Technical Cost Modeling Research Articles

A conceptual cost estimation model for the pre-design stage of road projects using multiple regression analysis

Purpose The current estimation practice in construction projects greatly needs upgrading, as there has been no improvement in the cost overrun issue over the past 70 years. The purpose of this research was to develop a new multiple regression analysis (MRA)-based model to forecast the final cost of road projects at the pre-design stage using data from 43 projects in New Zealand (NZ). Design/methodology/approach The research used the case study of 43 completed road projects in NZ. Document analysis was conducted to collect data, and statistical tests were used for model development and analysis. Findings Eight models were developed, and all models achieved the required F statistics and met the regression assumptions. The models’ mean absolute percentage error (MAPE) was between 21.25% and 22.77%. The model with the lowest MAPE comprised the road length and width, number of bridges, pavement area, cut and fill area, preliminary cost and cost indices change. Research limitations/implications The model is based on road projects in NZ. However, it was designed to be able to adapt to other contexts. The findings suggest that the model can be used to improve traditional conceptual estimating methods. Past project data is often stored by the project team but rarely used for analysing and forecasting purposes. This research emphasises that past data can be effectively used to predict the project cost at the pre-design stage with limited information. Originality/value No research was conducted to adopt cost modelling techniques into the conceptual estimation practice in the NZ construction industry.

A bibliometric review of the statistical modelling techniques for cost estimation of infrastructure projects

PurposeCost overrun in infrastructure projects is a constant concern, with a need for a proper solution. The current estimation practice needs improvement to reduce cost overruns. This study aimed to find possible statistical modelling techniques that could be used to develop cost models to produce more reliable cost estimates.Design/methodology/approachA bibliographic literature review was conducted using a two-stage selection method to compile the relevant publications from Scopus. Then, Visualisation of Similarities (VOS)-Viewer was used to develop the visualisation maps for co-occurrence keyword analysis and yearly trends in research topics.FindingsThe study found seven primary techniques used as cost models in construction projects: regression analysis (RA), artificial neural network (ANN), case-based reasoning (CBR), fuzzy logic, Monte-Carlo simulation (MCS), support vector machine (SVM) and reference class forecasting (RCF). RA, ANN and CBR were the most researched techniques. Furthermore, it was observed that the model's performance could be improved by combining two or more techniques into one model.Research limitations/implicationsThe research was limited to the findings from the bibliometric literature review.Practical implicationsThe findings provided an assessment of statistical techniques that the industry can adopt to improve the traditional estimation practice of infrastructure projects.Originality/valueThis study mapped the research carried out on cost-modelling techniques and analysed the trends. It also reviewed the performance of the models developed for infrastructure projects. The findings could be used to further research to develop more reliable cost models using statistical modelling techniques with better performance.

Using interpretive structural modelling and quality cost model to solve project completion delay in shipyard case study in PT X

Purpose – This research proposes an alternative method to solve completion delay issue and optimized the strategy using ISM technical method and Quality Cost Model application. Design/methodology/approach – Data was acquired from 120 questions from company key persons that involved in project for last 5 years. The instruments processed using ISM analysis to measure the relationship among causes, then using Quality Cost Model to solve. Findings – This research shows that factors of late payment from client, delays in bank credit processing, bad weather, and design changes by owners are the root causes of delays. Further analysis using the Theory of Constraint (TOC) shows that financial constraint issues influence the decreased throughput and increase operating cost. Further management use five sequential steps to improve the management and P-A-F models as one of strategic cost management tools applied to the root causes to determine the optimum cost strategy to solve the problem. Research limitations/implications – This research was conducted using a case study method, and the conclusion related to problem and root cause may not be applied totally to other companies, but the framework may be applicable. Future research can investigate other issue using TOC framework, combine TOC with other models to conduct root cause analysis, and the COQ model implementation in shipyard management. Practical implications – This research demonstrates that management can use Interpretative Structural Modelling (ISM) analysis to determine the root cause, then analyse and overcome the issues using TOC framework. COQ model approach to sharpening the decision, and prioritize the resources allocation. Originality/value – This research combine ISM, TOC, and PAF Quality Cost Model approach for decision making which can be a management tool in strategic cost management.

