Thesis deals with the topic of computational scheduling of production with dynamic reconfigurations and maintenance. The problem is formally defined by a mathematical model named Resource Constrained Project Scheduling Problem which was extended by dynamic reconfiguration and maintenance. Number of different schedule generation algorithms were proposed based on this model. Also methods of solution optimization based on genetic algorithms were described. The typology of production orders of which different task types are created was described in the experimental part. The result of the experiments is clear recommendation of scheduling algorithm for given task type. For the conclusion, thesis deals with the case study of choice of suitable solution for specific production companies.

[pt] O uso de ferramentas de otimização destaca-se como um relevante diferencial para as empresas no que tange a otimização de processos e melhoria de sistemas e performances. Neste contexto, a busca por modelos de programação simples e eficazes para a resolução dos problemas contribuem para adaptação de modelos existentes a fim de atender a esta crescente demanda. Atualmente, o setor de transporte ferroviário busca otimização de seus processos com o objetivo de aumentar sua competitividade e eficiência frente ao transporte realizado por rodovia. Este estudo, focado na melhoria de processos do setor ferroviário, tem como objetivo realizar o planejamento da distribuição de materiais de manutenção em uma malha ferroviária com o menor custo operacional viável. Para isto, o problema é modelado como um problema de programação inteira mista e busca tornar o processo mais eficiente, com redução de desperdícios e otimização dos recursos. Os resultados obtidos foram comparados ao processo atual de distribuição a fim de medir os ganhos em processo e em redução de custos e recursos. O modelo se mostrou eficiente em tempo e qualidade de solução quando comparado com o atual, apresentando uma redução de 20 por cento a 26 por cento nos custos totais de distribuição, variando de acordo com o almoxarifado analisado. Além disso, o estudo também mostrou uma redução no custo de distribuição para todas as localidades testadas, sendo que, quanto menor a distância destes locais ao almoxarifado, maior a redução dos custos logísticos relacionados. / [en] The use of optimization tools highlights a relevant differential to companies in terms of improving processes, systems and performance. In this context, the search for simple and effective programming models for problem solving contributes to the adaptation of existing models to attend this increasing demand. Currently, the railway transport seeks to optimize its processes in order to increase its competitiveness and efficiency when compared to road transport. This study, focused on improving processes in the railway, aims to realize the distribution planning of maintenance materials in a railway network with the lowest feasible operating cost. For this, the problem is modeled as a mixedinteger programming problem and it aims to make the process more efficient, with waste reduction and resource optimization. The obtained results were compared to the current distribution process in order to measure gains in process and in reducing costs and resources. The model proved to be efficient in both time and solution quality when compared to the current one, presenting a reduction of 20 percent to 26 percent in the distribution costs, depending on the analyzed warehouses. In addition, the study has also indicated a reduction in the distribution costs in all tested locations and the distance among those locations and their warehouses leads to a greater reduction in the logistic costs.

