capaç de treballar sobre fonts de dades semànticament pobres. És a dir, explotant el fet que amb uns requeriments de qualitat, podem superar els inconvenients de disposar de fonts de dades que no capturen apropiadament el nostre domini de treball.
2. A diferència d'MDBE, AMDO assumeix un escenari on es disposa de fonts de dades semànticament riques. Per aquest motiu, dirigeix el procés de modelatge des de les fonts de dades, i empra els requeriments per donar forma i adaptar els resultats generats a les necessitats de l'usuari. En aquest context, a diferència de l'anterior, unes fonts de dades semànticament riques esmorteeixen el fet de no tenir clars els requeriments d'usuari d'avantmà.
Cal notar que els nostres mètodes estableixen un marc de treball combinat que es pot emprar per decidir, donat un escenari concret, quin enfocament és més adient. Per exemple, no es pot seguir el mateix enfocament en un escenari on els requeriments són ben coneguts d'avantmà i en un escenari on aquestos encara no estan clars (un cas recorrent d'aquesta situació és quan l'usuari no té clares les capacitats d'anàlisi del seu propi sistema). De fet, disposar d'uns bons requeriments d'avantmà esmorteeix la necessitat de disposar de fonts de dades semànticament riques, mentre que a l'inversa, si disposem de fonts de dades que capturen adequadament el nostre domini de treball, els requeriments no són necessaris d'avantmà. Per aquests motius, en aquesta tesi aportem un marc de treball combinat que cobreix tots els possibles escenaris que podem trobar durant la tasca de modelatge del magatzem de dades.
Previous experiences in the data warehouse field have shown that the data warehouse multidimensional conceptual schema must be derived from a hybrid approach: i.e., by considering both the end-user requirements and the data sources, as first-class citizens. Like in any other system, requirements guarantee that the system devised meets the end-user necessities. In addition, since the data warehouse design task is a reengineering process, it must consider the underlying data sources of the organization: (i) to guarantee that the data warehouse must be populated from data available within the organization, and (ii) to allow the end-user discover unknown additional analysis capabilities.
Currently, several methods for supporting the data warehouse modeling task have been provided. However, they suffer from some significant drawbacks. In short, requirement-driven approaches assume that requirements are exhaustive (and therefore, do not consider the data sources to contain alternative interesting evidences of analysis), whereas data-driven approaches (i.e., those leading the design task from a thorough analysis of the data sources) rely on discovering as much multidimensional knowledge as possible from the data sources. As a consequence, data-driven approaches generate too many results, which mislead the user. Furthermore, the design task automation is essential in this scenario, as it removes the dependency on an expert's ability to properly apply the method chosen, and the need to analyze the data sources, which is a tedious and timeconsuming task (which can be unfeasible when working with large databases). In this sense, current automatable methods follow a data-driven approach, whereas current requirement-driven approaches overlook the process automation, since they tend to work with requirements at a high level of abstraction. Indeed, this scenario is repeated regarding data-driven and requirement-driven stages within current hybrid approaches, which suffer from the same drawbacks than pure data-driven or requirement-driven approaches.
In this thesis we introduce two different approaches for automating the multidimensional design of the data warehouse: MDBE (Multidimensional Design Based on Examples) and AMDO (Automating the Multidimensional Design from Ontologies). Both approaches were devised to overcome the limitations from which current approaches suffer. Importantly, our approaches consider opposite initial assumptions, but both consider the end-user requirements and the data sources as first-class citizens.
1. MDBE follows a classical approach, in which the end-user requirements are well-known beforehand. This approach benefits from the knowledge captured in the data sources, but guides the design task according to requirements and consequently, it is able to work and handle semantically poorer data sources. In other words, providing high-quality end-user requirements, we can guide the process from the knowledge they contain, and overcome the fact of disposing of bad quality (from a semantical point of view) data sources.
2. AMDO, as counterpart, assumes a scenario in which the data sources available are semantically richer. Thus, the approach proposed is guided by a thorough analysis of the data sources, which is properly adapted to shape the output result according to the end-user requirements. In this context, disposing of high-quality data sources, we can overcome the fact of lacking of expressive end-user requirements.
Importantly, our methods establish a combined and comprehensive framework that can be used to decide, according to the inputs provided in each scenario, which is the best approach to follow. For example, we cannot follow the same approach in a scenario where the end-user requirements are clear and well-known, and in a scenario in which the end-user requirements are not evident or cannot be easily elicited (e.g., this may happen when the users are not aware of the analysis capabilities of their own sources). Interestingly, the need to dispose of requirements beforehand is smoothed by the fact of having semantically rich data sources. In lack of that, requirements gain relevance to extract the multidimensional knowledge from the sources.
So that, we claim to provide two approaches whose combination turns up to be exhaustive with regard to the scenarios discussed in the literature
2
Romero, Moral Oscar. "Automating the multidimensional design of data warehouses." Doctoral thesis, Universitat Politècnica de Catalunya, 2010. http://hdl.handle.net/10803/6670.
