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Simulinve : um ambiente de simulação de inventário para centro de distribuição de peças / Simulinve : a simulation environment of inventory to a part distribution centerPontes, Heráclito Lopes Jaguaribe 15 May 2006 (has links)
Atualmente, as empresas buscam garantir disponibilidade de produto ao cliente final, com o menor nível de inventário possível. Isto ocorre devido a diversidade crescente no número de produtos e o elevado custo de oportunidade do capital. As ferramentas de simulação disponibilizam aos gestores melhores visões do negócio e melhores condições para a tomada de decisão. Em um Centro de Distribuição de Peças (CDP), para se alcançar um melhor desempenho no gerenciamento do inventário é importante poder contar com uma ferramenta capacitada para realizações de simulações de possíveis cenários. Este trabalho tem como objetivo desenvolver um ambiente de simulação do inventário de um CDP. O ambiente de simulação permite realizar simulações visando obter como resultados a previsão de demanda, a política de reposição das peças, o percentual de atendimento dos pedidos, os meses de inventário, a quantidade de scrap e a quantidade de peças para devolução. Para o desenvolvimento do ambiente de simulação utilizou-se de métodos de modelagem e linguagem de programação orientado a objeto. O ambiente de simulação foi submetido a experimentos com três cenários diferentes e os resultados confirmaram a qualidade do sistema de simulação proposto. / Nowadays companies are trying to become their product available to final client with the smallest possible level of inventory. The simulation tools offer to managers best views of business and best condition to decide. In a Part Distribution Center (PDC), to reach the best performance in the management of the inventory it is important to be able to count on a tool that is capable of accomplishments from simulation possible sceneries. The objective of this work is to develop a simulation environment of the inventory of a PDC. The simulation environment performs projections in order to get demand forecasts, the parts replenishment policy, the attendance percentage, the inventory months, scrap quantity and quantity part to devolution. To develop the simulation environment are used tools like modeling methods and programming object-oriented language. The simulation environment was submitted to experiments with three different sceneries and the results confirmed the quality of the simulation system proposed.
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[en] A MODEL FOR OPTIMAL LOCATION OF DISTRIBUTION CENTERS / [pt] MODELO PARA LOCALIZAÇÃO ÓTIMA DE CENTROS DE DISTRIBUIÇÃOCLAUDIO JOSE COUTINHO ARROMATE 10 July 2006 (has links)
[pt] As necessidadeS de ganhos de escala para diluir custos
fixos de produção, aliadas a grande segmentação e
criação
de novos mercados faz com que cada vez mais seja preciso
produzir em quantidades maiores e vender em quantidades
menores; Pressões para para redução de estoques, de
produtos acabados e insumos em todos os elos da cadeia;
Localização do centro produtor cada vez mais distante do
centro consumidor, em função de benefícios fiscais, de
infra-estrutura e respeito ao meio-ambiente, fazem do
conceito centro de distribuição um dos tópicos mais
importantes no gerenciamento da cadeia logística de
qualquer empresa, e matéria obrigatória na literatura
sobre as várias formas de implementação, e a viabilidade
econômica de tais alternativas como forma de agregar
valor
ao negócio.
Independente do modelo a ser adotado, é questão
relevante
a sua localização. E esta contempla variáveis como o
custo
de distribuição em função das distâncias ao centro
consumidor e centro produtor; custos do estoque e
manuseio
em função do giro previsto, custos fixos de operação
fabris e de armazém, além da necessidade de previsão e
dispersão da demanda do item a ser distribuído. Outras
variáveis que precisam ser contempladas na prática são
as
questões tributárias, disponibilidade / qualificação de
mão de obra, equipamentos de transporte e questões
mercadológicas envolvendo o produto e o consumidor a ser
atingido.
Escolheu-se uma técnica especifica e facilmente
executável
em softwares comerciais para cada classe de problemas:
Modelo de previsão de vendas - foi desenvolvido um
modelo
de regressão dinâmica e utilizado o software FORECAST
MASTER ; Algoritmo de caminho mais curto para cálculo do
custo de distribuição - foi implementado o Algoritmo de
Djkstra de caminho mais curto; Modelo para localização e
tamanho dos centros de distribuição - foi desenvolvido
um
modelo de programação inteira mista utilizando o
algoritmo
de Branch and Bound, implementando no software OSL.
