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Reliable cost estimation is important for economic production, cost control and maintaining competitive advantage in manufacturing contract bidding. Therefore, estimating the manufacturing cost of a machined part is of critical importance in CNC manufacture. Computers aided systems the link to manufacturers CAD systems and databases have been used since the 1980’s to identify product cost and enable a company to evaluate resource utilisation. While the concept of an integrated costing system has made significant advances in integrating the design function with the cost estimation process, there are still major gaps in acquisition and application of detailed product data for generation of timely and reliable costing information feedback to engineers. Integrated costing systems are information intensive and require significant manufacturing data support. A major obstacle is the bespoke nature of the available cost relevant data and their storage in company specific database tailored to individual company practices. Thus there is need to consider standardisation of information from the design of component through to their process planning and manufacture. This will allow seamless exchange of detailed, cost relevant, information between other computers aided systems and costing systems to facilitate automatic and reliable cost information feedback. In this research a novel framework is specified and designed for enabling detailed product information that exists across CNC manufacturing, to be utilised for generation of reliable cost estimates. The standards based costing proposed in this thesis framework facilitates high-level integration of various CAx resources and increases the availability of product creation process (PCP) data that are applicable in costing process. A prototype implementation of the unified costing framework is utilised to demonstrate the capabilities of the framework. The demonstration is conducted using two industrially inspired prismatic test components where the components machining cycles were timed with a stop watch and the actual result compared with the prototype system estimated result to determine its reliability. The research shows that implementation of manufacturing standard that contain structured representation PCP information together with an effective data retrieval mechanism and computational algorithms can provide a standard compliant framework to realise an information rich (detailed) costing system. The potential of the proposed framework is not limited to enabling the use of detailed information that exist within manufacturing facility to generate cost information; it also provides a standard compliant approach for the development of future generations of costing systems.

This thesis presents a framework to conduct a quantity take-off (QTO) and cost estimate within the Building Information Modeling (BIM) Environment. The product of this framework is a model-based cost estimating tool. The framework addresses the cost uncertainty associated with the detailed information defining BIM model element properties. This cost uncertainty is due to the lack of available tools that address detailed QTO and cost estimation using solely a BIM platform. In addition, cost estimators have little experience in leveraging and managing information within semantic-rich BIM models. Unmanaged BIM element parameters are considered a source of uncertainty in a model-based cost estimate, therefore they should be managed and quantified as work items. A model-based system, which assists the estimators to conduct a QTO and cost estimate within the BIM environment, is developed. This system harnesses BIM element parameters to drive work items associated with the parameter’s host element. The system also captures the cost of scope not modeled in the design team’s BIM models. The system consists of four modules 1) establishing estimate requirements, 2) planning and structuring the estimate, 3) quantification and costing, and 4) model-based historical cost data collection. The complete system can produce a project cost estimate based on the 3D BIM Model. This framework is supported by a computation engine built within an existing virtual design and construction (VDC) model review software. The computation engine supports BIM authoring and reviewing BIM data. The Framework’s quantification and costing module was compared to existing methods in a case study. The outcomes of the model-based system demonstrated improved cost estimate accuracy in comparison to the BIM QTO method and improved speed compared to the traditional methods. The framework provides a systematic workflow for conducting a detailed cost estimate leveraging the parameters stored in the BIM models.

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Increasing competition and regulation are raising the pressure on manufacturing organisations to innovate their products. Innovation is fraught by significant uncertainty of whole product life cycle costs and this can lead to hesitance in investing which may result in a loss of competitive advantage. Innovative products exist when the minimum information for creating accurate cost models through contemporary forecasting methods does not exist. The scientific research challenge is that there are no forecasting methods available where cost data from only one time period suffices for their application. The aim of this research study was to develop a framework for forecasting cost uncertainty using cost data from only one time period. The developed framework consists of components that prepare minimum information for conversion into a future uncertainty range, forecast a future uncertainty range, and propagate the uncertainty range over time. The uncertainty range is represented as a vector space representing the state space of actual cost variance for 3 to n reasons, the dimensionality of that space is reduced through vector addition and a series of basic operators is applied to the aggregated vector in order to create a future state space of probable cost variance. The framework was validated through three case studies drawn from the United States Department of Defense. The novelty of the framework is found in the use of geometry to increase the amount of insights drawn from the cost data from only one time period and the propagation of cost uncertainty based on the geometric shape of uncertainty ranges. In order to demonstrate its benefits to industry, the framework was implemented at an aerospace manufacturing company for identifying potentially inaccurate cost estimates in early stages of the whole product life cycle.

Additive Manufacture (AM) is a novel manufacturing method; it is a process of forming components by adding materials. Owing to material saving and manufacturing cost saving, more and more research has been focused on metal AM technologies. WAAM is one AM technology, using arc as the heat sources and wire as the material to create parts with weld beads on a layer-by-layer basis. The process can produce components in a wide range of materials, including aluminum, titanium and steel. High deposition rate, material saving and elimination of tooling cost are critical characteristics of the process. Cost estimation is important for all companies. The estimated results can be used as a datum to create a quote for customers or evaluate a quote from suppliers, an important consideration for the application of WAAM is its cost effectiveness compared with traditional manufacture methods. The aim of this research is to find a way to develop a cost estimating method capable of providing manufacturing cost comparison of WAAM with CNC. A cost estimation model for CNC machining has been developed. A process planning approach for WAAM was also defined as part of this research. An Excel calculation spreadsheet was also built and it can be easily used to estimate and compare manufacture cost of WAAM with CNC. Using the method developed in this research, the cost driver analysis of WAAM has been made. The result shows that reduced material cost is the biggest cost driver in WAAM. The cost comparison of WAAM and CNC also has been made and the results show that with the increase of buy-to-fly ratio WAAM is more economical than CNC machining.