[pt] No sistema elétrico de potência podem ocorrer falhas que resultarão na interrupção do fornecimento de energia para os consumidores conectados a esses sistemas. Uma concessionária de energia elétrica deve prestar aos seus clientes um serviço que seja confiável e de boa qualidade. Por isso, o planejamento seguro e eficiente se faz necessário para obter a confiabilidade do sistema elétrico de acordo com as exigências estabelecidas pela agência reguladora do setor, onde caso não sejam observadas pela distribuidora de energia são cabíveis de punições monetárias. O desempenho de um sistema pode ser observado com base no histórico de interrupções, por meio dos indicadores de continuidade. A baixa flexibilidade operativa de subestações aliada à configuração das redes reduz a confiabilidade dos sistemas, causando prejuízos às empresas e aos consumidores por estarem vulneráveis e sofrerem interrupções de energia. O presente estudo é essencial, pois visa identificar métodos e análises apuradas que indiquem os pontos prioritários para manutenções nas redes elétricas. Dessa forma, a dissertação apresenta uma metodologia que identifica os equipamentos e trechos associados aos pontos críticos e de maior impacto em uma rede de distribuição. A partir daí é possível direcionar os serviços de manutenção dos circuitos para os trechos de maior impacto nos indicadores de continuidade de uma determinada região e otimizar o orçamento correspondente. A ferramenta usada para analisar os indicadores é uma matriz de risco, onde os eixos representam probabilidade de ocorrência (reincidência) e impacto corporativo (índice de continuidade) de modo a capturar mais precisamente os pontos para atuações de manutenção prioritária. Desenhada a estrutura da matriz, os fatores de risco identificados são avaliados qualitativamente, em termos de probabilidade e impacto, e posicionado na matriz, indicando seu estado: eminente, crítico, alto, médio e baixo. São analisados dois sistemas de distribuição reais da classe de 13,8 kV, com o objetivo de demonstrar a capacidade da metodologia de encontrar as soluções condizentes do ponto de vista técnico e econômico. Os resultados apontam uma redução dos indicadores de continuidade, colaborando assim na eficaz gestão do sistema elétrico e na mitigação dos prejuízos econômicos associados às interrupções de energia. / [en] Faults can occur in the electrical power system which will result in interruption of the power supply to consumers connected to these systems. An electric power utility should provide its customers with a service that is reliable and of good quality. Therefore, safe and efficient planning is necessary to obtain the reliability of the electrical system according to the requirements established by the regulatory agency of the sector. In case they are not observed by the electrical energy distributor, monetary penalties are possibly applied. The performance of a system can be observed based on the history of interruptions, through the continuity indicators. The low operational flexibility of substations, coupled with the network configurations, reduces the reliability of the systems causing monetary damage to companies and consumers, due to their vulnerability to interruptions of energy. The present study is essential because it aims to identify methods and analysis that detect the priority points for maintenance in the electric networks. In this way, the dissertation presents a methodology that identifies the equipment and sections associated to the critical points of greater impact in a distribution network. Thus, it is possible to direct the maintenance services of the circuits to the segments of greater impact in the indices of continuity of a certain region and to optimize the corresponding budget. The basic tool used to analyze the indices is a risk matrix, where the axes represent the probability of occurrence (recurrence) and company impact (continuity indices), in order to capture more precisely the points for priority maintenance actions. When the matrix structure is established, the identified risk factors are qualitatively assessed in terms of probability and impact, and positioned in the matrix, indicating their state: eminent, critical, high, medium, and low. Two real distribution systems of the 13.8 kV class are analyzed to demonstrate the ability of the proposed methodology to find the appropriate solutions from a technical and economic point of view. The results point to a reduction in continuity indicators, thus contributing to the effective management of the power electric system and mitigating the economic losses associated with power outages.

Change from a regulated to deregulated structure means that, the centralized maintenance system is not valid any more. In the surveyed published literature, there is not a single model which incorporates all maintenance cost components to analyze the effect of different maintenance strategies for generator companies (GENCOs). The work enclosed in this thesis demonstrates that there is a considerable requirement for accurately modelling cost components of the maintenance model, to be used in maintenance scheduling for deregulated power system, in order to attain a superior schedule with major financial and operational impact. This research investigates and models most cost factors that affect the maintenance activities of the deregulated GENCOs, and demonstrates the utilization of the developed cost models in maintenance scheduling. It also presents the data gathering process for the developed maintenance cost model. A generator maintenance scheduling model that considers direct and indirect maintenance costs, opportunity costs (i.e. loss of customer goodwill), effective maintenance strategies, failures, and interruptions is developed. A Genetic Algorithm (GA) based approach is employed to achieve maintenance schedules to various generators maintenance scenarios. An Analytical Hierarchy Process (AHP) approach is proposed for modelling customer goodwill. The maintenance model was redeveloped under the Reliability Centred Maintenance (RCM) strategy to analyze the effect of a maintenance strategy on maintenance costs. Case studies are presented to demonstrate the utilisation of the developed models.The investigation shows that the market prices, opportunity costs and maintenance strategy have an effect on the final maintenance schedule. The research demonstrates that the cost components are critical factors to achieve an effective maintenance schedule, and they must be considered and carefully modelled in order to reflect more realistic situation for maintenance scheduling of generator units in deregulation environment.