Com o intuito de avaliar a performance frente a outras
técnicas existentes são vistos sucintamente técnicas de
alisamento exponencial (Holt-Winters), o método de Box e
Jenkins, com relação ao cálculo de distâncias, os
algoritmo de caminho mais curto de Fran Out, formulação
como problema de fluxo em redes - cálculo dofluxo de
custo
mínimo; Em relação ao modelo matemático de localização,
um
modelo de programação inteira alternativo que é a
utilização de plano de cortes.
Todas as técnicas foram aplicadas aos dados de uma
empresa
de bens de consumo de abrangência nacional, cuja
distribuição dá-se através de distribuidores de
distribuidores independentes que compram os produtos e
os
retiram nas fábricas produtoras, para posterior revenda
aos pontos de venda ao consumidor final, como
supermercados, lanchonetes, postos de gasolina, bares,
etc.
Este estudo serviu como ferramenta prática na tomada da
decisão da companhia de localizar seus centros de
distribuição. / [en] Gain of scale needsin order to decrease production fixed
costs, in addition with large segmentation and the
appearing of new markerts, makes more and more important
to produce in high quantities and on the other hand to
sell in small selling quantities. The inventory costs, and
inventory levels, of finished goods and raw materials in
the whole supply chain; the plants location more and more
far from the consumer´s center (due to tax benefits, infra-
structure and environment implications); makes the
distribuition center concept one of the most important
issues in the supply chain management of any company.
This is also a very important subject on the literature,
about the many ways of implementation, economic viability
of each alternative, and a way to add value to the
business. No matter the model is going to be used, it is
very a impportant question, the location. And this is
envolves distribuition costs, inventory costs, warehousing
and handling costs, operations fixed and variable costs,
and further the demand forecast of each SKU.
Another variables that need to be considered in practice
are the legal implications, mão de obra, Real State,
transportation equipments and merchandising issues,
envolving the product and the target consumer.
Such a specific and software easy run technique was chosen
for each class of problems: Sales Forecast Model - A
Dinamic regression model was developed and the software
Forecast Master was used. Shortest path algorithm.
Distribuition Center location and size model - A mixed
integer program was developed using Branch-and-Bound
technique, implemented with OSL software.
In order to evaluate the algorithms performance in
comparison with other avaible techniques, will be
mentioned another models: Demand Forecast - The
Exponential Smoothing technique (holt-Winters), and the
Box and Jenkins method. About the distances between
points - Fan out shortest path algorithm, and the
formulation of the shortest path problem stated as a
minimum cost flow algoritm. About the Distribuition center
location and size model, Such a alternative Integer
program approach was tried: the cutting planes.
All the tecniques were applied using a countywide bens de
consumo company database, whose distribuition is made
through independents distributors that buy and pick the
products directly in the production plant, and after
selling to the final consumer or point of sales in general.
This study was used as a tool in practice in the company
Distribuition center location decision making.
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Distribution Centers in GraphsDesormeaux, Wyatt J., Haynes, Teresa W., Hedetniemi, Stephen T., Moore, Christian 10 July 2018 (has links)
For a graph G=(V,E) and a set S⊆V, the boundary of S is the set of vertices in V∖S that have a neighbor in S. A non-empty set S⊆V is a distribution center if for every vertex v in the boundary of S, v is adjacent to a vertex in S, say u, where u has at least as many neighbors in S as v has in V∖S. The distribution center number of a graph G is the minimum cardinality of a distribution center of G. We introduce distribution centers as graph models for supply–demand type distribution. We determine the distribution center number for selected families of graphs and give bounds on the distribution center number for general graphs. Although not necessarily true for general graphs, we show that for trees the domination number and the maximum degree are upper bounds on the distribution center number.
