14 resultados para Train scheduling

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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Tutkimuksen päätavoite on arvioida, ovatko neljä ohjelmistovaihtoehtoa riittäviä tuotannon aikataulutuksen työkaluja ja mikä työkaluista sopii toimeksiantajayritykselle. Alatavoitteena on kuvata tuotannon aikataulutuksen nyky- ja tahtotila prosessimallinnuksen avulla, selvittää työkalun käyttäjätarpeet ja määritellä priorisoidut valintakriteerit työkalulle.Tutkimuksen teoriaosuudessa tutkitaan tuotannon aikataulutuksen logiikkaa ja haasteita. Työssä tarkastellaan aikataulutusohjelmiston valintaa rinnakkain prosessinmallinnuksen kanssa. Aikataulutusohjelmistovaihtoehdot ja metodit käyttäjätarpeiden selvittämiseksi käydään läpi. Empiriaosuudessa selvitetään tutkimuksen suhde toimeksiantajayrityksen strategiaan. Käyttäjätarpeet selvitetään haastattelujen avulla jaanalysoidaan QFD matriisin avulla. Toimeksiantajayrityksen tuotannon aikataulutuksen nyky- ja tahtotilaprosessit mallinnetaan, jotta ohjelmistojen sopivuutta, aikataulutusprosessia tukevana työkaluna voidaan arvioida.Tutkimustuloksena ovatpriorisoidut valintakriteerit aikataulutustyökalulle eli käyttäjätarpeista johdetut tärkeimmät toiminnalliset ominaisuudet, järjestelmätoimittaja-arvio sekä suositukset jatkotoimenpiteistä ja lisätutkimuksesta.

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In modem hitec industry Advanced Planning and Scheduling (APS) systems provide the basis for e-business solutions towards the suppliers and the customers. One objective of this thesis was to clarify the modem supply chain management with the APS systems and especially concentrate on the area of Collaborative Planning. In order Advanced Planning and Scheduling systems to be complete and usable, user interfaces are needed. Current Visual Basic user interfaces have faced many complaints and arguments from the users as well as from the development team. This thesis is trying to analyze the reasons and causes for the encountered problems and also provide ways to overcome them. The decision has been made to build the new user interfaces to be Web-enabled. Therefore another objective of this thesis was to research and find suitable technologies for building the Web-based user interfaces for Advanced Planning and Scheduling Systems in Nokia Demand/Supply Planning business area. Comparison between the most suitable technologies is made. Usability issues of Web-enabled user interfaces are also covered. The empirical part of the thesis includes design and implementation of a Web-based user interface with the chosen technology for a particular APS module that enables Collaborative Planning with suppliers.

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The amount of installed wind power has been growing exponentially during the past ten years. As wind turbines have become a significant source of electrical energy, the interactions between the turbines and the electric power network need to be studied more thoroughly than before. Especially, the behavior of the turbines in fault situations is of prime importance; simply disconnecting all wind turbines from the network during a voltage drop is no longer acceptable, since this would contribute to a total network collapse. These requirements have been a contributor to the increased role of simulations in the study and design of the electric drive train of a wind turbine. When planning a wind power investment, the selection of the site and the turbine are crucial for the economic feasibility of the installation. Economic feasibility, on the other hand, is the factor that determines whether or not investment in wind power will continue, contributing to green electricity production and reduction of emissions. In the selection of the installation site and the turbine (siting and site matching), the properties of the electric drive train of the planned turbine have so far been generally not been taken into account. Additionally, although the loss minimization of some of the individual components of the drive train has been studied, the drive train as a whole has received less attention. Furthermore, as a wind turbine will typically operate at a power level lower than the nominal most of the time, efficiency analysis in the nominal operating point is not sufficient. This doctoral dissertation attempts to combine the two aforementioned areas of interest by studying the applicability of time domain simulations in the analysis of the economicfeasibility of a wind turbine. The utilization of a general-purpose time domain simulator, otherwise applied to the study of network interactions and control systems, in the economic analysis of the wind energy conversion system is studied. The main benefits of the simulation-based method over traditional methods based on analytic calculation of losses include the ability to reuse and recombine existing models, the ability to analyze interactions between the components and subsystems in the electric drive train (something which is impossible when considering different subsystems as independent blocks, as is commonly done in theanalytical calculation of efficiencies), the ability to analyze in a rather straightforward manner the effect of selections other than physical components, for example control algorithms, and the ability to verify assumptions of the effects of a particular design change on the efficiency of the whole system. Based on the work, it can be concluded that differences between two configurations can be seen in the economic performance with only minor modifications to the simulation models used in the network interaction and control method study. This eliminates the need ofdeveloping analytic expressions for losses and enables the study of the system as a whole instead of modeling it as series connection of independent blocks with no lossinterdependencies. Three example cases (site matching, component selection, control principle selection) are provided to illustrate the usage of the approach and analyze its performance.

