Project cost escalation is a major problem for State Highway Agencies (SHA). This problem is evident in cost estimating procedures that may not promote consistency and accuracy of costs over the project development process. The research proposes that a relationship exists between applying good estimating practices and minimizing cost escalation from the initial planning estimate to the engineer??s estimate at final design. The objective of this research is to develop a preliminary list of strategies, methods, and tools for project cost estimation practices aimed at achieving greater consistency and accuracy between the project development phases. A literature review was conducted that assisted in identifying factors that lead to the cost escalation of projects. The information from the literature was used to discover the core estimating assumptions that are the root causes behind cost escalation and lack of project estimate consistency and accuracy. After the cost escalation factors were determined, interviews with SHAs were conducted that lead to identifying unique and/or innovative approaches that will aid the SHAs in overcoming the cost escalation factors. The main methodology used to develop a potential list of strategies, methods, and tools was first focused on linking strategies to causes of cost escalation. Global strategies were identified by means of this approach. Methods and tools that would likely be effective in implementing the strategies are therefore directed at mitigating root causes of estimate problems in a focused approach. The strategies, methods, and tools are aligned with the project development phase where they would be implemented. Thus, a preliminary list of strategies, methods, and tools is provided in this study.

The level of achieved accuracy in design cost estimating is generally accepted by researchers as being less than desirable. Low accuracy has been attributed to the nature of historical cost data, estimating method and the expertise of the estimator. Previous researchers have suggested that the adoption of resource based estimating by designers could eliminate data and method-related problems. The work in this thesis has shown that this will not solve the problem of inaccuracy in estimating. A major problem in assessing accuracy in design cost estimating has been the absence of a generally agreed definition of the'true cost' of a construction project. Hitherto, studies of accuracy in design cost estimating have relied solely on the assessment of errors using the low bid as a datum. Design cost estimators do not always focus on predicting the low bid. Rather, they may focus on the lowest, second lowest, third lowest or any other bid, mean/median of bids, or sometimes, on just being'within the collection'. This has resulted in designers and researchers having different views on the level of achieved accuracy in estimating. To resolve this problem, an analysis package, ACCEST (ACCuracy in ESTimating), was developed to facilitate 'fair' assessment of accuracy in design cost estimates. Tests - using cost data from 7 offices, the ACCEST package and the OPEN ACCESS II package on an IBM PS/2 - have shown that error in design cost estimating (averaging 3.6% higher than the predicted parameter) is much lower than portrayed in construction literature (averagel3% higher than the low bid). Also, false associations between project environment factors (such as geographical location, market conditions, number of bidders, etc.) and the level of achieved accuracy has been developed by researchers through using the low bid as a datum. Previous researches have also demonstrated that design estimators do not learn sufficiently from experience on past projects. A controlled experiment on design cost estimating information selection was designed to explain this occurrence. Failure to learn, and the persistent use of information on one project for estimating, has been shown to result from the method of information storage in design offices, the illusion of validity of inaccurate rules and over-confidence resulting from inaccurate assessment of individual expertise. A procedure for aiding learning from experience in design cost estimating has been suggested. Finally, the work has shown that by distinguishing between different trades, and selectively applying different estimating strategies, based on the objective evaluation of the uncertainty associated with cost prediction for ear h trade, error in design cost estimating could be further reduced. Two formulae for predicting tender prices using data generated from historical cost estimating experience are represented.

National economic development relies on long-term stable supply of electricity, and the stability of electricity supply absolutely relates to the quality of maintenance of power generation units. In the past, the electricity supply of Taiwan was exclusively dominated by the state-run Taiwan Power Company (Taipower). Following government de-regulation policy, the private IPP (Independent Power Plants) also have joined the grid of Taiwan's electricity supply that diversified electricity power supply. This study collects power generation equipment maintenance cost information bases on practical detail cost information and labor cost paid by employer that listed in law or regulation. The information of estimating contrast cost which cannot be easily quantified is collected by questionnaire of power plant and contractor personnel who response for estimating cost of power generation equipment maintenance in order to gather practical cost estimating rules. After summarizing and analyzing collected maintenance cost data, easily calculating cost estimating model for power generation equipment had been proposed. The model can be set as criteria for cost estimating and examine the maintenance contract price of contractor in view of contractor cost. Power generation industries had faced severe cost pressures due to the high rising fuel costs, but not readily reflect the cost of power generation to the electricity charges. In the condition of high price of fuel, the only way to save operational cost was to reduce expense of equipment maintenance and other operation costs. So, the power plants aim at lowing equipment maintenance costs to meet limited budget. Most power plants plan their equipment maintenance budget according to quotation of original equipment manufacturer or professional contractor. There are lacks of related cost information to examine whether the quotation is reasonable or not. The study showed that the scale of contractor companies, indirect cost apportionment can affect indirect costs of contract cost, thereby affecting the contract price. The estimated profit will vary with many factors case by case such as market competition level, technical difficulty, working season, and duration etc.