Thesis (MEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: The demand for rail travel has increased over the years. As a result, it is becoming mandatory for railway industries to maintain very high availability of their assets to ensure that service levels are high. Railway industries require both their infrastructure and rolling stock assets maintained efficiently to sustain reliability. There has been on-going research on how maintenance can be carried out in a cost effective manner. However, the majority of this research has been done for infrastructure and the rolling stock maintenance has not been properly covered. The purpose of this research is to contribute to the maintenance sector of rolling stock for railway industries by developing a decision support model for rolling stock based on reliability and cost. The model is developed as an optimization problem of a system containing several components dependent on each other with different reliability characteristics. In this model, a mixed integer nonlinear problem is developed and solved using an exact method and metaheuristics methods. The Metrorail facility in Cape Town was chosen as a case study. Failure history and cost data were gathered from the facility and the information was applied to the model developed. The case study was investigated and different results were achieved using both exact and metaheuristics methods. The final result from the study is an optimal maintenance schedule based on reliability and cost. The developed model serves as a practical tool railway companies can adopt to schedule rolling stock maintenance to achieve a high level of reliability and at the same time maintaining minimum cost expenditure. / AFRIKAANSE OPSOMMING: Die vraag na spoorvervoer het oor die jare toegeneem. Dus het dit belangrik geword dat die spoorweg se bates hoogs toeganklik moet wees om te verseker dat die vlak van dienslewering hoog bly. Die spoorweg industrie besef dat hulle infrastruktuur, lokomotiewe, waens ens. effektief in stand gehou moet word sodat dit betroubaar kan wees. Navorsing word nog steeds gedoen oor hoe instandhouding op ’n koste-effektiewe wyse gedoen kan word. Die meeste van hierdie navorsing gaan egter oor infrastruktuur en instandhouding word nie ordentlik gedek nie. Die doel met hierdie navorsing is om by te dra tot die instandhoudingsektor van die spoorweg deur om ’n besluit-ondersteunende model vir lokomotiewe, waens, ens wat op betroubaarheid en koste gegrond is, te ontwikkel. Die model is ontwikkel as ’n optimasie probleem van ’n sisteem wat verskillende komponente wat van mekaar afhanklik is maar oor verskillende betroubaarheidskenmerke beskik, inluit. In hierdie model word ’n gemengde, heeltal nie-lineêre probleem ontwikkel en met ’n eksakte metode en metaheuristiese metodes opgelos. Die Metrorail fasiliteit in Kaapstad is vir die gevalle studie gekies. Die geskiedenis van mislukkings en koste data is by die fasiliteit versamel en die inligting is op die model wat ontwikkel is, toegepas. Die gevalle studie is ondersoek, en verskillende resultate is met eksakte en metaheuristiese metodes bereik. Die finale uitkomste van die studie is ’n optimale instandhoudingskedule wat op betroubaarheid en koste gegrond is. Die model wat ontwikkel is dien as ’n praktiese instrument wat spoormaatskappye kan gebruik om die instandhouding van lokomotiewe, waens ens. te reël sodat ’n hoë vlak van betroubaarheid bereik kan word en kostes terselfdertyd tot ’n minimum beperk kan word.

Effective maintenance planning is essential and important in any organisation that is responsible for procuring and managing complex assets. In the marine shipping industry maintenance planning is very significant due to its complexity and the obligations on shipping organisations to comply with certain regulations and requirements. Moreover, improper planning can reduce the ship's availability, which may in turn, be reflected in the revenue of the company. Another issue that requires attention in this field is the cost of maintenance, since improper or inadequate planning could result in breakdowns that could increase the cost of maintenance.This research aims to identify the key factors that affect ship maintenance planning and to provide a framework that can help the decision maker to identify and choose optimum decisions regarding ship maintenance. The research is divided into four stages in order to achieve its objectives and to address the research problem.The first stage is the review of the literature to identify the need for maintenance and to select the key factors that affect maintenance planning. The findings indicate that: maintenance scheduling, selection of maintenance strategy, ship construction, crew compensation, and shipyard selection are the most important factors.The second stage is to evaluate maintenance performance measurements for the marine shipping industry by conducting case study and interviews with professionals involved in the mercantile industry. Semi-structured interviews were conducted with six senior staff experts from three different organisations. The results show that: dry docking scheduling, maintenance costs and budgets, customer satisfaction, employees' satisfaction, classification requirements, and the ship's maintenance requirements are the main factors that have great influence on maintenance planning.The third stage is to develop new methodology to measure the maintenance performance in the marine shipping organisation which is the ship maintenance performance measurement (SMPM) framework. The developed method was validated to assist managers in making the right decisions in ship maintenance planning. The framework was developed based on ten thematic criteria that can be used as indicators for potential organisation growth, i.e., maintenance strategy; dry docking scheduling; budget and costs; the ship's equipment; customer satisfaction; employees; health, safety and environment; learning and growth; classification requirements; and the ship's operation and demands requirements. Interviews were conducted with key personnel from the Kuwait Oil Tanker Company (KOTC) to validate the framework.The fourth stage demonstrates that an optimised schedule for the dry docking of ships for routine maintenance has been constructed. This is accomplished on the basis of one measured criterion, dry docking scheduling, by using an integer programming model to maximise the ship's availability within the company fleet. The model is defined by three constraints: the maintenance window, maintenance completion, and the ship's limit. The model was validated using data from KOTC, and the results depict an optimum solution for maintenance scheduling, maximising the ship's availability to 100% and not less than 92%.