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Determining the Optimal Aisle-Width for Order Picking in Distribution CentersWallace-Finney, Sheena R. 16 August 2011 (has links)
No description available.
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Determining optimal staffing levels for the picking and packing operations in a distribution centerBadurdeen, Fathima Fazleena January 2002 (has links)
No description available.
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Designing Order Picking Systems for Distribution CentersParikh, Pratik J. 06 October 2006 (has links)
This research addresses decisions involved in the design of an order picking system in a distribution center. A distribution center (DC) in a logistics system is responsible for obtaining materials from different suppliers and assembling (or sorting) them to fulfill a number of different customer orders. Order picking, which is a key activity in a DC, refers to the operation through which items are retrieved from storage locations to fulfill customer orders.
Several decisions are involved when designing an order picking system (OPS). Some of these decisions include the identification of the picking-area layout, configuration of the storage system, and determination of the storage policy, picking method, picking strategy, material handling system, pick-assist technology, etc. For a given set of these parameters, the best design depends on the objective function (e.g., maximizing throughout, minimizing cost, etc.) being optimized. The overall goal of this research is to develop a set of analytical models for OPS design. The idea is to help an OPS designer to identify the best performing alternatives out of a large number of possible alternatives. Such models will complement experienced-based or simulation-based approaches, with the goal of improving the efficiency and efficacy of the design process.
In this dissertation we focus on the following two key OPS design issues: configuration of the storage system and selection between batch and zone order picking strategies. Several factors that affect these decisions are identified in this dissertation; a common factor amongst these being picker blocking. We first develop models to estimate picker blocking (Contribution 1) and use the picker blocking estimates in addressing the two OPS design issues, presented as Contributions 2 and 3.
In Contribution 1 we develop analytical models using discrete-time Markov chains to estimate pick-face blocking in wide-aisle OPSs. Pick-face blocking refers to the blocking experienced by a picker at a pick-face when another picker is already picking at that pick-face. We observe that for the case when pickers may pick only one item at a pick-face, similar to in-the-aisle blocking, pick-face blocking first increases with an increase in pick-density and then decreases. Moreover, pick-face blocking increases with an increase in the number of pickers and pick to walk time ratio, while it decreases with an increase in the number of pick-faces. For the case when pickers may pick multiple items at a pick-face, pick-face blocking increases monotonically with an increase in the pick-density. These blocking estimates are used in addressing the two OPS design issues, which are presented as Contributions 2 and 3.
In Contribution 2 we address the issue of configuring the storage system for order picking. A storage system, typically comprised of racks, is used to store pallet-loads of various stock keeping units (SKU) --- a SKU is a unique identifier of products or items that are stored in a DC. The design question we address is related to identifying the optimal height (i.e., number of storage levels), and thus length, of a one-pallet-deep storage system. We develop a cost-based optimization model in which the number of storage levels is the decision variable and satisfying system throughput is the constraint. The objective of the model is to minimize the system cost, which is comprised of the cost of labor and space. To estimate the cost of labor we first develop a travel-time model for a person-aboard storage/retrieval (S/R) machine performing Tchebyshev travel as it travels in the aisle. Then, using this travel-time model we estimate the throughput of each picker, which helps us estimate the number of pickers required to satisfy the system throughput for a given number of storage levels. An estimation of the cost of space is also modeled to complete the total cost model. Results from an experimental study suggest that a low (in height) and long (in length) storage system tends to be optimal for situations where there is a relatively low number of storage locations and a relatively high throughput requirement; this is in contrast with common industry perception of the higher the better. The primary reason for this contrast is because the industry does not consider picker blocking and vertical travel of the S/R machine. On the other hand, results from the same optimization model suggest that a manual OPS should, in almost all situations, employ a high (in height) and short (in length) storage system; a result that is consistent with industry practice. This consistency is expected as picker blocking and vertical travel, ignored in industry, are not a factor in a manual OPS.
