Life cycle costing of major household appliances /

"Illinois Energy Conservation Program."

Life cycle costing procurement guide (interim).

"July 1970"--Cover.

Activity-based life cycle costing model for cost estimation and monitoring – Case: manned and autonomous dry bulk carrier

Recent developments in automation, robotics and artificial intelligence have given a push to a wider usage of these technologies in recent years, and nowadays, driverless transport systems are already state-of-the-art on certain legs of transportation. This has given a push for the maritime industry to join the advancement. The case organisation, AAWA initiative, is a joint industry-academia research consortium with the objective of developing readiness for the first commercial autonomous solutions, exploiting state-of-the-art autonomous and remote technology. The initiative develops both autonomous and remote operation technology for navigation, machinery, and all on-board operating systems. The aim of this study is to develop a model with which to estimate and forecast the operational costs, and thus enable comparisons between manned and autonomous cargo vessels. The building process of the model is also described and discussed. Furthermore, the model’s aim is to track and identify the critical success factors of the chosen ship design, and to enable monitoring and tracking of the incurred operational costs as the life cycle of the vessel progresses. The study adopts the constructive research approach, as the aim is to develop a construct to meet the needs of a case organisation. Data has been collected through discussions and meeting with consortium members and researchers, as well as through written and internal communications material. The model itself is built using activity-based life cycle costing, which enables both realistic cost estimation and forecasting, as well as the identification of critical success factors due to the process-orientation adopted from activity-based costing and the statistical nature of Monte Carlo simulation techniques. As the model was able to meet the multiple aims set for it, and the case organisation was satisfied with it, it could be argued that activity-based life cycle costing is the method with which to conduct cost estimation and forecasting in the case of autonomous cargo vessels. The model was able to perform the cost analysis and forecasting, as well as to trace the critical success factors. Later on, it also enabled, albeit hypothetically, monitoring and tracking of the incurred costs. By collecting costs this way, it was argued that the activity-based LCC model is able facilitate learning from and continuous improvement of the autonomous vessel. As with the building process of the model, an individual approach was chosen, while still using the implementation and model building steps presented in existing literature. This was due to two factors: the nature of the model and – perhaps even more importantly – the nature of the case organisation. Furthermore, the loosely organised network structure means that knowing the case organisation and its aims is of great importance when conducting a constructive research.

The importance of environmental issues and costs in Life Cycle Cost Analysis (LCCA) for highway projects

Sustainability has been increasingly recognised as an integral part of highway infrastructure development. In practice however, the fact that financial return is still a project’s top priority for many, environmental aspects tend to be overlooked or considered as a burden, as they add to project costs. Sustainability and its implications have a far-reaching effect on each project over time. Therefore, with highway infrastructure’s long-term life span and huge capital demand, the consideration of environmental cost/ benefit issues is more crucial in life-cycle cost analysis (LCCA). To date, there is little in existing literature studies on viable estimation methods for environmental costs. This situation presents the potential for focused studies on environmental costs and issues in the context of life-cycle cost analysis. This paper discusses a research project which aims to integrate the environmental cost elements and issues into a conceptual framework for life cycle costing analysis for highway projects. Cost elements and issues concerning the environment were first identified through literature. Through questionnaires, these environmental cost elements will be validated by practitioners before their consolidation into the extension of existing and worked models of life-cycle costing analysis (LCCA). A holistic decision support framework is being developed to assist highway infrastructure stakeholders to evaluate their investment decision. This will generate financial returns while maximising environmental benefits and sustainability outcome.