Change from a regulated to deregulated structure means that, the centralized maintenance system is not valid any more. In the surveyed published literature, there is not a single model which incorporates all maintenance cost components to analyze the effect of different maintenance strategies for generator companies (GENCOs). The work enclosed in this thesis demonstrates that there is a considerable requirement for accurately modelling cost components of the maintenance model, to be used in maintenance scheduling for deregulated power system, in order to attain a superior schedule with major financial and operational impact. This research investigates and models most cost factors that affect the maintenance activities of the deregulated GENCOs, and demonstrates the utilization of the developed cost models in maintenance scheduling. It also presents the data gathering process for the developed maintenance cost model. A generator maintenance scheduling model that considers direct and indirect maintenance costs, opportunity costs (i.e. loss of customer goodwill), effective maintenance strategies, failures, and interruptions is developed. A Genetic Algorithm (GA) based approach is employed to achieve maintenance schedules to various generators maintenance scenarios. An Analytical Hierarchy Process (AHP) approach is proposed for modelling customer goodwill. The maintenance model was redeveloped under the Reliability Centred Maintenance (RCM) strategy to analyze the effect of a maintenance strategy on maintenance costs. Case studies are presented to demonstrate the utilisation of the developed models.The investigation shows that the market prices, opportunity costs and maintenance strategy have an effect on the final maintenance schedule. The research demonstrates that the cost components are critical factors to achieve an effective maintenance schedule, and they must be considered and carefully modelled in order to reflect more realistic situation for maintenance scheduling of generator units in deregulation environment.

No description available.

The maintenance schedule of generators in power plants needs to match the electricity demand and needs to ensure the reliability of the power plant at a minimum cost of operation. In this study, a comparison is made between the modified generator maintenance scheduling model and the classic generator maintenance scheduling model using the reliability objective functions. Both models are applied to a 21-unit test system, and the results show that the modified generator maintenance scheduling model gives better and more reliable solutions than the regular generator maintenance scheduling model. The better results of the modified generator maintenance scheduling model are due the modified and additional constraints in the modified generator maintenance scheduling model. Due to the reliable results of the modified generator maintenance scheduling model, a robust model is formulated using the economic cost objective function. The model includes modified crew and maintenance window constraints, with some additional constraints such as the relationship constraints among the variables. To illustrate the robustness of the formulated GMS model, the maintenance of the Arnot power plant in South Africa is scheduled with open-loop and closed-loop controllers. Both controllers satisfy all the constraints but the closed-loop results are better than the open-loop results. AFRIKAANS : Die onderhoudskedule vir kragopwekkers (OSK) in kragstasies moet kan voorsien in die vraag na elektrisiteit en moet die betroubaarheid van die kragstasie teen ’n minimum operasiekoste verseker. In hierdie studie word die betroubaarheidsdoelwitfunksie gebruik om ’n gewysigde onderhoudskeduleringsmodel vir kragopwekkers te vergelyk met die konvensionele onderhoudskeduleringsmodel. Beide modelle word toegepas op 'n 21-eenheid-toetsstelsel, en die resultate toon dat die gewysigde model ’n beter en meer betroubare oplossing bied as die konvensionele model. Die beter resultate van die gewysigde model is die gevolg van die gewysigde en bykomende beperkings in die gewysigde model. As gevolg van die betroubare resultate van die gewysigde onderhoudskeduleringsmodel word die koste-ekonomie-doelwitfunksie gebruik om ’n robuuste model te formuleer. Die model sluit gewysigde bemanning- en onderhoudvensterbeperkings in, met ’n paar bykomende beperkings soos die verhoudingsbeperkings tussen die veranderlikes. Om die robuustheid van die geformuleerde OSK-model te illustreer word die instandhouding van die Arnot kragstasie in Suid-Afrika geskeduleer met oop- en geslotelus-beheerders. Beide beheerders voldoen aan al die beperkinge, maar die geslotelusresultate is beter as die ooplusresultate. / Dissertation (MSc)--University of Pretoria, 2011. / Electrical, Electronic and Computer Engineering / Unrestricted