In Contribution 3 we address the issue of selecting between batch and zone picking strategies. A picking strategy defines the manner in which the pickers navigate the picking aisles of a storage area to pick the required items. Our aim is to help the designer in identifying the least expensive picking strategy to be employed that meets the system throughput requirements. Consequently, we develop a cost model to estimate the system cost of a picking system that employs either a batch or a zone picking strategy. System cost includes the cost of pickers, equipment, imbalance, sorting system, and packers. Although all elements are modeled, we highlight the development of models to estimate the cost of imbalance and sorting system. Imbalance cost refers to the cost of fulfilling the left-over items (in customer orders) due to workload-imbalance amongst pickers. To estimate the imbalance cost we develop order batching models, the solving of which helps in identifying the number of items unfulfilled. We also develop a comprehensive cost model to estimate the cost of an automated sorting system. To demonstrate the use of our models we present an illustrative example that compares a sort-while-pick batch picking system with a simultaneous zone picking system.
To summarize, the overall goal of our research is to develop a set of analytical models to help the designer in designing order picking systems in a distribution center. In this research we focused on two key design issues and addressed them through analytical approaches. Our future research will focus on addressing other design issues and incorporating them in a decision support system. / Ph. D.
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Authentication and Identification of Sensor Nodes to Avoid Unauthorized Access in Sensor Networks / Autentisering och identifiering av sensornoder för att undvika obehörig åtkomst i sensornätverkHenriksson, Michael January 2020 (has links)
With the increasing popularity of Internet of Things (IoT), network connected devices and sensors, to easier collect data is security an aspect that must not be forgotten. When sensitive data, such as personal or private data, is sent over the network without protection can it easier be obtained by anyone who want to get their hands on it. This risk increases with the value of the data sent and an increase in security should therefore follow this value. Based on this is it therefore important to look at the security aspects of a sensor network to find ways to easy integrate security such as authentication. This to make sure that the only devices and users accessing or sending data on the network is authorized and not malicious devices. This thesis focuses on the authentication and identification of the devices joining the network to make sure that only trusted devices would be able to join. The protocol in focus is ZigBee but the proposed solution can be integrated with any protocol and utilizes a Key Distribution Center (KDC) together with an authentication method based on the Challenge Handshake Authentication Protocol (CHAP) to authenticate new devices before they are allowed into the network. This solution is secure and relatively simple which makes it easy to integrate with any sensor network. / Med en ökad popularitet av att koppla upp sensorer och apparater mot ett nät- verk för att enklare kunna samla in data är säkerhet en aspekt som inte får glömmas bort. När känslig data, så som personlig eller privat data, skickas över nätverket oskyddat kan någon som vill komma åt datan lättare få tag på den. Denna risk ökar med värdet av datan som skickas och en ökningen av säkerhet bör darav följa ökning av värdet på datan. Utav denna anledning är det viktigt att se över säkerheten i sensornätverk och finna lösningar som lätt kan integreras med ett sensornätverk. Detta för att säkerhetsställa att endast de snesornoder som har auktoritet kan gå med i, samt skicka data på nätverket och därmed undvika oönskad åtkomst. Denna avhandling fukuserar på autentisering och identifiering av de noder som ska anslutas till nätverket för att säkerhetsställa att endast pålitliga och auktoriserade noder blir insläppta. Det protokoll som är i fokus i denna avhandling är ZigBee men den föreslagna lösningen kan även integreras med andra protokoll. Den föreslagna lösning- en använder sig även av ett Key Distribution Center (KDC) samt en autentiseringsmetod som baseras på Challenge Handshake Authentication Protocol (CHAP) för att authentisera nya noder innan de blir insläppta i nätverket. Denna lösning är säker och relativt enkel vilket gör det enkelt att integrera med all typer av sensornätverk.
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Logistika obchodních řetězců / Logistics of retail chainsKrálová, Veronika January 2010 (has links)
This diploma thesis aims to review and assess a current state of Czech retail market with fast-moving consumer goods and to analyze a logistic base of leading retail chains doing business in the Czech Republic. A reader can learn about development of retail in the last few years, but also about prediction of the future trends. Based on the theoretical background regarding retail and logistics, the analysis of particular leading companies is made. Moreover, possible future efficiency improvements of companies' process which could lead to better market position are considered. The result of the thesis is the clear picture of well operating retail chain, its logistics and a flow of the goods into the retail market as a whole.