Bridge Information Modeling (BrIM), as a concept, has been introduced to enhance the procedures of the whole phases of a bridge life-cycle starting with concept and design, through construction and operation, and ending with maintenance and rehabilitation. Integrating BrIM and design tools will help improve the methods used in designing and constructing bridge projects at early stages taking into considerations their cost and time constraints. The main objective of this research is to develop an integrated model that helps owners, designers and construction managers visualize bridge projects in a 3D mode and accordingly automate the process of generating preliminary cost estimates during the conceptual design stage. To achieve the above mentioned objective, a proposed methodology will be applied where all the aspects needed to develop an efficiently integrated model are realized. Thus, this research describes the proposed methodology that incorporates three modules, which are the core of the integrated model. These modules are: a knowledge based system module, which is used to generate conceptual dimensions and parameters depending on algorithmic and heuristic knowledge gathered from codes, guidelines and design experts; a conceptual cost estimation module, which is used to generate conceptual cost estimate based on the results of the first module; and a 3DCAD module, which is integrated with the previous modules where users will visualize the proposed bridge in 3D based on the results of the knowledge based module. The successful development of the model would help owners and investors identify the cost and visualize the proposed projects at the early stages of the project life, so they have an idea of the budget required and the aesthetics of the proposed projects. The integrated model is validated through an actual case project to test its workability and output.

Preconstruction services play a vital role in ensuring timely approval of infrastructure funds and successful execution of construction projects. Most state DOTs use simple methods such as a percentage of estimated construction costs that has proven to be unreliable. Several studies have developed statistical models using historical data to improve current practices. However, such models have performed poorly, and practitioners have not utilized these models. This study develops and evaluates data mining models such as multiple regression and artificial neural networks and concludes that such models do not provide sufficiently accurate estimates of preconstruction service fees and hours. Subsequently, it proposes an alternative approach using a case-based reasoning (CBR) technique that uses similarity scoring to retrieve the most similar projects. The historical preconstruction service fees and hours of similar projects can be used to estimate preconstruction service fees and hours for a new project and make any adjustment necessary. A spreadsheet tool is developed to implement this CBR technique. The tool provides a simple and flexible platform that enables engineers to extract necessary data and help them in making data-driven estimates. Thus, the tool is expected to aid state DOT engineers in negotiating with consultants with higher confidence.

This thesis is the result of many years of research in the field of manufacturing cost modelling. It particularly focuses on the Data Collection Process for the development of manufacturing cost models in the UK Aerospace Industry with no less important contributions from other areas such as construction, process and software development. The importance of adopting an effective model development process is discussed and a new CMD Methodology is proposed. In this respect, little research has considered the development of the cost model from the point of view of a standard and systematic Methodology, which is essential if an optimum process is to be achieved. A Model Scoping 3 Framework, a functional Data Source and Data Collection Library and a referential Data Type Library are the core elements of the proposed Cost Model Development Methodology. The research identified a number of individual data collection methods, along with a comprehensive list of data sources and data types, from which essential data for developing cost models could be collected. A Taxonomy based upon sets of generic characteristics for describing the individual data collection, data sources and data types was developed. The methods, tools and techniques were identified and categorised according to these generic characteristics. This provides information for selecting between alternative methods, tools and techniques. The need to perform frequent iterations of data collection, data identification, data analysis and decision making tasks until an acceptable cost model has been developed has become an inherent feature of the CMDP. It is expected that the proposed model scoping framework will assist cost engineering and estimating practitioners in: defining the features, activities of the process and the attributes of the product for which a cost model is required, and also in identifying the cost model characteristics before the tasks of data identification and collection start. It offers a structured way of looking at the relationship between data sources, cost model characteristics and data collection tools and procedures. The aim was to make the planning process for developing cost models more effective and efficient and consequently reduce the time to generate cost models.

The research was conducted in the light of a training programme which will train a total of 150 engineers of AVIC I in Cranfield University during a period of 3 years. Cost has become an essential driver to aircraft design, as well as performances due to either the limited defence budget or competitive airline market. Consequently, knowing the possible cost prior to making actual expenditure will help managers to make proper decisions and allocate resources efficiently, and designers to optimize their work. Existing aircraft cost estimating models are outdated and mainly based on a database including both military and civil aircraft with various missions. This research concentrated on commercial jet aircraft and was to develop a suitable acquisition cost estimating methodology for conceptual design from a commercial aircraft manufacturer’s perspective. The literature reviewing took a comprehensive overview of some widely-applied cost estimating methods: Analogy, Parametric, Bottom-up, Feature-based costing, Activitybased costing (ABC), Expert judgement, and etc. Some practical cost models were also reviewed to learn the application of cost estimating in the aerospace industry. Then, analogy and parametric approaches were selected to perform the methodology development considering the limited data available at the conceptual design phase. An investigation was deployed to identify the actual problems in practice. The results helped to recognize the needs of industry. Also, the preparation works for development are presented to understand the environment. With subjective judgement and statistical techniques, a series of cost estimating relationships (CERs) were achieved, in which some historic explanatory parameters remained or were eliminated, and some new ones introduced. Size of aircraft became another variable besides weight. As to engines, all developed explanatory variables have been revealed in prior researches. The validation of CERs proves that they can provide reliable cost estimates with high accuracy and can be applied to conceptual design. In addition, a case study was conducted using a baseline aircraft defined in the group design project (GDP) and presents cost forecasting for the proposed aircraft. At last, discussion and conclusion presents an overview of the research. A framework for cost estimating system can be educed. Also, the future work is proposed for in-depth research.