Full textAbstract:
Les experiències prèvies en l'àmbit dels magatzems de dades (o data warehouse), mostren que l'esquema multidimensional del data warehouse ha de ser fruit d'un enfocament híbrid; això és, una proposta que consideri tant els requeriments d'usuari com les fonts de dades durant el procés de disseny.Com a qualsevol altre sistema, els requeriments són necessaris per garantir que el sistema desenvolupat satisfà les necessitats de l'usuari. A més, essent aquest un procés de reenginyeria, les fonts de dades s'han de tenir en compte per: (i) garantir que el magatzem de dades resultant pot ésser poblat amb dades de l'organització, i, a més, (ii) descobrir capacitats d'anàlisis no evidents o no conegudes per l'usuari.Actualment, a la literatura s'han presentat diversos mètodes per donar suport al procés de modelatge del magatzem de dades. No obstant això, les propostes basades en un anàlisi dels requeriments assumeixen que aquestos són exhaustius, i no consideren que pot haver-hi informació rellevant amagada a les fonts de dades. Contràriament, les propostes basades en un anàlisi exhaustiu de les fonts de dades maximitzen aquest enfocament, i proposen tot el coneixement multidimensional que es pot derivar des de les fonts de dades i, conseqüentment, generen massa resultats. En aquest escenari, l'automatització del disseny del magatzem de dades és essencial per evitar que tot el pes de la tasca recaigui en el dissenyador (d'aquesta forma, no hem de confiar únicament en la seva habilitat i coneixement per aplicar el mètode de disseny elegit). A més, l'automatització de la tasca allibera al dissenyador del sempre complex i costós anàlisi de les fonts de dades (que pot arribar a ser inviable per grans fonts de dades).Avui dia, els mètodes automatitzables analitzen en detall les fonts de dades i passen per alt els requeriments. En canvi, els mètodes basats en l'anàlisi dels requeriments no consideren l'automatització del procés, ja que treballen amb requeriments expressats en llenguatges d'alt nivell que un ordenador no pot manegar. Aquesta mateixa situació es dona en els mètodes híbrids actual, que proposen un enfocament seqüencial, on l'anàlisi de les dades es complementa amb l'anàlisi dels requeriments, ja que totes dues tasques pateixen els mateixos problemes que els enfocament purs.En aquesta tesi proposem dos mètodes per donar suport a la tasca de modelatge del magatzem de dades: MDBE (Multidimensional Design Based on Examples) and AMDO (Automating the Multidimensional Design from Ontologies). Totes dues consideren els requeriments i les fonts de dades per portar a terme la tasca de modelatge i a més, van ser pensades per superar les limitacions dels enfocaments actuals.1. MDBE segueix un enfocament clàssic, en el que els requeriments d'usuari són coneguts d'avantmà. Aquest mètode es beneficia del coneixement capturat a les fonts de dades, però guia el procés des dels requeriments i, conseqüentment, és capaç de treballar sobre fonts de dades semànticament pobres. És a dir, explotant el fet que amb uns requeriments de qualitat, podem superar els inconvenients de disposar de fonts de dades que no capturen apropiadament el nostre domini de treball.2. A diferència d'MDBE, AMDO assumeix un escenari on es disposa de fonts de dades semànticament riques. Per aquest motiu, dirigeix el procés de modelatge des de les fonts de dades, i empra els requeriments per donar forma i adaptar els resultats generats a les necessitats de l'usuari. En aquest context, a diferència de l'anterior, unes fonts de dades semànticament riques esmorteeixen el fet de no tenir clars els requeriments d'usuari d'avantmà.Cal notar que els nostres mètodes estableixen un marc de treball combinat que es pot emprar per decidir, donat un escenari concret, quin enfocament és més adient. Per exemple, no es pot seguir el mateix enfocament en un escenari on els requeriments són ben coneguts d'avantmà i en un escenari on aquestos encara no estan clars (un cas recorrent d'aquesta situació és quan l'usuari no té clares les capacitats d'anàlisi del seu propi sistema). De fet, disposar d'uns bons requeriments d'avantmà esmorteeix la necessitat de disposar de fonts de dades semànticament riques, mentre que a l'inversa, si disposem de fonts de dades que capturen adequadament el nostre domini de treball, els requeriments no són necessaris d'avantmà. Per aquests motius, en aquesta tesi aportem un marc de treball combinat que cobreix tots els possibles escenaris que podem trobar durant la tasca de modelatge del magatzem de dades.Previous experiences in the data warehouse field have shown that the data warehouse multidimensional conceptual schema must be derived from a hybrid approach: i.e., by considering both the end-user requirements and the data sources, as first-class citizens. Like in any other system, requirements guarantee that the system devised meets the end-user necessities. In addition, since the data warehouse design task is a reengineering process, it must consider the underlying data sources of the organization: (i) to guarantee that the data warehouse must be populated from data available within the organization, and (ii) to allow the end-user discover unknown additional analysis capabilities.Currently, several methods for supporting the data warehouse modeling task have been provided. However, they suffer from some significant drawbacks. In short, requirement-driven approaches assume that requirements are exhaustive (and therefore, do not consider the data sources to contain alternative interesting evidences of analysis), whereas data-driven approaches (i.e., those leading the design task from a thorough analysis of the data sources) rely on discovering as much multidimensional knowledge as possible from the data sources. As a consequence, data-driven approaches generate too many results, which mislead the user. Furthermore, the