Transportation agencies engage in extensive data collection activities in order to support their decision processes at various levels. However, not all the data collected supply transportation officials with useful information for efficient and effective decision-making. This thesis presents research aimed at formally identifying links between data collection and the supported decision processes. The research objective identifies existing relationships between Asset Management data collection and the decision processes to be supported by them, particularly in the project selection level. It also proposes a framework for effective and efficient data collection. The motivation of the project was to help transportation agencies optimize their data collection processes and cut down data collection and management costs. The methodology used entailed two parts: a comprehensive literature review that collected information from various academic and industrial sources around the world (mostly from Europe, Australia and Canada) and the development of a web survey that was e-mailed to specific expert individuals within the 50 U.S. Departments of Transportation (DOTs) and Puerto Rico. The electronic questionnaire was designed to capture state officials' experience and practice on: asset management endorsement and implementation; data collection, management and integration; decision-making levels and decision processes; and identified relations between decision processes and data collection. The responses obtained from the web survey were analyzed statistically and combined with the additional resources in order to develop the proposed framework and recommendations. The results of this research are expected to help transportation agencies and organizations not only reduce costs in their data collection but also make more effective project selection decisions. / Master of Science

<p dir="ltr">This thesis investigates approaches to classify and anticipate the energy consumption of commercial office buildings using external and performance benchmarking to reduce the energy consumption. External benchmarking in the context of building energy consumption considers the influence of climate zones that significantly impact a building's energy needs. Performance benchmarking recognizes that different types of commercial buildings have distinct energy consumption patterns. Benchmarks are established separately for each building type to provide relevant comparisons.</p><p dir="ltr">The first part of this thesis is about providing a benchmarking baseline for buildings to show their consumption levels. This involves simulating the buildings based on standards and developing a model based on real-time results. Software tools like Open Studio and Energy Plus were utilized to simulate buildings representative of different-sized structures to organize the benchmark energy consumption baseline. These simulations accounted for two opposing climate zones—one cool and humid and one hot and dry. To ensure the authenticity of the simulation, details, which are the building envelope, operational hours, and HVAC systems, were matched with ASHRAE standards.</p><p dir="ltr">Secondly, the neural network machine learning model is needed to predict the consumption of the buildings based on the trend data came out of simulation part, by training a comprehensive set of environmental characteristics, including ambient temperature, relative humidity, solar radiation, wind speed, and the specific HVAC (Heating, Ventilation, and Air Conditioning) load data for both heating and cooling of the building. The model's exceptional accuracy rating of 99.54% attained across all, which comes from the accuracy of training, validation, and test about 99.6%, 99.12%, and 99.42%, respectively, and shows the accuracy of the predicted energy consumption of the building. The validation check test confirms that the achieved accuracy represents the optimal performance of the model. A parametric study is done to show the dependency of energy consumption on the input, including the weather data and size of the building, which comes from the output data of machine learning, revealing the reliability of the trained model. Establishing a Graphic User Interface (GUI) enhances accessibility and interaction for users. In this thesis, we have successfully developed a tool that predicts the energy consumption of office buildings with an impressive accuracy of 99.54%. Our investigation shows that temperature, humidity, solar radiation, wind speed, and the building's size have varying impacts on energy use. Wind speed is the least influential component for low-rise buildings but can have a more substantial effect on high-rise structures.</p>

<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>

La gestion du patrimoine est un concept récemment adopté par le secteur public qui consiste d'une manière générale à prendre les décisions, jugées optimales, concernant l'acquisition, la maintenance, le fonctionnement et la disposition des immobilisations. Pour pouvoir prendre ces décisions, plusieurs outils peuvent être retrouvés à l'exemple de la comptabilité des immobilisations. Ces outils forment le système de gestion du patrimoine ou la chaîne de gestion patrimoniale. C'est ce qui est affirmé dans la littérature. Notre étude est accès sur la manière dont ces décisions se prennent au niveau de deux communes malgaches : la commune suburbaine d'Ambohimanga Rova et la commune rurale de Mahabo. L'analyse de plusieurs décisions patrimoniales a permis de déduire par la suite la place potentielle des outils qui ne s'arrête pas seulement à l'aide à la décision mais peuvent constituer également des éléments de légitimation des décisions politiques. / The public asset management which recently adopted by public sector, consists in making decision, considered as optimal, about the acquisition, the maintenance, the operating and the disposition of fixed assets. To make those decisions, several management tools can be found like the fixed assets accounting. Those tools constitute the asset management system. It is what is marked on the research about the asset management. Our study is about the way in which those decisions are made on the level of two malagasy's municipalities: the suburban municipality of Ambohimanga Rova and the rural municipality of Mahabo. The analysis of several decisions implies the potential roles of those tools which does not stop only with the decision-making process but can also constitute elements of legitimation of political decisions.