Cost Modelling for Recycling Fiber-Reinforced Composites: State-of-the-Art and Future Research

Fiber-reinforced composites, such as carbon and glass fibers, are widely used across various industries. This is mainly a result of their outperforming properties in contrast with traditional materials. As a response to the environmental legal enforcement of the recycling of composite materials, several recycling methods such as mechanical, thermal, and chemical recycling, have been developed. Despite various merits, these recycling methods still face challenges, such as the heterogeneity of material, the quality of the recycled product, the high cost of recycling, and a lack of an established market. Since, in many cases, the financial aspect tends to be the major barrier to recycling composites, the appropriate cost modelling of the recycling process requires urgent consideration. To the knowledge of the authors, there is no prior research efforts on the reviewing of cost modelling techniques on composites recycling. Cost modelling research projects for different recycling technologies, with their findings and limitations, are sought from the literature and reported in this paper. It is found that recycling techniques still cannot compete with traditional landfilling in terms of cost, and are dependent on fiber recovery rates and plant capacities. Following a comprehensive literature review, research gaps are identified to formulate the research directions in this field.

Size of CO2 matters on the metal affinity in aqueous solution

There is currently great interest in the utilisation of CO2, which has served as an essential tool for chemical conversion. Here, ultrafine bubblised form of CO2 (CUB) with an average size of 147 nm was doped onto activated carbon fibre (ACF) for the green heavy metal uptake in aqueous solution. As a counterpart, a non-bubblised size of CO2 sample (C-ACF) was also investigated. A CUB-treated sample (N-ACF) experienced a 22.53% decrease in the specific surface area, but a 26.81% increase in acidity as compared to ACF. This implies that CUBs could successfully introduce oxygen contents on the carbonaceous surface. Despite the different synthesis processes, the general adsorption trends of the samples were spontaneous and endothermic in nature. Under all circumstances, the maximum adsorption capacity was secured in the order of N-ACF > C-ACF > ACF. Further, special emphasis on the increased randomness via CUBs was discussed in detail. The use of CUBs also demonstrated a level of environmental feasibility by securing >75% of regeneration efficiency after three trials. Lastly, technical cost modelling revealed that CUBs could be a cost-viable option compared to traditional strong acids from a long-term macroeconomic viewpoint.

A Cost Model for 3D Woven Preforms

Lack of cost information is a barrier to acceptance of 3D woven preforms as reinforcements for composite materials, compared with 2D preforms. A parametric, resource-based technical cost model (TCM) was developed for 3D woven preforms based on a novel relationship equating manufacturing time and 3D preform complexity. Manufacturing time, and therefore cost, was found to scale with complexity for seventeen bespoke manufactured 3D preforms. Two sub-models were derived for a Weavebird loom and a Jacquard loom. For each loom, there was a strong correlation between preform complexity and manufacturing time. For a large, highly complex preform, the Jacquard loom is more efficient, so preform cost will be much lower than for the Weavebird. Provided production is continuous, learning, either by human agency or an autonomous loom control algorithm, can reduce preform cost for one or both looms to a commercially acceptable level. The TCM cost model framework could incorporate appropriate learning curves with digital twin/multi-variate analysis so that cost per preform of bespoke 3D woven fabrics for customised products with low production rates may be predicted with greater accuracy. A more accurate model could highlight resources such as tooling, labour and material for targeted cost reduction.

PARAMETRIC COST MODELLING OF COMPONENTS FOR TURBOMACHINES: PRELIMINARY STUDY

AbstractThe ever-increasing competitiveness, due to the market globalisation, has forced the industries to modify their design and production strategies. Hence, it is crucial to estimate and optimise costs as early as possible since any following changes will negatively impact the redesign effort and lead time.This paper aims to compare different parametric cost estimation methods that can be used for analysing mechanical components. The current work presents a cost estimation methodology which uses non-historical data for the database population. The database is settled using should cost data obtained from analytical cost models implemented in a cost estimation software. Then, the paper compares different parametric cost modelling techniques (artificial neural networks, deep learning, random forest and linear regression) to define the best one for industrial components.Such methods have been tested on 9 axial compressor discs, different in dimensions. Then, by considering other materials and batch sizes, it was possible to reach a training dataset of 90 records. From the analysis carried out in this work, it is possible to conclude that the machine learning techniques are a valid alternative to the traditional linear regression ones.