design task automation is essential in this scenario, as it removes the dependency on an expert's ability to properly apply the method chosen, and the need to analyze the data sources, which is a tedious and timeconsuming task (which can be unfeasible when working with large databases). In this sense, current automatable methods follow a data-driven approach, whereas current requirement-driven approaches overlook the process automation, since they tend to work with requirements at a high level of abstraction. Indeed, this scenario is repeated regarding data-driven and requirement-driven stages within current hybrid approaches, which suffer from the same drawbacks than pure data-driven or requirement-driven approaches.In this thesis we introduce two different approaches for automating the multidimensional design of the data warehouse: MDBE (Multidimensional Design Based on Examples) and AMDO (Automating the Multidimensional Design from Ontologies). Both approaches were devised to overcome the limitations from which current approaches suffer. Importantly, our approaches consider opposite initial assumptions, but both consider the end-user requirements and the data sources as first-class citizens.1. MDBE follows a classical approach, in which the end-user requirements are well-known beforehand. This approach benefits from the knowledge captured in the data sources, but guides the design task according to requirements and consequently, it is able to work and handle semantically poorer data sources. In other words, providing high-quality end-user requirements, we can guide the process from the knowledge they contain, and overcome the fact of disposing of bad quality (from a semantical point of view) data sources.2. AMDO, as counterpart, assumes a scenario in which the data sources available are semantically richer. Thus, the approach proposed is guided by a thorough analysis of the data sources, which is properly adapted to shape the output result according to the end-user requirements. In this context, disposing of high-quality data sources, we can overcome the fact of lacking of expressive end-user requirements.Importantly, our methods establish a combined and comprehensive framework that can be used to decide, according to the inputs provided in each scenario, which is the best approach to follow. For example, we cannot follow the same approach in a scenario where the end-user requirements are clear and well-known, and in a scenario in which the end-user requirements are not evident or cannot be easily elicited (e.g., this may happen when the users are not aware of the analysis capabilities of their own sources). Interestingly, the need to dispose of requirements beforehand is smoothed by the fact of having semantically rich data sources. In lack of that, requirements gain relevance to extract the multidimensional knowledge from the sources.So that, we claim to provide two approaches whose combination turns up to be exhaustive with regard to the scenarios discussed in the literature
3
Jürgens, Marcus. "Index structures for data warehouses /." Berlin [u.a.] : Springer, 2002. http://www.loc.gov/catdir/enhancements/fy0817/2002021075-d.html.
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Siqueira, Thiago Luís Lopes. "The design of vague spatial data warehouses." Universidade Federal de São Carlos, 2015. https://repositorio.ufscar.br/handle/ufscar/298.
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Previous issue date: 2015-12-07Universidade Federal de Minas Gerais
O data warehouse espacial (DWE) é um banco de dados multidimensional integrado e volumoso que armazena dados espaciais e dados convencionais. Já o processamento analítico espacial online (SOLAP) permite consultar o DWE, tanto pela seleção de dados espaciais que satisfazem um relacionamento topológico, quanto pela agregação dos dados espaciais. Deste modo, DWE e SOLAP beneficiam o suporte a tomada de decisão. As aplicações de DWE e SOLAP abordam majoritarimente fenômenos representados por dados espaciais exatos, ou seja, que assumem localizações e fronteiras bem definidas. Contudo, tais aplicações negligenciam dados espaciais afetados por imperfeições, tais como a vagueza espacial, a qual interfere na identificação precisa de um objeto e de seus vizinhos. Um objeto espacial vago não tem sua fronteira ou seu interior precisamente definidos. Além disso, é composto por partes que certamente pertencem a ele e partes que possivelmente pertencem a ele. Apesar de inúmeros fenômenos do mundo real serem caracterizados pela vagueza espacial, na literatura consultada não se identificaram trabalhos que considerassem a vagueza espacial no projeto de DWE e nem para consultar o DWE. Tal limitação motivou a elaboração desta tese de doutorado, a qual introduz os conceitos de DWE vago e de SOLAP vago. Um DWE vago é um DWE que armazena dados espaciais vagos, enquanto que SOLAP vago provê os meios para consultar o DWE vago. Nesta tese, o projeto de DWE vago é abordado e as principais contribuições providas são: (i) o modelo conceitual VSCube que viabiliza a criação de um cubos de dados multidimensional para representar o esquema conceitual de um DWE vago; (ii) o modelo conceitual VSMultiDim que permite criar um diagrama para representar o esquema conceitual de um DWE vago; (iii) diretrizes para o projeto lógico do DWE vago e de suas restrições de integridade, e para estender a linguagem SQL visando processar as consultas de SOLAP vago no DWE vago; e (iv) o índice VSB-index que aprimora o desempenho do processamento de consultas no DWE vago. A aplicabilidade dessas contribuições é demonstrada em dois estudos de caso no domínio da agricultura, por meio da criação de esquemas conceituais de DWE vago, da transformação dos esquemas conceituais em esquemas lógicos de DWE vago, e do processamento de consultas envolvendo as regiões vagas do DWE vago.