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

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

Digital transformation is an advancement in the wake of digitalization and have affected many industries and organizations during the recent decade. Due to both internal and external factors, this transformation is currently hitting the financial institutions and the asset management industry. Pressure from newcomers in the industry that have utilized the new technology and are taking over market share from larger banks. For asset managers to be able to hold on to their position in the market they will have to develop firm and sustainable digital strategies alongside the technological development. Regulations are toughening the industry and it is ever as important to report correct information about all your products. This thesis project will focus on asset managers who are facing such digital transformation and look at the key drivers of the digital strategy. The research was conducted via a qualitative method using interviews to gain further understanding of what the key driver are and the issues a legacy technical system can have on a team in asset management. The results found indicates the importance of adopting a digital strategy that is fit for the digitalization wave happening in the industry. Three main drivers were found to be most relevant, Human Capital, Digitalization \&amp; Technology, and External Factors. The importance to focus on these three drivers when constructing the digital strategy is argued. The analysis has been in cooperation with an asset manager, however the digital strategy drivers could also be applied on other industries that are facing digital transformation. / Digital transformation är en fortsättning av vågen av digitalisering och har påverkat många industrier och organisationer det senaste årtiondet. Både på grund av interna och externa faktorer så har den här transformationen nätt finansiella institutioner och asset managementindustrin. Press från nykomlingar i industrin har utnyttjat nya teknologier och har börjat ta över marknadsandelar från bankerna. För att asset managers ska lyckas hålla kvar i sin dominanta position i marknaden så måste de utveckla starka och hållbara digitala strategier tillsammans med den tekniska utvecklingen. Regelverk blir allt tuffare i industrin och det blir allt mer viktigt att rapportera korrekt information om alla sina produkter. Det här examensarbetet kommer fokusera på asset managers som just nu möter sådan digital transformation och kommer titta på vad som är de viktigaste aspekterna i den digitala strategin. Arbetet har genomförts med kvalitativa metoder i form av intervjuer för att samla vidare information om vad som är just de viktigaste aspekterna. även analysera dem problemen som kan uppstå med förlegade tekniska system inom asset management. De funna resultaten indikerar vikten av att anamma en digital strategi som är passande den digitaliserings våg som just ni sker i industrin. De tre huvudaspekterna som hittades var, Det Mänskliga Kapitalet, Digitalisering &amp; Teknologi och Externa Faktorer. Vikten av att fokusera på dessa tre aspekter när man konstruerar den digitala strategin har diskuterats. Analysen har gjorts i samarbete med en asset manager, men dessa huvudaspekter kan också bli applicerbara i andra industrier som möter digital transformation när man utvecklar den digitala strategin.