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物流中心撿貨資訊系統之策略研究及實作分析 / The Design and Case Study of Picking Information System in Distribution Center辜靜玟, Ku Ching-wen Unknown Date (has links)
物流中心是為因應現代商業環境中,『少量、多樣、多頻次』的需求型態
,而設立的貨品儲存及配送中心,具有倉儲、流通加工及配送等等整合性
的功能,在管理上不僅要求訂單處理的效率,更注重客戶服務水準的提高
以及總成本的降低等的管理課題。本研究基於這樣的管理需求,針對物流
中心的撿貨作業,研究撿貨資訊系統設計的方法及其內容,希望透過資訊
系統的協助,可以改善撿貨作業管理的決策品質,並進而提升撿貨作業之
整體效率。本研究共分為『撿貨資訊系統之設計』以及『實作分析』等兩
部分。在撿貨資訊系統設計部分,本研究透過撿貨作業管理決策問題的分
析,整理出在發展撿貨作業管理的決策方案時,有哪些限制因素,以及哪
些可控制的因素。並且定義出可協助決策制定的撿貨資訊系統需要提供哪
些資訊,具備哪些功能。此外,針對撿貨作業決策問題的特性,本研究提
出發展撿貨作業管理決策方案的操作模式,並以這個操作模式作為撿貨資
訊系設計的基礎,配合決策支援系統之概念,提出一個可以幫助決策制定
的撿貨資訊系統的設計架構。在實作分析方面,本研究根據所提出設計架
構,實際以一個案廠商的撿貨作業為例,一方面分析其訂單的成長狀況,
成長型態,另一方面則依據其目前的撿貨作業進行方式,建立一個雛型系
統。首先,由訂單分析知道,該個案廠商所面臨的壓力為訂單張數成長的
問題,其餘如每張訂單項目數的成長,則較不明顯,尚不造成撿貨作業效
率的阻礙。另外,透過雛型系統的操作分析,本研究提供個案廠商在人力
配置方面的建議,指出增加人力對效率改進有限,並且發現,該個案廠商
目前的撿作業進行方式的瓶頸主要在撿取貨物完畢後,包裝作業的進行上
,為配合該案廠商所制定的客戶服務政策,本研究建議管理者可以從增加
人力之外的方案著手,尋求訂單張數不斷成長的狀況之下,撿貨作業效率
改進的方案。
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A Study on the Global Logistic Developed Strategy for Kaohsiung HarborChieh, Wang-Chao 15 January 2001 (has links)
At present, enterprises adopt global production and marketing strategy to reinforce their competitive advantages. In addition, they tend to search suitable places for establishing global logistic distribution centers. An international harbor with good geography, cost advantage, and complete facilities, will be attractive for those enterprises to set global logistic distribution centers.
The Kaohsiung Harbor is the third largest container transport in the world. However, the global logistics is operated at the beginning stage. To match the developing plans of the government's global logistics, this exploratory study is designed to develop a strategy for the global logistic distribution center in Kaohsiung Harbor with Delphi Method and Analytic Hierarchy Process.
Through literature review and two rounds Delphi Questionnaire, we find five evaluating criteria (operating efficiency, administrative efficiency, tax incentive, infrastructure and logistic professions) for positioning the Kaohsiung Harbor in global logistics. Five major functions including transit shipment, container consolidation, distribution, simple processing and warehousing are inducted. Three alternatives for global logistic distribution center are centralized, decentralized, or mixed type.
Major findings of this study are as follows:
1.Centralized global logistic distribution center is the best type for Kaohsiung Harbor.
2.The priority of the major functions for a centralized global logistic distribution center in orders is simple processing, distribution, warehousing, container consolidation, and transit shipment.
3.The criteria for evaluating centralized global logistic distribution center in orders are administrative efficiency, operating efficiency, tax incentive, logistic professions and infrastructure.
According to the results, researcher offers a strategy for developing global logistic distribution center in Kaohsiung Harbor.
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