Escalation of right-of-way (ROW) costs have been shown to be a prime contributor to project cost escalation in the highway industry. Two problems contribute to ROW cost escalation: 1) the ROW cost estimation and cost estimate management process generally lacks structure and definition as compared to other areas of cost estimation; and 2) there is a lack of integration and communication between those responsible for ROW cost estimating and those responsible for general project cost estimating. The research for this thesis was preceded by a literature review to establish the basis for the study. Data collection was completed through interviews of seven state highway agencies (SHAs) and two local public agencies (LPAs). The findings of the research are presented in a set of ROW flowcharts which document the steps, inputs, and outputs of the ROW cost estimation and cost estimate management process. Three ROW cost estimates and a cost management process take place throughout project development. An effort was made from the onset of the research to relate the ROW cost estimating and cost estimate management process to the first four project development phases (planning, programming. preliminary design, and final design). There are five flowcharts produced as a result of this research: 1) an agency-level flowchart showing all cost estimates and the interaction of ROW with the project development process; 2) a conceptual ROW cost estimating flowchart which depicts the required steps during planning; 3) a baseline ROW cost estimating flowchart which depicts the required steps during programming; 4) an update ROW cost estimating flowchart which depicts the required steps during preliminary design to include a cost estimate management loop; and 5) a ROW cost management flowchart which depicts the required steps during final design. Although selected SHA contacts provided input following the development of the flowcharts, the flowcharts were only validated to a limited extent due to time and budget constraints. These flowcharts attempt to address the two contributing problems to ROW cost escalation by providing structure to the ROW cost estimation process and by developing the ROW process flowcharts linked to the project development process. Based on the input provided by SHA contacts, the flowcharts appear to have the potential to provide guidance to SHAs in improving the accuracy of ROW cost estimates through addressing these two problems.

The costs of acquiring parcels by condemnation are usually significantly higher than those for property acquired by negotiation, suggesting that Right-of-Way (R/W) acquisition costs may best be described by two different regression equations. This paper develops a switching regression model of acquisition cost to simultaneously predict the probability of whether a parcel will go to condemnation rather than be acquired via negotiation and the corresponding acquisition costs under these two regimes. The error terms of the selection equation and the two cost equations follow a trivariate normal distribution to reflect correlations across unobserved factors (such as a land owner's tenacity or a site's view value). When this model is calibrated using data on properties acquired across the state of Texas for transportation projects between 2008 and 2011, results suggest that R/W appraisers and staff should pay special attention to commercially used parcels in urban areas involving a partial taking with a relatively small remainder. Comparison of cost estimates between the two regimes (condemnation vs. negotiation) suggests that condemned parcels will have, on average, 78% higher acquisition costs across the 1,710 acquired properties and 51% greater price variation. These results suggest that it is much more costly to acquire a property and more difficult to accurately predict its costs if it cannot be acquired via negotiation. The application of model estimates to an example corridor highlights the value of simulation to capture all modeling uncertainties. This two-regime model is further extended to a three-category multinomial endogenous switching, allowing for differential cost estimates across negotiation-deed, administrative settlement, and condemnation contexts. A model of acquisition time -- from the agency's initial-offer date to its final possession date is also developed, to examine the effects of condemnation on acquisition duration. The results suggest that condemnation proceedings add approximately 7 to 8 months, on average, to parcel acquisitions by the Texas Department of Transportation. Taken together, such switching models for condemnation versus negotiated settlement highlight the benefits of avoiding condemnation proceedings in R/W acquisition. Estimation results illuminate the relative importance of various parcel and owner attributes, impacting the nature and cost of acquisition, and enhancing opportunities for R/W staff to identify more contentious properties and establish more reliable budget estimates. / text

The feasibility and success of petroleum development projects depend to a large degree on well construction costs. Well construction cost estimates often contain high levels of uncertainty. In many cases, these costs have been estimated using deterministic methods that do not reliably account for uncertainty, leading to biased estimates. The primary objective of this work was to improve the reliability of deterministic well construction cost estimates by incorporating probabilistic methods into the estimation process. The method uses historical well cost estimates and actual well costs to develop probabilistic correction factors that can be applied to future well cost estimates. These factors can be applied to the entire well cost or to individual cost components. Application of the methodology to estimation of well construction costs for horizontal wells in a shale gas play resulted in well cost estimates that were well calibrated probabilistically. Overall, average estimated well cost using this methodology was significantly more accurate than average estimated well cost using deterministic methods. Systematic use of this methodology can provide for more accurate and efficient allocation of capital for drilling campaigns, which should have significant impacts on reservoir development and profitability.