940 resultados para service level deviation


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¿Se pueden utilizar las habilidades, las técnicas y los principios de la dirección estratégica en el diseño y ejecución de la programación docente de una asignatura? Esta es la pregunta que nos planteamos al diseñar la asignatura Dirección Estratégica de las Tecnologías de la Información perteneciente al Máster Universitario en Ingeniería Informática de la Universidad de Alicante. Estas técnicas las aplicaremos a aspectos clave de la innovación educativa: contrato pedagógico, objetivos, evaluación, trabajo en equipo y comunicación oral. Algunas de las propuestas innovadoras, que tienen el doble objetivo de ser un instrumento de la asignatura pero al mismo tiempo recoger aspectos de dirección y de mejora continua, son el SLA (“Service Level Agreement”) de aprendizaje, las actas de aprendizaje, el análisis de tendencias en las TI y el espacio para la creatividad. Tras dos cursos académicos de ajuste de la propuesta docente, en el curso 2014-2015 hemos analizado el nivel de satisfacción de los estudiantes con la misma y la autoevaluación crítica de los profesores que la han impartido. Los resultados han sido muy satisfactorios, con comentarios del estilo “ha sido una experiencia de aprendizaje efectivo”. Los estudiantes agradecen que los profesores prediquemos con el ejemplo. Nos hace más humanos y más creíbles.

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Over the past decade, several experienced Operational Researchers have advanced the view that the theoretical aspects of model building have raced ahead of the ability of people to use them. Consequently, the impact of Operational Research on commercial organisations and the public sector is limited, and many systems fail to achieve their anticipated benefits in full. The primary objective of this study is to examine a complex interactive Stock Control system, and identify the reasons for the differences between the theoretical expectations and the operational performance. The methodology used is to hypothesise all the possible factors which could cause a divergence between theory and practice, and to evaluate numerically the effect each of these factors has on two main control indices - Service Level and Average Stock Value. Both analytical and empirical methods are used, and simulation is employed extensively. The factors are divided into two main categories for analysis - theoretical imperfections in the model, and the usage of the system by Buyers. No evidence could be found in the literature of any previous attempts to place the differences between theory and practice in a system in quantitative perspective nor, more specifically, to study the effects of Buyer/computer interaction in a Stock Control system. The study reveals that, in general, the human factors influencing performance are of a much higher order of magnitude than the theoretical factors, thus providing objective evidence to support the original premise. The most important finding is that, by judicious intervention into an automatic stock control algorithm, it is possible for Buyers to produce results which not only attain but surpass the algorithmic predictions. However, the complexity and behavioural recalcitrance of these systems are such that an innately numerate, enquiring type of Buyer needs to be inducted to realise the performance potential of the overall man/computer system.

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The thesis deals with the background, development and description of a mathematical stock control methodology for use within an oil and chemical blending company, where demand and replenishment lead-times are generally non-stationary. The stock control model proper relies on, as input, adaptive forecasts of demand determined for an economical forecast/replenishment period precalculated on an individual stock-item basis. The control procedure is principally that of the continuous review, reorder level type, where the reorder level and reorder quantity 'float', that is, each changes in accordance with changes in demand. Two versions of the Methodology are presented; a cost minimisation version and a service level version. Realising the importance of demand forecasts, four recognised variations of the Trigg and Leach adaptive forecasting routine are examined. A fifth variation, developed, is proposed as part of the stock control methodology. The results of testing the cost minimisation version of the Methodology with historical data, by means of a computerised simulation, are presented together with a description of the simulation used. The performance of the Methodology is in addition compared favourably to a rule-of-thumb approach considered by the Company as an interim solution for reducing stack levels. The contribution of the work to the field of scientific stock control is felt to be significant for the following reasons:- (I) The Methodology is designed specifically for use with non-stationary demand and for this reason alone appears to be unique. (2) The Methodology is unique in its approach and the cost-minimisation version is shown to work successfully with the demand data presented. (3) The Methodology and the thesis as a whole fill an important gap between complex mathematical stock control theory and practical application. A brief description of a computerised order processing/stock monitoring system, designed and implemented as a pre-requisite for the Methodology's practical operation, is presented as an appendix.