Road Design for Future Maintenance : Life-cycle Cost Analyses for Road Barriers

The cost of a road construction over its service life is a function of design, quality of construction as well as maintenance strategies and operations. An optimal life-cycle cost for a road requires evaluations of the above mentioned components. Unfortunately, road designers often neglect a very important aspect, namely, the possibility to perform future maintenance activities. Focus is mainly directed towards other aspects such as investment costs, traffic safety, aesthetic appearance, regional development and environmental effects. This doctoral thesis presents the results of a research project aimed to increase consideration of road maintenance aspects in the planning and design process. The following subgoals were established: Identify the obstacles that prevent adequate consideration of future maintenance during the road planning and design process; and Examine optimisation of life-cycle costs as an approach towards increased efficiency during the road planning and design process. The research project started with a literature review aimed at evaluating the extent to which maintenance aspects are considered during road planning and design as an improvement potential for maintenance efficiency. Efforts made by road authorities to increase efficiency, especially maintenance efficiency, were evaluated. The results indicated that all the evaluated efforts had one thing in common, namely ignorance of the interrelationship between geometrical road design and maintenance as an effective tool to increase maintenance efficiency. Focus has mainly been on improving operating practises and maintenance procedures. This fact might also explain why some efforts to increase maintenance efficiency have been less successful. An investigation was conducted to identify the problems and difficulties, which obstruct due consideration of maintainability during the road planning and design process. A method called “Change Analysis” was used to analyse data collected during interviews with experts in road design and maintenance. The study indicated a complex combination of problems which result in inadequate consideration of maintenance aspects when planning and designing roads. The identified problems were classified into six categories: insufficient consulting, insufficient knowledge, regulations and specifications without consideration of maintenance aspects, insufficient planning and design activities, inadequate organisation and demands from other authorities. Several urgent needs for changes to eliminate these problems were identified. One of the problems identified in the above mentioned study as an obstacle for due consideration of maintenance aspects during road design was the absence of a model for calculating life-cycle costs for roads. Because of this lack of knowledge, the research project focused on implementing a new approach for calculating and analysing life-cycle costs for roads with emphasis on the relationship between road design and road maintainability. Road barriers were chosen as an example. The ambition is to develop this approach to cover other road components at a later stage. A study was conducted to quantify repair rates for barriers and associated repair costs as one of the major maintenance costs for road barriers. A method called “Case Study Research Method” was used to analyse the effect of several factors on barrier repairs costs, such as barrier type, road type, posted speed and seasonal effect. The analyses were based on documented data associated with 1625 repairs conducted in four different geographical regions in Sweden during 2006. A model for calculation of average repair costs per vehicle kilometres was created. Significant differences in the barrier repair costs were found between the studied barrier types. In another study, the injuries associated with road barrier collisions and the corresponding influencing factors were analysed. The analyses in this study were based on documented data from actual barrier collisions between 2005 and 2008 in Sweden. The result was used to calculate the cost for injuries associated with barrier collisions as a part of the socio-economic cost for road barriers. The results showed significant differences in the number of injuries associated with collisions with different barrier types. To calculate and analyse life-cycle costs for road barriers a new approach was developed based on a method called “Activity-based Life-cycle Costing”. By modelling uncertainties, the presented approach gives a possibility to identify and analyse factors crucial for optimising life-cycle costs. The study showed a great potential to increase road maintenance efficiency through road design. It also showed that road components with low investment costs might not be the best choice when including maintenance and socio-economic aspects. The difficulties and problems faced during the collection of data for calculating life-cycle costs for road barriers indicated a great need for improving current data collecting and archiving procedures. The research focused on Swedish road planning and design. However, the conclusions can be applied to other Nordic countries, where weather conditions and road design practices are similar. The general methodological approaches used in this research project may be applied also to other studies.

A framework for life cycle cost estimation of a product family at the early stage of product development

A cost estimation method is required to estimate the life cycle cost of a product family at the early stage of product development in order to evaluate the product family design. There are difficulties with existing cost estimation techniques in estimating the life cycle cost for a product family at the early stage of product development. This paper proposes a framework that combines a knowledge based system and an activity based costing techniques in estimating the life cycle cost of a product family at the early stage of product development. The inputs of the framework are the product family structure and its sub function. The output of the framework is the life cycle cost of a product family that consists of all costs at each product family level and the costs of each product life cycle stage. The proposed framework provides a life cycle cost estimation tool for a product family at the early stage of product development using high level information as its input. The framework makes it possible to estimate the life cycle cost of various product family that use any types of product structure. It provides detailed information related to the activity and resource costs of both parts and products that can assist the designer in analyzing the cost of the product family design. In addition, it can reduce the required amount of information and time to construct the cost estimation system.

Full cost accounting for the life cycle of coal.

Each stage in the life cycle of coal-extraction, transport, processing, and combustion-generates a waste stream and carries multiple hazards for health and the environment. These costs are external to the coal industry and are thus often considered "externalities." We estimate that the life cycle effects of coal and the waste stream generated are costing the U.S. public a third to over one-half of a trillion dollars annually. Many of these so-called externalities are, moreover, cumulative. Accounting for the damages conservatively doubles to triples the price of electricity from coal per kWh generated, making wind, solar, and other forms of nonfossil fuel power generation, along with investments in efficiency and electricity conservation methods, economically competitive. We focus on Appalachia, though coal is mined in other regions of the United States and is burned throughout the world.

Integrating health and sustainability in life cycle assessment

Until now health impact assessment and environmental impact assessment are two different issues, often not addressed together. Both issues have to be dealt with for sustainable building. The aim of this paper is to link healthy and sustainable housing in life cycle assessment. Two strategies are studied: clean air as a functional unity and health as a quality indicator. The strategies are illustrated with an example on the basis of Eco-Quantum, which is a Dutch whole-building assessment tool. It turns out that both strategies do not conflict with the LCA methodology. The LCA methodology has to be refined for this purpose.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Improving the management of building life cycle : a data mining approach

The construction industry has adapted information technology in its processes in terms of computer aided design and drafting, construction documentation and maintenance. The data generated within the construction industry has become increasingly overwhelming. Data mining is a sophisticated data search capability that uses classification algorithms to discover patterns and correlations within a large volume of data. This paper presents the selection and application of data mining techniques on maintenance data of buildings. The results of applying such techniques and potential benefits of utilising their results to identify useful patterns of knowledge and correlations to support decision making of improving the management of building life cycle are presented and discussed.