An efficient cost estimation framework for aerospace applications using Matlab/Simulink

The ability to estimate costs and process times at the early stage of a design phase is of great importance to the product development process, enabling selection of the most suitable design and manufacturing concepts. Therefore, herein an efficient framework is developed, utilising appropriate process and feature based cost modelling techniques in a MATLAB/SIMULINK environment. The sophisticated structure of the cost tool, using the drag and drop approach of predefined SIMULINK blocks, enables the rapid cost modelling of complex aerospace assemblies. The capabilities of the developed framework are demonstrated through analysis of a novel air-intake structure for single aisle aircraft.

From aviation to automotive - a study on material selection and its implication on cost and weight efficient structural composite and sandwich designs

The design of a composite material structure is often challenging as it is driven by the trade-off between lightweight performance and production costs. In this paper, the boundaries of this design trade-off and its implications on material selection, geometrical design and manufacturability are analysed for a number of design strategies and composite material systems. The analysis is founded on a methodology that couples weight-optimization and technical cost modelling through an application-bound design cost. Each design strategy is evaluated for three levels of bending and torsional stiffness. The resulting stiffness-versus cost-range together constructs the design envelope and provides guidelines on the suitability and improvement potential of each case. Design strategies researched include monolithic, u-beam-, sandwich-insert- and sandwich-stiffened plates. Considered material systems include carbon-, glass, recycled carbon-, lignin- and hemp-fibre reinforced composites. Optimized sandwich designs are shown to have lowest design cost. Glass-, recycled carbon-, lignin- and hemp-fibre reinforced composite materials are all shown to reduce costs but at lower stiffness performance. Ultimately, the case study demonstrates the importance of early structural design trade-off studies and material selection and justifies introducing novel fibre systems in low-cost applications of moderate stiffness levels.

Effective Cost Models for Predicting Web Query Execution Cost

Classical query optimizers rely on sophisticated cost models to estimate the cost of executing a query and its operators. By using this cost model, an efficient global plan is created by the optimizer which will be used to execute a given query. This cost modeling facility is difficult to be implemented in Web query engines because many local data sources might not be comfortable in sharing meta data information due to confidentiality issues. In this work, an efficient and effective cost modeling techniques for Web query engines are proposed. These techniques does not force the local data sources to reveal their meta data but employs a learning mechanism to estimate the cost of executing a given local query. Two cost modeling algorithms namely: Poisson cost model and Exponential cost model algorithms are presented. Empirical results over real world datasets reveal the efficiency and effectiveness of the new cost models.

Trade-off study of a variation aware determinate wing assembly against a traditional assembly strategy

The present study introduces a trade-off framework to evaluate assembly concepts to make informed decisions for aircraft wing structures. This includes (1) the design of the assembly concepts and the estimation of the probability of achieving specific Assembly Key Characteristics, (2) the estimation of the associated costs for each assembly concept using technical cost modelling in combination with Monte Carlo simulation techniques to deal with the uncertainty of the input cost and process parameters and (3) the formulation of the decision matrix to assess the alternative concepts. The suggested trade-off concept can easily be expanded to include weight and performance criteria. Results for a 4m generic composite wing indicated that both conventional and determinate assembly can be successfully implemented with high value probabilities to achieve the predetermined assembly key characteristics.

A review of Additive Manufacturing technology and Cost Estimation techniques for the defence sector

“Additive Manufacturing” (AM) is a promising technology which will provide major advantages to Defence Support Service providers, given its ability of delocalised manufacturing near the point of use. The technology is gaining increasing interest due to its disruptive potential. AM groups together a wide range of different approaches which have the ability to convert a 3D file into a physical product by depositing layer upon layer of material. AM is still under development and considered an immature technology. This immaturity provides high level of uncertainty around key indicators such as time and cost. These indicators represent also key decision variables to evaluate AM and compare it with traditional manufacturing. This review paper represents an investigation of existing knowledge on AM and aims to present to the reader the various AM approaches with a detailed focus on the most applicable technologies to Defence Support Services. The paper is structured as follows, firstly the various technologies of AM and their economic aspects are presented, secondly the cost modelling techniques are investigated and finally a discussion is carried out. The contribution of this paper is to present to Defence Support Service stakeholders the various AM technologies and cost modelling techniques for measuring the product or service cost.