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A special inventory problem is presented: aircraft spares that are repaired and returned to spares, called rotable inventory. Rotable inventory is not consumed so does not change in the medium term, but is rotated through operational, maintenance and stock phases. The objective for inventory performance is fleet Service Level (SL), which effects aircraft dispatch performance. A model is proposed where the fleet SL drives combined stock levels such that cost is optimized. By holding greater numbers of lower-cost items and holding lower levels of more expensive items, it is possible to achieve substantial cost savings while maintaining performance. This approach is shown to be an advance over the current literature and is tested with case data, with conclusive results.

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This paper explores demand and production management challenges in the food processing industry. The goal is to identify the main production planning constraints and secondly to explore how each of these constraints affects company’s performance in terms of costs and customer service level. A single case study methodology was preferred since it enabled the collection of in-depth data. Findings suggest that product shelf life, carcass utilization and production lead time are the main constraints affecting supply chain efficiency and hence, a single planning approach is not appropriate when different products have different technological and processing characteristics.

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Purpose – The purpose of this research is to develop a holistic approach to maximize the customer service level while minimizing the logistics cost by using an integrated multiple criteria decision making (MCDM) method for the contemporary transshipment problem. Unlike the prevalent optimization techniques, this paper proposes an integrated approach which considers both quantitative and qualitative factors in order to maximize the benefits of service deliverers and customers under uncertain environments. Design/methodology/approach – This paper proposes a fuzzy-based integer linear programming model, based on the existing literature and validated with an example case. The model integrates the developed fuzzy modification of the analytic hierarchy process (FAHP), and solves the multi-criteria transshipment problem. Findings – This paper provides several novel insights about how to transform a company from a cost-based model to a service-dominated model by using an integrated MCDM method. It suggests that the contemporary customer-driven supply chain remains and increases its competitiveness from two aspects: optimizing the cost and providing the best service simultaneously. Research limitations/implications – This research used one illustrative industry case to exemplify the developed method. Considering the generalization of the research findings and the complexity of the transshipment service network, more cases across multiple industries are necessary to further enhance the validity of the research output. Practical implications – The paper includes implications for the evaluation and selection of transshipment service suppliers, the construction of optimal transshipment network as well as managing the network. Originality/value – The major advantages of this generic approach are that both quantitative and qualitative factors under fuzzy environment are considered simultaneously and also the viewpoints of service deliverers and customers are focused. Therefore, it is believed that it is useful and applicable for the transshipment service network design.

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Despite the importance of information and communication technology (ICT) in the management of transport and logistics systems, there is a shortage of studies in the road freight haulage sector. This paper is aimed at filling this void through an exploratory survey on ICT adoption and the influencing factors carried out in the Italian road transport market. The paper provides a review of the previous research on this topic that allows the identification of research gaps that have been addressed through a questionnaire survey. The findings provide evidence of a passive stance on ICT usage characterised by the adoption of isolated applications. The financial risk associated with technology investment and human resources are the main barriers to ICT adoption, while the improvement of service level and the reliability of transport operations emerge as stimulating factors. The results suggest that the potential benefits of technology have not been fully exploited and a risk-sensitive stance on ICT is evident preventing the full incorporation of ICT into business processes.

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The enormous potential of cloud computing for improved and cost-effective service has generated unprecedented interest in its adoption. However, a potential cloud user faces numerous risks regarding service requirements, cost implications of failure and uncertainty about cloud providers' ability to meet service level agreements. These risks hinder the adoption of cloud. We extend the work on goal-oriented requirements engineering (GORE) and obstacles for informing the adoption process. We argue that obstacles prioritisation and their resolution is core to mitigating risks in the adoption process. We propose a novel systematic method for prioritising obstacles and their resolution tactics using Analytical Hierarchy Process (AHP). We provide an example to demonstrate the applicability and effectiveness of the approach. To assess the AHP choice of the resolution tactics we support the method by stability and sensitivity analysis. Copyright 2014 ACM.