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The objective of this thesis is to research Manufacturing Planning and Control (MPC) system and Master Scheduling (MS) in a manufacturing firm. The study is conducted at Ensto Finland Corporation, which operates on a field of electrical systems and supplies. The paper consists of theoretical and empirical parts. The empirical part is based on weekly operating at Ensto and includes inter-firm material analysis, learning and meetings. Master Scheduling is an important module of an MPC system, since it is beneficial on transforming strategic production plans based on demand forecasting into operational schedules. Furthermore, capacity planning tools can remarkably contribute to production planning: by Rough-Cut Capacity Planning (RCCP) tool, a MS plan can be critically analyzed in terms of available key resources in real manufacturing environment. Currently, there are remarkable inefficiencies when it comes to Ensto’s practices: the system is not able to take into consideration seasonal demand and react on market changes on time; This can cause significant lost sales. However, these inefficiencies could be eliminated through the appropriate utilization of MS and RCCP tools. To utilize MS and RCCP tools in Ensto’s production environment, further testing in real production environment is required. Moreover, data accuracy, appropriate commitment to adapting and learning the new tools, and continuous developing of functions closely related to MS, such as sales forecasting, need to be ensured.

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This work contains a series of studies on the optimization of three real-world scheduling problems, school timetabling, sports scheduling and staff scheduling. These challenging problems are solved to customer satisfaction using the proposed PEAST algorithm. The customer satisfaction refers to the fact that implementations of the algorithm are in industry use. The PEAST algorithm is a product of long-term research and development. The first version of it was introduced in 1998. This thesis is a result of a five-year development of the algorithm. One of the most valuable characteristics of the algorithm has proven to be the ability to solve a wide range of scheduling problems. It is likely that it can be tuned to tackle also a range of other combinatorial problems. The algorithm uses features from numerous different metaheuristics which is the main reason for its success. In addition, the implementation of the algorithm is fast enough for real-world use.

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The maintenance of electric distribution network is a topical question for distribution system operators because of increasing significance of failure costs. In this dissertation the maintenance practices of the distribution system operators are analyzed and a theory for scheduling maintenance activities and reinvestment of distribution components is created. The scheduling is based on the deterioration of components and the increasing failure rates due to aging. The dynamic programming algorithm is used as a solving method to maintenance problem which is caused by the increasing failure rates of the network. The other impacts of network maintenance like environmental and regulation reasons are not included to the scope of this thesis. Further the tree trimming of the corridors and the major disturbance of the network are not included to the problem optimized in this thesis. For optimizing, four dynamic programming models are presented and the models are tested. Programming is made in VBA-language to the computer. For testing two different kinds of test networks are used. Because electric distribution system operators want to operate with bigger component groups, optimal timing for component groups is also analyzed. A maintenance software package is created to apply the presented theories in practice. An overview of the program is presented.

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Formal methods provide a means of reasoning about computer programs in order to prove correctness criteria. One subtype of formal methods is based on the weakest precondition predicate transformer semantics and uses guarded commands as the basic modelling construct. Examples of such formalisms are Action Systems and Event-B. Guarded commands can intuitively be understood as actions that may be triggered when an associated guard condition holds. Guarded commands whose guards hold are nondeterministically chosen for execution, but no further control flow is present by default. Such a modelling approach is convenient for proving correctness, and the Refinement Calculus allows for a stepwise development method. It also has a parallel interpretation facilitating development of concurrent software, and it is suitable for describing event-driven scenarios. However, for many application areas, the execution paradigm traditionally used comprises more explicit control flow, which constitutes an obstacle for using the above mentioned formal methods. In this thesis, we study how guarded command based modelling approaches can be conveniently and efficiently scheduled in different scenarios. We first focus on the modelling of trust for transactions in a social networking setting. Due to the event-based nature of the scenario, the use of guarded commands turns out to be relatively straightforward. We continue by studying modelling of concurrent software, with particular focus on compute-intensive scenarios. We go from theoretical considerations to the feasibility of implementation by evaluating the performance and scalability of executing a case study model in parallel using automatic scheduling performed by a dedicated scheduler. Finally, we propose a more explicit and non-centralised approach in which the flow of each task is controlled by a schedule of its own. The schedules are expressed in a dedicated scheduling language, and patterns assist the developer in proving correctness of the scheduled model with respect to the original one.

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With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.

