Process plants come with a wide variety of engineering challenges. Each process has uniqueoperating conditions that require careful operation and maintenance programs to keep the process equipment in a condition that is safe for operation. A pilot-scale plant was built in Luleå to demonstrate the possibility of carbon dioxide removal from blast furnace gas usingthe Sorption Enhanced Water Gas Shift (SEWGS) technology. One of the challenges facingthe SEWGS pilot plant was the lack of a maintenance plan which was the motivation for this thesis. The aim of this thesis was to create a maintenance plan for the SEWGS pilot plant. Studying the process conditions of the pilot plant was the starting point since an understanding of the unique operating conditions was necessary for creating a maintenance plan for the pilot plant’s equipment. The Reliability-centered maintenance (RCM) method was chosen to create the maintenance plan. The study began with determining the objectives and contents of the analysis. The next step was a functional failure analysis in the form of a Failure Mode and Effect Criticality Analysis (FMECA) covering all the equipment in the plant. Afterwards the failure consequences were assessed based on a criticality assessment matrix to determine which equipment necessitate the performance of maintenance activities. The maintenance plan was created based upon the criticality of the equipment and the selected maintenance activities were based on the recommendations of manufacturers. The failure analysis found that the blast furnace gas compressor is the most critical for the process. The boiler and superheater have been found to be highly critical due to the dangerous safety consequences of their failure. In addition, all pressure safety valves have been found to be highly critical due to the hidden nature of their failure. The maintenance plan addresses these critical items and other less critical items while some non-critical items have been removed from the plan due to the negligible consequences of their failure.

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.

El sector textil y confecciones es uno de los sectores con mayores expectativas de crecimiento sostenible de la industria y uno de los que mayor competencia acumula con otros países del sector internacional. Este sector abarca diferentes tipos de procesos, que van desde tratamiento de fibras, hilatura, tejido y confección. El presente análisis recae sobre la baja disponibilidad que presenta los equipos en el proceso de teñido. Este proceso se mide a partir de los reprocesos que existen debido a que se ejecuta mantenimientos correctivos, el cual afecta la producción en el teñido de telas. Asimismo, se logra evaluar el tiempo promedio entre fallas (MTBF) y el tiempo promedio de reparación (MTTR), lo que indica la variabilidad por debajo del objetivo esperado por la organización. Por otro lado, en el tercer capítulo se desarrolla le propuesta de mejora a partir del desarrollo del estado del arte del primer capítulo. Para ello se propone la metodología da seguir de acuerdo con una combinación de RCM y TPM. Bajo esta metodología se desarrolla diferentes actividades y estrategias que permitirán detectar equipos críticos e implementar planes de mantenimiento preventivo mecánico y eléctrico. Además, se incluye como parte de este sistema la implementación de un mantenimiento basado en condición (predictivo) y autónomo. Finalmente, el tercer capítulo finaliza con el soporte de la metodología 5 ‘’S’’ y la evaluación económica a partir de la estructura de costos que tiene prevista el proyecto. Finalmente, en el capítulo cuatro se presenta la validación de la propuesta de mejora a partir de la validación de los resultados en el software Arena. Ello permite concluir que los indicadores MTTR y MTBF ha logrado alcanzar los objetivos presentados en la propuesta. / The textile and garment sector is one of the sectors with the highest expectations of sustainable growth in the industry and one of the sectors with the highest competition with other countries in the international sector. This sector covers different types of processes, ranging from fiber treatment, spinning, weaving and confection. The present analysis falls on the low availability that presents the equipment in the process of dyeing. This process is measured from the reprocesses that exist due to the execution of corrective maintenance, which affects the production of fabric dyeing. Likewise, it is possible to evaluate the average time between failures (MTBF) and the average repair time (MTTR), which indicates the variability below the target expected by the organization. On the other hand, in the third chapter the improvement proposal is developed from the development of the state of art of the first chapter. For this, the methodology to be followed is proposed according to a combination of RCM and TPM. Under this methodology, different activities and strategies are developed to detect critical equipment and implement mechanical and electrical preventive maintenance plans. In addition, the implementation of a maintenance based on (predictive) and autonomous condition is included as part of this system. Finally, the third chapter ends with the support of the 5 '' S '' methodology and the economic evaluation based on the cost structure planned by the project. Finally, chapter four presents the validation of the improvement proposal based on the validation of the results in the Arena software. This allows concluding that the MTTR and MTBF indicators have achieved the objectives presented in the proposal. / Tesis

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.