Competitive-Cost Analysis: Cost-Modeling Techniques

The second in a series on competitive-cost analysis, this note provides a general discussion of four specific tools that will further assist in analyzing cost drivers for competitive analysis. These techniques include teardown analysis, public data sources, scale curves, and utilization curves. Excerpt UVA-OM-1255 Rev. Aug. 9, 2018 Competitive-Cost Analysis: Cost-Modeling Techniques Competitive-cost analysis, a method for analyzing the cost structures of two competing companies, represents a strategic application of cost modeling. The first note in this three-part series on competitive-cost analysis (see also UVA-OM-1254 and UVA-OM-1256) identified the basic conceptual framework and principles for developing accurate and comprehensive cost models with four categories of cost drivers: design, facility, geography, and execution. This framework, coupled with cost-modeling techniques, can help the operations analyst or consultant achieve the quantitative rigor needed to ensure solid operations decisions at the strategic and tactical levels. This note discusses four tools that can be used to analyze cost drivers: teardown analysis, public data sources, scale curves, and utilization curves. The final note provides step-by-step guidance on estimating scale curves and calculating utilization impact. Teardown Analysis Teardown analysis consists of the physical disassembly and piecemeal analysis of a complete product. Common among engineering organizations, the typical teardown analysis looks at competitors' products to track new features or design choices that could be applied to the company's own products. For example, for many years General Motors (GM) maintained a facility in Detroit that dedicated more than 50,000 square feet to the display of disassembled vehicles from competitors. Engineers from across the company visited the facility (known internally as the “Mona Lisa Center”) to examine specific parts such as the brake system or seat assembly. Such information can prove particularly useful in quantifying the design-driven costs in a competitive-cost analysis. . . .

Cost and performance prospects for composite bipolar plates in fuel cells and redox flow batteries

Carbon–polymer-composite bipolar plates (BPP) are suitable for fuel cell and flow battery applications. The advantages of both components are combined in a product with high electrical conductivity and good processability in convenient polymer forming processes. In a comprehensive techno-economic analysis of materials and production processes cost factors are quantified. For the first time a technical cost model for BPP is set up with tight integration of material characterization measurements.

Manufacturing cost relationships for vacuum bag-only prepreg processing

Vacuum bag-only prepregs enable the out-of-autoclave manufacture of high-performance composite structures and increase the material, part, and process selection space. However, manufacturing choices involve economic as well as technical considerations. To understand these relationships, we developed a technical cost model that captures the distinctive characteristics of vacuum bag-only prepreg processing (including vacuum-induced air evacuation and resin cure) and estimates the costs associated with materials, equipment, and labor. We applied the model to realistic manufacturing cases and used a parametric study to evaluate the effects of part characteristics, material use efficiency, and cure efficiency. The results indicate that prepreg cost, part size, prepreg waste, and the air evacuation capacity of the material have the strongest influence on part costs and demonstrate that cost modeling can guide efforts to improve or optimize processing by identifying the most economically valuable modifications.

Environmental and economic evaluation of cathode ray tube (CRT) funnel glass waste management options in the United States