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The objective of this project was to introduce a new software product to pulp industry, a new market for case company. An optimization based scheduling tool has been developed to allow pulp operations to better control their production processes and improve both production efficiency and stability. Both the work here and earlier research indicates that there is a potential for savings around 1-5%. All the supporting data is available today coming from distributed control systems, data historians and other existing sources. The pulp mill model together with the scheduler, allows what-if analyses of the impacts and timely feasibility of various external actions such as planned maintenance of any particular mill operation. The visibility gained from the model proves also to be a real benefit. The aim is to satisfy demand and gain extra profit, while achieving the required customer service level. Research effort has been put both in understanding the minimum features needed to satisfy the scheduling requirements in the industry and the overall existence of the market. A qualitative study was constructed to both identify competitive situation and the requirements vs. gaps on the market. It becomes clear that there is no such system on the marketplace today and also that there is room to improve target market overall process efficiency through such planning tool. This thesis also provides better overall understanding of the different processes in this particular industry for the case company.

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Operational excellence of individual tramp shipping companies is important in today’s market, where competition is intense, freight revenues are modest and capital costs high due to global financial crisis, and tighter regulatory framework is generating additional costs and challenges to the industry. This thesis concentrates on tramp shipping, where a tramp operator in a form of an individual case company, specialized in short-sea shipping activities in the Baltic Sea region, is searching ways to map their current fleet operations and better understand potential ways to improve the overall routing and scheduling decisions. The research problem is related to tramp fleet planning where several cargoes are carried on board at the same time, which are here systematically referred to as part cargoes. The purpose is to determine the pivotal dimensions and characteristics of these part cargo operations in tramp shipping, and offer both the individual case company and wider research community better understanding of potential risks and benefits related to utilization of part cargo operations. A mixed method research approach is utilized in this research, as the objectives are related to complex, real-life business practices in the field of supply chain management and more specifically, maritime logistics. A quantitative analysis of different voyage scenarios is executed, including alternative voyage legs with varying cost structure and customer involvement. An on-line-based questionnaire designed and prepared by case company’s decision group again provides desired data of predominant attitudes and views of most important industrial customers regarding the part cargo-related operations and potential future utilization of this business model. The results gained from these quantitative methods are complied with qualitative data collection tools, along with suitable secondary data sources. Based on results and logical analysis of different data sources, a framework for characterizing the different aspects of part cargo operations is developed, utilizing both existing research and empirical investigation of the phenomenon. As conclusions, part cargoes have the ability to be part of viable fleet operations, and even increase flexibility among the fleet to a certain extent. Naturally, several hinderers for this development is recognized as well, such as potential issues with information gathering and sharing, inefficient port activities, and increased transit times.

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With the development of electronic devices, more and more mobile clients are connected to the Internet and they generate massive data every day. We live in an age of “Big Data”, and every day we generate hundreds of million magnitude data. By analyzing the data and making prediction, we can carry out better development plan. Unfortunately, traditional computation framework cannot meet the demand, so the Hadoop would be put forward. First the paper introduces the background and development status of Hadoop, compares the MapReduce in Hadoop 1.0 and YARN in Hadoop 2.0, and analyzes the advantages and disadvantages of them. Because the resource management module is the core role of YARN, so next the paper would research about the resource allocation module including the resource management, resource allocation algorithm, resource preemption model and the whole resource scheduling process from applying resource to finishing allocation. Also it would introduce the FIFO Scheduler, Capacity Scheduler, and Fair Scheduler and compare them. The main work has been done in this paper is researching and analyzing the Dominant Resource Fair algorithm of YARN, putting forward a maximum resource utilization algorithm based on Dominant Resource Fair algorithm. The paper also provides a suggestion to improve the unreasonable facts in resource preemption model. Emphasizing “fairness” during resource allocation is the core concept of Dominant Resource Fair algorithm of YARM. Because the cluster is multiple users and multiple resources, so the user’s resource request is multiple too. The DRF algorithm would divide the user’s resources into dominant resource and normal resource. For a user, the dominant resource is the one whose share is highest among all the request resources, others are normal resource. The DRF algorithm requires the dominant resource share of each user being equal. But for these cases where different users’ dominant resource amount differs greatly, emphasizing “fairness” is not suitable and can’t promote the resource utilization of the cluster. By analyzing these cases, this thesis puts forward a new allocation algorithm based on DRF. The new algorithm takes the “fairness” into consideration but not the main principle. Maximizing the resource utilization is the main principle and goal of the new algorithm. According to comparing the result of the DRF and new algorithm based on DRF, we found that the new algorithm has more high resource utilization than DRF. The last part of the thesis is to install the environment of YARN and use the Scheduler Load Simulator (SLS) to simulate the cluster environment.