A growing use of sensors on the electric grid has opened the door to new methods of asset management: Distribution System Operators are now looking into conditionbased maintenance, as opposed to the traditional corrective or time-based methods. As an emerging field, the methodology must be constructed from the ground, with the little data available. The focus is put on cross-linked polyethylene medium voltage overhead lines (XLPE MVOHL)asthe asset to manage, and the aim of this work is to study under which conditions the use of sensors to improve maintenance scheduling on those lines is economically profitable. Solving this problem starts with a necessary review of key ageing mechanisms of XLPE MV overhead lines, followed by the identification of sensors which can monitor the quantities behind these mechanisms. Statistical models for the lifetime of electrical assets and economic models for the analysis of investments are also described. From this preliminary study, a condition-based maintenance methodology was devised using the concept of Health Index to gather data from multiple types of sensors into one unique indicator. Using existing literature, this health index is used to dynamically estimate the failure rate of the line. This failure rate is the key to condition-based maintenance scheduling: maintenance operations are triggered when the failure rate reaches a threshold. Selecting one ageing mechanism- electrical stress-, and one type of sensorpartial discharge inductive sensors-, a Python simulation was built (and is shared at the end of this thesis) allowing to compare the cost of predictive maintenance to the cost of corrective maintenance over several decades, with the key parameters clearly identified and analysed. Beyond the methodology in itself, the main result of the work is that the use of sensors is economically profitable in most of the studied conditions. This project also reveals the strong influence of some parameters on this profitability: condition monitoring is particularly justified for short-lived assets, with a narrow distribution of failures. The failure rate threshold must be set carefully as it has a major impact on the analysis: setting it too high leads to an unprofitable scenario. / Den ökande användningen av sensorer i elnätet har öppnat dörren för nya metoder för förvaltning av tillgångar: Distributionsnätsoperatörer tittar nu på tillståndsbaserat underhåll, i motsats till de traditionella korrigerande eller tidsbaserade metoderna. Eftersom det rör sig om ett nytt område måste metoden byggas upp från grunden, med de få data som finns tillgängliga. Fokus ligger på luftledningar av tvärbanden polyeten med medelhög spänning (XLPE MV OHL) som den tillgång som ska förvaltas, och syftet med detta arbete är att undersöka under vilka förhållanden det är ekonomiskt lönsamt att använda sensorer för att förbättra underhållsplaneringen på dessa ledningar. För att lösa detta problem börjar man med en nödvändig genomgång av de viktigaste åldringsmekanismerna för XLPE MV luftledningar, följt av identifiering av sensorer som kan övervaka de kvantiteter som ligger bakom dessa mekanismer. Statistiska modeller för livslängden för elektriska tillgångar och ekonomiska modeller för analys av investeringar beskrivs också. Utifrån denna preliminära studie utarbetades en metod för tillståndsbaserat underhåll med hjälp av begreppet hälsoindex för att samla data från flera olika typer av sensorer till en unik indikator. Med hjälp av befintlig litteratur används detta hälsoindex för att dynamiskt uppskatta felfrekvensen för ledningen. Denna felfrekvens är nyckeln till en tillståndsbaserad underhållsplanering: underhålls åtgärder utlöses när felfrekvensen når ett tröskelvärde. Genom att välja en åldringsmekanism- elektrisk belastning- och en typ av sensor- induktiva sensorer med partiell urladdning- byggdes en Python-simulering (som delas i slutet av denna avhandling) som gör det möjligt att jämföra kostnaden för förebyggande underhåll med kostnaden för korrigerande underhåll under flera decennier, med de viktigaste parametrarna tydligt identifierade och analyserade. Utöver själva metoden är det viktigaste resultatet av arbetet att användningen av sensorer är ekonomiskt lönsam under de flesta av de studerade förhållandena. Projektet visar också att vissa parametrar har ett starkt inflytande på denna lönsamhet: tillståndskontroll är särskilt motiverat för tillgångar med kort livslängd och en snäv fördelning av fel. Tröskelvärdet för felfrekvensen måste sättas med omsorg eftersom det har stor inverkan på analysen: om det sätts för högt leder det till ett olönsamt scenario.