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A fejlett társadalmak egészségügyi szolgáltató rendszerei napjainkban kettős kihívással néznek szembe: miközben a társadalom a szolgáltatási színvonal emelkedését, a hibák számának a csökkenését várja el, addig a költségvetési terhek miatt a költségcsökkentés is feltétlenül szükséges. Ez a kihívás nagyságában összevethető azzal, amellyel az USA autóipara nézett szembe az 1970-es évektől. A megoldást az autóipar esetében a konkurens „lean” menedzsment elvek és eszközök megértése és alkalmazása jelentette. A tanulmány arra keresi a választ, hogy vajon lehetséges-e ennek a megoldásnak az alkalmazása az egészségügy esetében is. A cikk az egészségügy problémájának bemutatása után tárgyalja a lean menedzsment kialakulását és hogy milyen módon került köztudatba. A tanulmány második felében a szakirodalomban fellelhető, a témával kapcsolatos tapasztalatokat foglalja össze, majd levonja a következtetéseket. = In developed societies healthcare service systems are facing double challenge; society expects service level to rise and the number of mistakes to drop, but at the same time, because of the overloaded budgets, cutting cost is also absolutely necessary. This challenge compares to the one the US automotive industry was facing in the 1970-s. In case of the automotive industry the solution was the comprehension and application of the principles and the tools of lean management. This study aims to answer the question whether it is possible to apply this solution also in the case of the healthcare system. The article first introduces the problems in the healthcare system, than describes the formation of lean management concept and its wide spread. The second half of the study summarizes the available knowledge in the literature and drives conclusions.

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The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

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Component-based Software Engineering (CBSE) and Service-Oriented Architecture (SOA) became popular ways to develop software over the last years. During the life-cycle of a software system, several components and services can be developed, evolved and replaced. In production environments, the replacement of core components, such as databases, is often a risky and delicate operation, where several factors and stakeholders should be considered. Service Level Agreement (SLA), according to ITILv3’s official glossary, is “an agreement between an IT service provider and a customer. The agreement consists on a set of measurable constraints that a service provider must guarantee to its customers.”. In practical terms, SLA is a document that a service provider delivers to its consumers with minimum quality of service (QoS) metrics.This work is intended to assesses and improve the use of SLAs to guide the transitioning process of databases on production environments. In particular, in this work we propose SLA-Based Guidelines/Process to support migrations from a relational database management system (RDBMS) to a NoSQL one. Our study is validated by case studies.

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The substantial increase in the number of applications offered through the computer networks, as well as in the volume of traffic forwarded through the network, have hampered to assure adequate service level to users. The Quality of Service (QoS) offer, honoring specified parameters in Service Level Agreements (SLA), established between the service providers and their clients, composes a traditional and extensive computer networks’ research area. Several schemes proposals for the provision of QoS were presented in the last three decades, but the acting scope of these proposals is always limited due to some factors, including the limited development of the network hardware and software, generally belonging to a single manufacturer. The advent of Software Defined Networking (SDN), along with the maturation of its main materialization, the OpenFlow protocol, allowed the decoupling between network hardware and software, through an architecture which provides a control plane and a data plane. This eases the computer networks scenario, allowing that new abstractions are applied in the hardware composing the data plane, through the development of new software pieces which are executed in the control plane. This dissertation investigates the QoS offer through the use and extension of the SDN architecture. Based on the proposal of two new modules, one to perform the data plane monitoring, SDNMon, and the second, MP-ROUTING, developed to determine the use of multiple paths in the forwarding of data referring to a flow, we demonstrated in this work that some QoS metrics specified in the SLAs, such as bandwidth, can be honored. Both modules were implemented and evaluated through a prototype. The evaluation results referring to several aspects of both proposed modules are presented in this dissertation, showing the obtained accuracy of the monitoring module SDNMon and the QoS gains due to the utilization of multiple paths defined by the MP-Routing, when forwarding data flow through the SDN.

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Winner of a best paper award.

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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.