Spatial data warehouses (SDW) and spatial online analytical processing (SOLAP) enhance decision making by enabling spatial analysis combined with multidimensional analytical queries. A SDW is an integrated and voluminous multidimensional database containing both conventional and spatial data. SOLAP allows querying SDWs with multidimensional queries that select spatial data that satisfy a given topological relationship and that aggregate spatial data. Existing SDW and SOLAP applications mostly consider phenomena represented by spatial data having exact locations and sharp boundaries. They neglect the fact that spatial data may be affected by imperfections, such as spatial vagueness, which prevents distinguishing an object from its neighborhood. A vague spatial object does not have a precisely defined boundary and/or interior. Thus, it may have a broad boundary and a blurred interior, and is composed of parts that certainly belong to it and parts that possibly belong to it. Although several real-world phenomena are characterized by spatial vagueness, no approach in the literature addresses both spatial vagueness and the design of SDWs nor provides multidimensional analysis over vague spatial data. These shortcomings motivated the elaboration of this doctoral thesis, which addresses both vague spatial data warehouses (vague SDWs) and vague spatial online analytical processing (vague SOLAP). A vague SDW is a SDW that comprises vague spatial data, while vague SOLAP allows querying vague SDWs. The major contributions of this doctoral thesis are: (i) the Vague Spatial Cube (VSCube) conceptual model, which enables the creation of conceptual schemata for vague SDWs using data cubes; (ii) the Vague Spatial MultiDim (VSMultiDim) conceptual model, which enables the creation of conceptual schemata for vague SDWs using diagrams; (iii) guidelines for designing relational schemata and integrity constraints for vague SDWs, and for extending the SQL language to enable vague SOLAP; (iv) the Vague Spatial Bitmap Index (VSB-index), which improves the performance to process queries against vague SDWs. The applicability of these contributions is demonstrated in two applications of the agricultural domain, by creating conceptual schemata for vague SDWs, transforming these conceptual schemata into logical schemata for vague SDWs, and efficiently processing queries over vague SDWs.
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Lopes, Siqueira Thiago Luis. "The Design of Vague Spatial Data Warehouses." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/221701.
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Spatial data warehouses (SDW) and spatial online analytical processing (SOLAP) enhance decision making by enabling spatial analysis combined with multidimensional analytical queries. A SDW is an integrated and voluminous multidimensional database containing both conventional and spatial data. SOLAP allows querying SDWs with multidimensional queries that select spatial data that satisfy a given topological relationship and that aggregate spatial data. Existing SDW and SOLAP applications mostly consider phenomena represented by spatial data having exact locations and sharp boundaries. They neglect the fact that spatial data may be affected by imperfections, such as spatial vagueness, which prevents distinguishing an object from its neighborhood. A vague spatial object does not have a precisely defined boundary and/or interior. Thus, it may have a broad boundary and a blurred interior, and is composed of parts that certainly belong to it and parts that possibly belong to it. Although several real-world phenomena are characterized by spatial vagueness, no approach in the literature addresses both spatial vagueness and the design of SDWs nor provides multidimensional analysis over vague spatial data. These shortcomings motivated the elaboration of this doctoral thesis, which addresses both vague spatial data warehouses (vague SDWs) and vague spatial online analytical processing (vague SOLAP). A vague SDW is a SDW that comprises vague spatial data, while vague SOLAP allows querying vague SDWs. The major contributions of this doctoral thesis are: (i) the Vague Spatial Cube (VSCube) conceptual model, which enables the creation of conceptual schemata for vague SDWs using data cubes; (ii) the Vague Spatial MultiDim (VSMultiDim) conceptual model, which enables the creation of conceptual schemata for vague SDWs using diagrams; (iii) guidelines for designing relational schemata and integrity constraints for vague SDWs, and for extending the SQL language to enable vague SOLAP; (iv) the Vague Spatial Bitmap Index (VSB-index), which improves the performance to process queries against vague SDWs. The applicability of these contributions is demonstrated in two applications of the agricultural domain, by creating conceptual schemata for vague SDWs, transforming these conceptual schemata into logical schemata for vague SDWs, and efficiently processing queries over vague SDWs.Les entrepôts de données spatiales (EDS) et l'analyse en ligne spatiale (ALS) améliorent la prise de décision en permettant l'analyse spatiale combinée avec des requêtes analytiques multidimensionnelles. Un EDS est une base de données multidimensionnelle intégrée et volumineuse qui contient des données classiques et des données spatiales. L'ALS permet l'interrogation des EDS avec des requêtes multidimensionnelles qui sélectionnent des données spatiales qui satisfont une relation topologique donnée et qui agrègent les données spatiales. Les EDS et l'ALS considèrent essentiellement des phénomènes