Asset management within the nuclear industry has become an increasingly relevant topic as safety requirements have tightened and energy security has become more important. Asset management ensures performance and reliability in a nuclear facility by balancing costs, opportunities, and risks to get the most out of assets. Asset management processes can often be modeled as capital budgeting problems, where investments are evaluated based on costs and benefits, which establishes a link to mathematical optimization. This study addresses asset management at the Swedish nuclear power plant, Forsmark, and aims to implement an optimization model to improve the project selection related to maintenance and replacement of assets at the plant. First, the most relevant areas of nuclear asset management are identified through a comprehensive literature review. The most relevant method, identified as a mix between risk-informed asset management and capital budgeting, is then implemented to fit the prerequisites at Forsmark. Several models of different complexity are developed and the resulting stochastic model incorporates uncertainty of input variables by assuming underlying distributions. Finally, a methodology to incorporate a quantitative risk measure in the optimization is suggested through the use of conditional value at risk. Results are generated based on simulated data and illustrate the potential of implementing the method at Forsmark. / Tillgångsförvaltning inom kärnkraftsindustrin har blivit alltmer aktuellt i takt med att säkerhetskraven har skärpts och tillförlitlighet i energiproduktionen blivit viktigare. Effektiv tillgångshantering säkerställer prestanda och reliabilitet i ett kärnkraftverk genom att hitta en balans mellan kostnader, möjligheter och risker för att maximera nyttan av tillgångar. Projekturval i tillgångsförvaltningen kan ofta modelleras som ett kapitalbudgeteringsproblem, där investeringar utvärderas utifrån kostnader och uppsida, vilket påvisar en koppling till matematisk optimering. Denna studie behandlar tillgångshantering vid det svenska kärnkraftverket Forsmark och syftar till att implementera en optimeringsmodell för att förbättra projekturvalet relaterat till underhåll av tillgångar vid anläggningen. Det första steget i studien bearbetar den befintliga litteraturen inom området för att få en uppfattning av relevanta metoder. Den mest relevanta metoden identifierades som en mix mellan riskinformerad tillgångsförvaltning och kapitalbudgetering. En metod baserad på de generella principerna för dessa områden utvecklades och anpassades för de specifika förutsättningarna på Forsmark. Flera modeller av olika komplexitet utvecklades och den slutgiltiga stokastiska modellen inkorporerar osäkerhet i de mest relevanta ingångsvariablerna genom att anta sannolikhetsfördelningar. Slutligen föreslås en metod för att implementera ett kvantitativt riskmått i optimeringen genom att använda CVaR. Resultaten genereras utifrån simulerade data och illustrerar potentialen i att implementera metoden på Forsmark.

Submitted in fulfillment of the requirement for the Degree of Master of Technology: Cost and Management Accounting, Durban University of Technology, 2013. / Property, plant and equipment (PPE) constitute a significant portion of total assets of South African public higher education institutions. It is therefore important to keep proper records of the assets and to account for them accurately in the Annual Financial Statements. The aim of this study therefore was to investigate the accounting treatment of property, plant and equipment at public higher education institutions (PHEIs) in South Africa. The following objectives were addressed in this study, to: determine how assets are classified; find out how asset transactions are recorded; and to determine the accounting treatment of assets in terms of cost, depreciation, impairment and disposal. Based on the International Financial Reporting Standards, this study used a mixed-methods research approach to collect data regarding the accounting treatment of PPE at the 23 PHEIs in South Africa. Analysis of results indicated that some institutions: apply different useful lives for the same asset classes; use threshold amounts for the recording and depreciating of assets; use the same value for the recording and depreciating of assets while others record at one value but depreciate at a higher value; and depreciate PPE at different rates as they apply varying useful life to different asset classes. This study also found that while some institutions do impairment testing on an annual basis, others do not, as they do not have a policy in place for impairment testing. Given that the activities or business of educational institutions are similar in nature, this study recommends that PHEIs need to apply consistent recording of assets in terms of their useful life as the useful life of an asset has direct correlation with the surplus or deficit of an institution. This study makes further recommendations regarding the accounting treatment of PPE at PHEIs in South Africa based on the findings of this study. Suggestions for further research are also presented.

Over the last twenty years, the concepts of sustainability and sustainable development have assumed political importance around the world, and have been largely embraced by governments and prominent international institutions. These concepts have been a means of tackling the challenges of population growth and environmental change. For the UK water sector, these concepts now represent a multitude of challenges. The confluence of climate change and population growth is reducing access to, and the availability of, water resources. The financial costs of inputs such as energy, chemicals, materials and cost of process by-products such as greenhouse gases, carbon, and waste services continue to rise. Government regulators are demanding an improvement in the quality of services, increasingly stringent conditions for emissions to water, air or land, catchment-specific management of the water environment, and the adoption of longterm planning horizons. The UK government has expectations that the water sector will play a role in the delivery of its targets for reducing energy consumption and carbon emissions. Society demands that WaSCs engage in high-level stakeholder consultations and employ long-term visions to guide their decision-making. Finally, WaSCs are increasingly expected to demonstrate and respond to local and global concerns (under the rubric of corporate responsibility) to further justify their value to society. Cont/d.