<p>Maximum asset performance is one of the major goals for electric power system managers. To reach this goal minimal life cycle cost and maintenance optimization become crucial while meeting demands from customers and regulators. One of the fundamental objectives is therefore to relate maintenance and reliability in an efficiently and effectively way, which is the aim of several maintenance methods such as the Reliability Centered Maintenance method (RCM). Furthermore, this necessitates the determination of the optimal balance between preventive and corrective maintenance to obtain the lowest total cost.</p><p>This thesis proposes methods for defining the importance of individual components in a network with respect to total interruption cost. This is a first step in obtaining an optimal maintenance solution. Since the methods consider several customer nodes simultaneously, they are especially suitable for network structures that serve many purposes/customers e.g. transmission and distribution networks with more than one load point. The major results are three component reliability importance indices, which are applied in two case studies. The first case study is based on a network in the Stockholm area. The second case study is performed for one overhead line system in the rural parts of Kristinehamn. The application studies demonstrate that the indices are possible to implement for existing electrical networks and that they can be used for maintenance prioritization. Consequently these indices constitute a first step in the overall objective of a maintenance optimization method.</p><p>The computations of the indices are performed both with analytical and simulation based techniques. Furthermore, the indices can be used to calculate the component contribution to the total system interruption cost. The approach developed for the importance indices can be utilized in any multi-state network that can be measured with one performance indicator.</p>

Maximum asset performance is one of the major goals for electric power distribution system operators (DSOs). To reach this goal minimal life cycle cost and maintenance optimization become crucial while meeting demands from customers and regulators. One of the fundamental objectives is therefore to relate maintenance and reliability in an efficient and effective way. Furthermore, this necessitates the determination of the optimal balance between pre¬ventive and corrective maintenance, which is the main problem addressed in the thesis. The balance between preventive and corrective maintenance is approached as a multiobjective optimization problem, with the customer interruption costs on one hand and the maintenance budget of the DSO on the other. Solutions are obtained with meta-heuristics, developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The methods deliver a Pareto border, a set of several solutions, which the operator can choose between, depending on preferences. The optimization is built on component reliability importance indices, developed specifically for power systems. One vital aspect of the indices is that they work with several supply and load points simultaneously, addressing the multistate-reliability of power systems. For the computation of the indices both analytical and simulation based techniques are used. The indices constitute the connection between component reliability performance and system performance and so enable the maintenance optimization. The developed methods have been tested and improved in two case studies, based on real systems and data, proving the methods’ usefulness and showing that they are ready to be applied to power distribution systems. It is in addition noted that the methods could, with some modifications, be applied to other types of infrastructures. However, in order to perform the optimization, a reliability model of the studied power system is required, as well as estimates on effects of maintenance actions (changes in failure rate) and their related costs. Given this, a generally decreased level of total maintenance cost and a better system reliability performance can be given to the DSO and customers respectively. This is achieved by focusing the preventive maintenance to components with a high potential for improvement from system perspective. / QC 20100810