représentés par des données spatiales ayant une localisation exacte et des frontières précises. Ils négligent que les données spatiales peuvent être affectées par des imperfections, comme l'imprécision spatiale, ce qui empêche de distinguer précisément un objet de son entourage. Un objet spatial vague n'a pas de frontière et/ou un intérieur précisément définis. Ainsi, il peut avoir une frontière large et un intérieur flou, et est composé de parties qui lui appartiennent certainement et des parties qui lui appartiennent éventuellement. Bien que plusieurs phénomènes du monde réel sont caractérisés par l'imprécision spatiale, il n'y a pas dans la littérature des approches qui adressent en même temps l'imprécision spatiale et la conception d'EDS ni qui fournissent une analyse multidimensionnelle des données spatiales vagues. Ces lacunes ont motivé l'élaboration de cette thèse de doctorat, qui adresse à la fois les entrepôts de données spatiales vagues (EDS vagues) et l'analyse en ligne spatiale vague (ALS vague). Un EDS vague est un EDS qui comprend des données spatiales vagues, tandis que l'ALS vague permet d'interroger des EDS vagues. Les contributions majeures de cette thèse de doctorat sont: (i) le modèle conceptuel Vague Spatial Cube (VSCube), qui permet la création de schémas conceptuels pour des EDS vagues à l'aide de cubes de données; (ii) le modèle conceptuel Vague Spatial MultiDim (VSMultiDim), qui permet la création de schémas conceptuels pour des EDS vagues à l'aide de diagrammes; (iii) des directives pour la conception de schémas relationnels et des contraintes d'intégrité pour des EDS vagues, et pour l'extension du langage SQL pour permettre l'ALS vague; (iv) l'indice Vague Spatial Bitmap (VSB-index) qui améliore la performance pour traiter les requêtes adressées à des EDS vagues. L'applicabilité de ces contributions est démontrée dans deux applications dans le domaine agricole, en créant des schémas conceptuels des EDS vagues, la transformation de ces schémas conceptuels en schémas logiques pour des EDS vagues, et le traitement efficace des requêtes sur des EDS vagues.
O data warehouse espacial (DWE) é um banco de dados multidimensional integrado e volumoso que armazena dados espaciais e dados convencionais. Já o processamento analítico-espacial online (SOLAP) permite consultar o DWE, tanto pela seleção de dados espaciais que satisfazem um relacionamento topológico, quanto pela agregação dos dados espaciais. Deste modo, DWE e SOLAP beneficiam o suporte a tomada de decisão. As aplicações de DWE e SOLAP abordam majoritarimente fenômenos representados por dados espaciais exatos, ou seja, que assumem localizações e fronteiras bem definidas. Contudo, tais aplicações negligenciam dados espaciais afetados por imperfeições, tais como a vagueza espacial, a qual interfere na identificação precisa de um objeto e de seus vizinhos. Um objeto espacial vago não tem sua fronteira ou seu interior precisamente definidos. Além disso, é composto por partes que certamente pertencem a ele e partes que possivelmente pertencem a ele. Apesar de inúmeros fenômenos do mundo real serem caracterizados pela vagueza espacial, na literatura consultada não se identificaram trabalhos que considerassem a vagueza espacial no projeto de DWE e nem para consultar o DWE. Tal limitação motivou a elaboração desta tese de doutorado, a qual introduz os conceitos de DWE vago e de SOLAP vago. Um DWE vago é um DWE que armazena dados espaciais vagos, enquanto que SOLAP vago provê os meios para consultar o DWE vago. Nesta tese, o projeto de DWE vago é abordado e as principais contribuições providas são: (i) o modelo conceitual VSCube que viabiliza a criação de um cubos de dados multidimensional para representar o esquema conceitual de um DWE vago; (ii) o modelo conceitual VSMultiDim que permite criar um diagrama para representar o esquema conceitual de um DWE vago; (iii) diretrizes para o projeto lógico do DWE vago e de suas restrições de integridade, e para estender a linguagem SQL visando processar as consultas de SOLAP vago no DWE vago; e (iv) o índice VSB-index que aprimora o desempenho do processamento de consultas no DWE vago. A aplicabilidade dessas contribuições é demonstrada em dois estudos de caso no domínio da agricultura, por meio da criação de esquemas conceituais de DWE vago, da transformação dos esquemas conceituais em esquemas lógicos de DWE vago, e do processamento de consultas envolvendo as regiões vagas do DWE vago.
Doctorat en Sciences de l'ingénieur et technologie
Location of the public defense: Universidade Federal de São Carlos, São Carlos, SP, Brazil.
info:eu-repo/semantics/nonPublished
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Dunkin, Ann Elizabeth. "Analysis and design of storage and retrieval systems for tote sized loads." Thesis, Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/25525.
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Vetencourt, Stull Rolando Jose. "Re-design warehouse plant layout for a food company." Online version, 2004. http://www.uwstout.edu/lib/thesis/2004/2004vetencourtr.pdf.
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Zerangue, Natalie Frances. "Modeling expertise in the design of warehousing and distribution systems." Thesis, Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/21737.
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Schilling, Benjamin Fritz. "Robotic vacuum cleaner design to mitigate slip errors in warehouses." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/114052.
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Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 83-84).