In recent years, the United States has seen a high demand for dam rehabilitation projects as most dam infrastructure has started to reach or exceed the expected life span of 50-70 years. Rehabilitation projects can be very expensive, however, and the funding options for dam owners are limited. To raise awareness, organizations such as ASDSO and the Virginia DCR release cost estimates every few years to encourage more investment in dam infrastructure. Unfortunately, many cost estimates have been made with limited data and outdated methodologies. This research collects a new sample of cost data for Virginia dam rehabilitation projects and uses it to assess key factors for cost estimating. Factors such as height, drainage area, hazard classification, and ownership type were used to make regression models that predict the cost of addressing Virginia's non-compliant dams. This study estimates that approximately $300 million is needed to address Virginia's 98 deficient high hazard, local government owned dams and that $122 million of that estimate is need for SWCD dams alone. / Master of Science / Dam rehabilitation refers to the repair, removal, or upgrade of an existing dam structure. Rehabilitation projects are done when dams start to exceed their intended life span (approximately 50-60 years) or when policy makers change the required safety standards. The demand for dam rehabilitation has been increasing for the past several years as more and more dams are being identified as unsafe, but the available funding for rehabilitation projects is limited and competitive to obtain for dam owners. To raise awareness, dam safety agencies release cost estimates every few years to encourage government leaders and the general public to take action. However, these estimates need to be taken with caution as they are often made with limited data availability and outdated methodologies. This research collects a new sample of cost data for Virginia dam rehabilitation projects that have occurred in the last 15 years. Dam characteristics such as height, watershed size, downstream risk potential, and ownership type were used to form equations that predict the cost of addressing Virginia's non-compliant dams. This study estimates that approximately $300 million is needed to address Virginia's 98 deficient high hazard, local government owned dams and that $122 million of that estimate is need for Virginia's Soil and Water Conservation District dams alone.

A computerised cost estimating system, which can be used for making preliminary estimates of fixed capital investment of process plants, has been developed. The contituents of the system are (1) a cost calculating routine, COSMOD, compatible with existing modular executive programs, such as GEMCS, (2) an equipment data base, and (3) an equipment catalogue. The following are the significant characteristics of the cost estimating system.It has flexibility. It can be used as an independent cost estimating system, or as part of a modular executive-aided computer program. As part of an executive aided system, it may be used as a subroutine to a 'module* or 'unit computation', or as a 'module' or 'unit computation' itself. It will estimate the cost of one or more equipment but is capable of accepting costs generated external to itself. It requires relatively little computer space and time. The COSMOD program is concise and efficient. Its common block requirements in executive-aided systems is small. It adds little to the cost or time of running equipment design cases on the computer. It has access to a large quantity of data on equipment costs. Its data base contains cost information on nearly 300 different types of equipment, ensuring satisfactory fulfilment of its varying and often complex data requirements. The data are organised in a multiple record, random access file. This allows direct access to the equipment data of interest. It also allows easy addition, deletion or change to the data on file. An equipment catalogue is provided for the user. It provides information about the equipment whose cost data are available in COSMOD*s data file, and serves as a guide for the user in selecting and in providing data required by COSMOD. In conclusion, this work makes available, complete with cost estimating data and equipment catalogue, a preliminary capital cost estimating system, the absence of which has discouraged or impeded economic evaluations in plant design studies on the computer. / Thesis / Master of Engineering (ME)

Although the issue of uncertainties in cost model parameters has been recognized as an important aspect of life-cycle cost analysis, it is often ignored or not well treated in cost estimating. A simulation approach employing kernel estimation techniques and their asymptotic properties in the development of the probability distribution functions (PDFs) of cost estimates is proposed. This eliminates the guess work inherent in current simulation based cost estimating procedures, reduces the amount of data sampled and makes it easier to specify the accuracy desired in the estimated distribution. Building energy costs can be reduced considerably if air duct systems are designed for the least life-cycle cost. The IPS-Method, a simple approach to HVAC air duct design is suggested. The Diameter and Enhanced Friction Charts are also developed. These are charts that implicitly incorporate the LCC and are better than the existing Friction Chart for the selection of duct sizes. Through illustrative examples, the ease and effectiveness of these are demonstrated. For more complex designs, a Segregated Genetic Algorithm (SGA) is recommend. A sample problem with variable time-of-day operating conditions and utility rates is used to illustrate its capabilities. The results are compared to those obtained using weighted average flow rates and utility rates to show the life-cycle cost savings possible by using this approach. Although life-cycle cost savings may be only between 0.4% and 8.3% for some simple designs, much larger savings may occur with more complex designs and operating constraints. The SGA is combined with probabilistic cost estimating to optimize HVAC air duct systems with uncertainties in the model parameters. The designs based on the SGA method tended to be less sensitive to typical variations in the component physical parameters and, therefore, are expected to result in lower balancing and operating costs.