<p>The Swedish electricity market was de-regulated in 1996, followed by new laws and a new regulation applied to the natural monopolies of electrical distribution systems (EDS). These circumstances have motivated distribution systems operators (DSOs) to introduce more comprehensive analysis methods. The laws, the regulation and additional incentives have been investigated within this work and results from this study can be valuable when developing risk methods or other quantitative methods applied to EDS. This tendency is not unique for Sweden, the results from a comparative study of customer outage compensation laws between Sweden and UK is for example included.</p><p>As a part of investigating these incentives, studies of the Swedish regulation of customer network tariffs have been performed which provide valuable learning when developing regulation models in different countries. The Swedish regulatory model, referred to as the Network Performance Assessment Model (NPAM), was created for one of the first de-regulated electricity markets in the world and has a unique and novel approach. For the first time, an overall presentation of the NPAM has been performed including description of the underlying theory as a part of this work. However, the model has been met by difficulties and the future usage of the model is uncertain. Furthermore, the robustness of the NPAM has been evaluated in two studies with the main conclusion that the NPAM is sensitive toward small variations in input data. Results from these studies are explained theoretically investigating algorithms of the NPAM.</p><p>A pre-study of a project on developing international test systems is presented and this ongoing project aims to be a useful input when developing risk methods. An application study is included with the approach to systematically describe the overall risk management process at a DSO including an evaluation and ideas of future developments. The main objective is to support DSOs in the development of risk management, and to give academic reference material to utilize industry experience. An idea of a risk management classification has been concluded from this application study. The study provides an input to the final objective of a quantitative risk method.</p>

Maximum asset performance is one of the major goals for electric power system managers. To reach this goal minimal life cycle cost and maintenance optimization become crucial while meeting demands from customers and regulators. One of the fundamental objectives is therefore to relate maintenance and reliability in an efficiently and effectively way, which is the aim of several maintenance methods such as the Reliability Centered Maintenance method (RCM). Furthermore, this necessitates the determination of the optimal balance between preventive and corrective maintenance to obtain the lowest total cost. This thesis proposes methods for defining the importance of individual components in a network with respect to total interruption cost. This is a first step in obtaining an optimal maintenance solution. Since the methods consider several customer nodes simultaneously, they are especially suitable for network structures that serve many purposes/customers e.g. transmission and distribution networks with more than one load point. The major results are three component reliability importance indices, which are applied in two case studies. The first case study is based on a network in the Stockholm area. The second case study is performed for one overhead line system in the rural parts of Kristinehamn. The application studies demonstrate that the indices are possible to implement for existing electrical networks and that they can be used for maintenance prioritization. Consequently these indices constitute a first step in the overall objective of a maintenance optimization method. The computations of the indices are performed both with analytical and simulation based techniques. Furthermore, the indices can be used to calculate the component contribution to the total system interruption cost. The approach developed for the importance indices can be utilized in any multi-state network that can be measured with one performance indicator. / QC 20101130

The Swedish electricity market was de-regulated in 1996, followed by new laws and a new regulation applied to the natural monopolies of electrical distribution systems (EDS). These circumstances have motivated distribution systems operators (DSOs) to introduce more comprehensive analysis methods. The laws, the regulation and additional incentives have been investigated within this work and results from this study can be valuable when developing risk methods or other quantitative methods applied to EDS. This tendency is not unique for Sweden, the results from a comparative study of customer outage compensation laws between Sweden and UK is for example included. As a part of investigating these incentives, studies of the Swedish regulation of customer network tariffs have been performed which provide valuable learning when developing regulation models in different countries. The Swedish regulatory model, referred to as the Network Performance Assessment Model (NPAM), was created for one of the first de-regulated electricity markets in the world and has a unique and novel approach. For the first time, an overall presentation of the NPAM has been performed including description of the underlying theory as a part of this work. However, the model has been met by difficulties and the future usage of the model is uncertain. Furthermore, the robustness of the NPAM has been evaluated in two studies with the main conclusion that the NPAM is sensitive toward small variations in input data. Results from these studies are explained theoretically investigating algorithms of the NPAM. A pre-study of a project on developing international test systems is presented and this ongoing project aims to be a useful input when developing risk methods. An application study is included with the approach to systematically describe the overall risk management process at a DSO including an evaluation and ideas of future developments. The main objective is to support DSOs in the development of risk management, and to give academic reference material to utilize industry experience. An idea of a risk management classification has been concluded from this application study. The study provides an input to the final objective of a quantitative risk method. / QC 20101125