Warehouses are extremely dusty environments due to the concrete and cardboard dust generated. This is problematic in automated warehouses that use robots to move items from one location to another. If the robot slips, it can collide with other robots or lose track of where it is located. Currently, to reduce the amount of dust on the floor, warehouses use industrial scrubbers that users walk behind or ride. This requires manual labor and a regular scheduled maintenance plan that needs to be followed to mitigate the dust accumulation. Therefore, an industrial robotic vacuum cleaner that can continuously clean the warehouse floors is proposed. The five key parts to a vacuum are inlet duct, brush roller, filtration, storage, and suction. This thesis will discuss in detail the design and development of the filtration, storage, and suction of the robotic vacuums that were developed in this project. The thesis will go through design considerations and computational fluid dynamics that were conducted to validate and improve the design. Then, it will discuss the experimental results of the robotic vacuum cleaners.
by Benjamin Fritz Schilling.
M. Eng. in Advanced Manufacturing and Design
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Veronica, Ruiz Castro Carla. "CSTM: a conceptual spatiotemporal model for data warehouses." Universidade Federal de Pernambuco, 2010. https://repositorio.ufpe.br/handle/123456789/2209.
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Previous issue date: 2010Conselho Nacional de Desenvolvimento Científico e Tecnológico
Estudos abrangentes relacionados a data warehouse temporais e espaciais têm sido conduzidos. Data warehouse temporais permitem lidar com dados variáveis no tempo tanto em tabelas de fatos quanto em tabelas de dimensões. Uma ampla variedade de aplicações precisa capturar não só características espaciais, mas também temporais das entidades modeladas. Entretanto, estudos que unam essas duas áreas de pesquisa não têm sido suficientemente considerados. É neste contexto que o presente trabalho de dissertação está definido. Ele propõe um modelo conceitual para data warehouses espaço temporais. Este modelo permite aos usuários definir níveis, hierarquias e dimensões tanto com características espaciais como temporais. Como consequência disso, é possível representar atributos espaciais variáveis no tempo. Além disso, este trabalho define um conjunto de operadores espaço temporais que poderia ser útil na consulta de data warehouses espaço temporais. Diferentemente de propostas existentes, nossos operadores integram não só operadores multidimensionais e espaciais, mas também espaciais e temporais (i.e., espaço temporais) em uma única sintaxe. Um esquema taxonômico, o qual classifica os operadores propostos, também é definido. A importância da taxonomia proposta é que ajuda no desenvolvimento de tecnologia OLAP espaço temporal. Com o objetivo de automatizar a modelagem de esquemas espaço temporais, uma ferramenta CASE foi desenvolvida. Além de permitir a definição de esquemas conformes com o modelo conceitual proposto, esta ferramenta também permite a geração automática do esquema lógico correspondente usando uma abordagem objeto relacional. As ideias propostas são validadas com um estudo de caso na área meteorológica. O estudo apresenta uma aplicação prática do modelo conceitual espaço temporal e dos operadores espaço temporais apresentados neste trabalho
Books on the topic "Warehouses Design"
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Kimball, Ralph. The data warehouse toolkit: Practical techniques for building dimensional data warehouses. New York: John Wiley & Sons, 1996.
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Drury, Jolyon. Building and planning for industrial storage and distribution. 2nd ed. Amsterdam: Architectural Press, 2003.
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Ackerman, Kenneth B. Practical Handbook of Warehousing. Boston, MA: Springer US, 1997.
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Napolitano, Maida. The time, space & cost guide to better warehouse design: A hands-on guide to help you improve the design and operations of your warehouse or distribution center. New York, NY: Distribution Center Management, 1994.
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Napolitano, Maida. The time, space & cost guide to better warehouse design: A hands-on guide to help you improve the design and operations of your warehouse or distribution center. 2nd ed. New York: Distribution Center Management, 2003.
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Cable, Carole. Warehouses: Their archaeology, design, remodeling, and reuse--recent periodical literature, 1977-1987. Monticello, Ill., USA: Vance Bibliographies, 1988.
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Rajagopalan, K. Storage structures. Rotterdam: A.A. Balkema, 1990.
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Smekhov, A. A. Avtomatizirovannye sklady. 4th ed. Moskva: "Mashinostroenie", 1987.
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John, Dieltz, ed. Order fulfillment and across the dock concepts, design, and operations handbook. Boca Raton: St. Lucie Press, 2004.
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1962-, Venerable Michael, ed. Data warehouse design solutions. New York: Wiley, 1998.
Find full textBook chapters on the topic "Warehouses Design"
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Jarke, Matthias, Maurizio Lenzerini, Yannis Vassiliou, and Panos Vassiliadis. "Quality-Driven Data Warehouse Design." In Fundamentals of Data Warehouses, 165–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05153-5_8.
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Nassis, Vicky, R. Rajugan, Tharam S. Dillon, and Wenny Rahayu. "Conceptual Design of XML Document Warehouses." In Data Warehousing and Knowledge Discovery, 1–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30076-2_1.
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Zajac, Pawel. "Conceptual Design of a Cold Room." In The Energy Consumption in Refrigerated Warehouses, 71–99. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40898-9_5.
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Sakka, Amir, Sandro Bimonte, Lucile Sautot, Guy Camilleri, Pascale Zaraté, and Aurelien Besnard. "A Volunteer Design Methodology of Data Warehouses." In Conceptual Modeling, 286–300. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00847-5_21.
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Jarke, Matthias, Manfred A. Jeusfeld, Christoph Quix, and Panos Vassiliadis. "Architecture and quality in data warehouses." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 93–113. Cham: Springer International Publishing, 1998. http://dx.doi.org/10.1007/bfb0054221.
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Bortolini, Marco, Francesco Gabriele Galizia, Mauro Gamberi, Francesco Gualano, and Ludovica Diletta Naldi. "Non-conventional Warehouses: Comparison of the Handling Performances." In Sustainable Design and Manufacturing 2020, 193–203. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8131-1_18.
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Hamberg, Roelof, and Jacques Verriet. "The Falcon Project: Model-Based Design of Automated Warehouses." In Automation in Warehouse Development, 3–13. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-968-0_1.
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Eder, Johann, Christian Koncilia, and Tadeusz Morzy. "The COMET Metamodel for Temporal Data Warehouses." In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 83–99. Cham: Springer International Publishing, 2002. http://dx.doi.org/10.1007/3-540-47961-9_9.
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Oliveira, Rui, Fátima Rodrigues, Paulo Martins, and João Paulo Moura. "Dimensional Templates in Data Warehouses: Automating the Multidimensional Design of Data Warehouse Prototypes." In Enterprise Information Systems, 184–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01347-8_16.
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Jeusfeld, Manfred A., Christoph Quix, and Matthias Jarke. "Design and Analysis of Quality Information for Data Warehouses." In Conceptual Modeling – ER ’98, 349–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-540-49524-6_28.
Full textConference papers on the topic "Warehouses Design"
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Siciliano, Giulia, Yue Yu, and Johannes Fottner. "Synergy between Shuttles and Stacker Cranes in Dynamic Hybrid Pallet Warehouses: Control Strategies and Performance Evaluation." In 36th ECMS International Conference on Modelling and Simulation. ECMS, 2022. http://dx.doi.org/10.7148/2022-0143.
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This article considers two dynamic hybrid pallet warehouses obtained hybridizing a shuttle-based warehouse with stacker cranes. We begin by describing their design and characteristics. Afterwards, we explain the control algorithms that were developed for them. Next, we illustrate the modalities of the discrete event simulation study we ran to investigate their performance. In conclusion, we discuss the results in terms of throughput of the simulation study to individuate the field of application for the two layouts of dynamic hybrid pallet warehouses in comparison to stacker crane-based and shuttle-based warehouses.
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Mihova, Lilyana. "THE IMPACT OF SUSTAINABLE DEVELOPMENT ON WAREHOUSING." In 4th International Scientific Conference – EMAN 2020 – Economics and Management: How to Cope With Disrupted Times. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2020. http://dx.doi.org/10.31410/eman.2020.135.
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The sustainable development is very emerging topic in the last two decades. This global trend has implications for the development of warehouse systems and technologies and the purpose of this article is to reveal the impact of sustainable development on green logistics practices in warehouses and the formation of sustainable warehouse systems. For this purpose, a literature reviews of sustainable or “green” warehouse is made. Also, the impact of the warehouse on the environment during the stages of construction and exploitation is researched. Other important issues concern the practices and technologies used in the warehouse to reduce energy consumption and harmful emissions. Last but not least a review of the legislative measures and certification methods for the construction and design of sustainable warehouses is made. In conclusion the guidelines for the state of development of sustainable logistics practices in warehousing in Bulgaria are given.
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Rocheleau, David N., and Matthew M. Moore. "Design and Analysis of a Camera and Sensor Positioning Mechanism for ARIES: An Autonomous Mobile Robot." In ASME 1998 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/detc98/mech-5988.
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Abstract ARIES (Autonomous Robotic Inspection Experimental System) is a program for the Department of Energy (DOE) that was charged with the mission of surveying and inspecting drums containing low-level radioactive waste stored in warehouses at DOE facilities. This paper reports on the final development of the ARIES project, and focuses on the mechanical design and analysis of three mechanisms that position a camera and sensor package that sits atop a Cybermotion K3A mobile robotic platform. The ARIES project was executed through a joint effort of three parties: University of South Carolina (USC), Clemson University, and Cybermotion, Inc., of Salem, Virginia. The goal of the project was to develop an autonomous mobile robot that positions a data acquisition package (DAP) which surveys drums containing hazardous materials in Department of Energy (DOE) warehouses. The unique mechanical design of the positioning system is comprised of three distinct components: a lift mechanism, a fourbar mechanism, and a camera panning mechanism. The components are integrated in a manner that allows the DAP to be positioned from 0 to 16 feet off the ground while the robot maneuvers through aisles of drums in a warehouse. The three mechanisms, and the integration thereof, are reported in this paper.
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Di Tria, Francesco, Ezio Lefons, and Filippo Tangorra. "Design process for Big Data Warehouses." In 2014 International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2014. http://dx.doi.org/10.1109/dsaa.2014.7058120.
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Jarke, M., C. Quix, D. Calvanese, M. Lenzerini, E. Franconi, S. Ligoudistianos, P. Vassiliadis, and Y. Vassiliou. "Concept based design of data warehouses." In the 2000 ACM SIGMOD international conference. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/342009.336570.
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Vrdoljak, B., M. Banek, and S. Rizzi. "Automating conceptual design of Web warehouses." In ConTEL 2003 - 7th International Conference on Telecommunications. IEEE, 2003. http://dx.doi.org/10.1109/contel.2003.176958.
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Banek, M., Z. Skocir, and B. Vrdoljak. "Logical design of data warehouses from XML." In 2005 Proceedings of the 8th International Conference on Telecommunications. IEEE, 2005. http://dx.doi.org/10.1109/contel.2005.185875.
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Hachaichi, Yasser, and Jamel Feki. "Hierarchy integration in the design of data warehouses." In Annual International Academic Conference on Business Intelligence and Data Warehousing. Global Science and Technology Forum, 2010. http://dx.doi.org/10.5176/978-981-08-6308-1_66.
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Gou, Xue. "A Design of Intelligent Management System for Warehouses." In 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/iccia-17.2017.173.
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Hajihashemi, Sara, Reza Alizadeh, Janet K. Allen, and Farrokh Mistree. "Impact of Asset Management in a Green Supply Chain." In ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-70826.
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Abstract With increasing concerns about global warming caused by greenhouse gasses (GHGs), organizations have become more responsible for their operations. According to the U.S. Environmental Protection Agency (EPA), companies with a supply chain (SC) generate about 42% of GHGs in their transportation (30%) and inventory systems (12%), which makes mitigating climate change through a green supply chain (GSC) management a reasonable solution. To design a GSC, we model the SC as a customer and store network, with customers driving in cars to and from stores and the retailer resupplying the stores from a central warehouse. The number and location of stores are determined to find a low-cost and low emission configuration for the SC. The key findings are (1) SCs with more small stores generate less emission than ones with fewer large stores; (2) when minimizing the operating cost is more important than mitigating GHG emissions, fewer large stores are preferred than having more small stores; (3) a SC with two warehouses reduces the number of open stores in a large area such as Puerto Rico. Our contributions are (1) building a model of a GSC based on population data; (2) modeling a GSC in a two-echelon network which can be solved simultaneously using the k-median approach; (3) evaluating the effect of multiple warehouses on the overall GHGs emissions; (4) managing the incompleteness and inaccuracy of the data through implementing the compromise Decision Support Problem construct to identify satisficing solutions. The model mentioned earlier highlights the important parameters that impact the green GHG emissions reduction from a SC that describe in this paper. We also discuss how this approach can be employed for other design problems, including manufacturing and healthcare.
Reports on the topic "Warehouses Design"
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Lutz, Carsten. Reasoning about Entity Relationship Diagrams with Complex Attribute Dependencies. Aachen University of Technology, 2002. http://dx.doi.org/10.25368/2022.119.
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Entity Relationship (ER) diagrams are among the most popular formalisms for the support of database design [7, 12, 17, 6]. Their classical use in the (usually computer aided) database design process can roughly be described as follows: after evaluating the requirements of the application, the database designer constructs an ER schema, which represents the conceptual model of the new database. CASE tools can be used to automatically transform the ER schema into a relational database schema, which is then manually fine-tuned. During the last years, the initially rather simple ER formalisms has been extended by various means of expressivity to account for new, more complex application areas such as schema integration for data warehouses [12, 3, 13]. Designing a conceptual model with such enriched ER diagrams is a nontrivial task: there exist complex interactions between the various means of expressivity, which quite often result in unnoticed inconsistencies in the ER schemas and in implicit ramifications of the modeling that have not been intended by the designer. To address this problem, Description Logics (DLs) have been proposed and succesfully used as a tool for reasoning about ER diagrams and thereby detecting the aforementioned anomalies [5, 6, 8].
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Mudryj, Igor, and Igor Ivaneіko. The Use of Small Drilling Equipment in the Arrangement of Pile Foundations in Compressed Conditions. Intellectual Archive, September 2022. http://dx.doi.org/10.32370/ia_2022_09_11.
Full textAbstract:
The procedure for finding technological parameters for the installation of pile foundations with small-sized drilling rigs, when developing design and technological documentation in compressed construction conditions, is considered. Methodological approaches to the choice of technologies for the construction of pile foundations are shown, depending on the dimensions of the small-sized drilling machines used, the required area for their placement, storage areas, and auxiliary equipment. in compressed conditions of construction. The existing normative documents do not set out separate requirements for the development of projects for the execution of works in compressed construction conditions, these norms do not provide for the definition of rational erection schemes for the selected set of mechanization in the dimensions of a specific construction site, which is characterized by various restrictions and obstacles. The proposed requirements for the use of mechanization methods in the conditions of compacted buildings during the installation of pile foundations based on a preliminary analysis of the parameters of the construction site: engineering and geological condition of the site; internal brevity of the designed structure; external brevity of the construction site; dimensions of the driving car; sites for the location of additional equipment, warehouses, unloading areas. Taking into account practical experience in the development of work projects and the analysis of current regulatory documents, made it possible to establish the main requirements for the use of small-sized drilling rigs in densely built-up conditions.
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Liu, Bing, Ronald E. Jarnagin, Wei Jiang, and Krishnan Gowri. Technical Support Document: The Development of the Advanced Energy Design Guide for Small Warehouse and Self-Storage Buildings. Office of Scientific and Technical Information (OSTI), December 2007. http://dx.doi.org/10.2172/921429.
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