The end-of-life waste management of cathode ray tube (CRT) funnel glass is a concern due to the high lead content (22%) within the glass. Inappropriate and insufficient waste management methods can lead to both health and climate impacts. This paper evaluates five waste management options: hazardous waste landfill, municipal waste landfill, pyrometallurgy, closed-loop recycling, and hydrometallurgy from environmental and economic standpoints. Environmental impacts are analyzed using two life-cycle assessment (LCA) methodologies: CML2001 and Eco-Indicator 99. Economic feasibilities are analyzed using the technical cost modeling (TCM) method and the cost, revenue, and profits associated with each waste management option are compared. Results show that discarded CRT funnel glass transportation has a significant effect on both the LCA and TCM results. By taking into account the transportation impact, all waste management options result in greenhouse gas emissions and reduced profit. A sensitivity analysis shows that the profit of closed-loop recycling, pyrometallurgy, and hydrometallurgy options all decrease with increases in transportation distance, while the hydrometallurgy option is less sensitive to the distance than the other two options. LCA results show that closed-loop recycling corresponds to the lowest human health and global warming impacts, followed by pyrometallurgy and hydrometallurgy. Landfill options would generate the most environmental impact. Closed-loop recycling, pyrometallurgy and hydrometallurgy generate more profits (110–450$/ton) than the landfill options (45$/ton). All in all, pyrometallurgy and hydrometallurgy are the most feasible recycling processes for implementation in the United States. Closed-loop recycling is not feasible because the CRT glass market in the U.S. has become obsolete. Overall, pyrometallurgy appears to be the most environmentally friendly and economical CRT funnel glass waste management option. However, the hydrometallurgy option represents the lowest human health impact due to minimized lead emissions. This option also has greater opportunity for process improvement and is more geographically flexible including the potential to be executed on-site, which allows this novel option the opportunity to become more competitive than the pyrometallurgy option if properly implemented.

The Role of Risk Analysis to Support Cost Models for Digital Preservation

Cost can be viewed as the amount required to resource inputs into an activity, and there will usually be a need to evaluate these inputs against the outcomes or benefits. Cost modeling techniques exist in many areas, to help to calculate and anticipate the costs of a given activity.However, there are areas where there is still insufficient knowledge about potential costs, and this is relevant for the domain of digital preservation. Particularly in this area, costs can only be understood in relation to benefits, and the benefits of investing in digital preservation have to be assessed against the potential threats that organizations face. For example, an analysis of the risks of format obsolescence or of a failure of business continuity should motivate organizations to undertake digital preservation when it becomes evident that the potential loss of value of not doing so overcomes the cost.In order for cost models to be useful, it is critical that they are linked to an analysis of the risks in the given domain. Risk analysis should be the foundation of cost modeling so that all costs can be traced back to a specific set of threats that are applicable to the relevant domains and contexts. For some domains where extensive risk analysis has already been done and the benefits are well defined, this may be fairly straightforward. For other domains it might be more difficult. That is the case of digital preservation, where the costs and benefits are not currently widely and well understood but there is also anxiety about not engaging with digital preservation. Many organizations struggle to understand its value and the reason for this is that there is an insufficient focus on the role of risk in decision-making and preservation planning.The European Commission's FP7 funded 4C project aims to address a number of issues that relate directly to the cost determinants of digital preservation, one of the most important being an assessment of risk. The objective is to define a clearer economic landscape within which organizations can operate with confidence and where commercial and community-driven organizations can provide solutions that are reliable and effective, but also economic, timely and sustainable. Large memory and archiving institutions are dealing with an ever increasing amount of digital data and there is a concomitant need for scalable and effective solutions and services to emerge that enable them to tackle that challenge. Medium and smaller organizations, as also entities in the private sector, face different types of challenges and a diversity of solutions are required. The cost of digital preservation needs to be understood through a number of different lenses. Benefits, value and sustainability are three different perspectives that must influence cost but a fundamental understanding of risk – and risk in relation to organizational mission – is of crucial importance. This can bring a new view to digital preservation, making it possible to analyze scenarios and take decisions based on perceptions of objective added value, and not only as objective costs and subjective values.

Method for control of the make-to-order manufacturing system on the base of earning power assessment

A key requirement for the make-to-order (MTO) manufacturing companies to remain competitive is the ability to assess incoming orders in terms of performance and to determine the best orders that they should accept. In this paper, we propose a method to control the entire production process, from customer enquiry up to product delivery, for the MTO manufacturing systems. In practice, decisions on order acceptance and on production planning are often made separately. Sales department is responsible for accepting orders, while the production department is in charge of production planning for implementation of accepted orders. The method proposed in this paper aims to facilitate the connection between the two departments by an integrated control based on the earning power evaluation. The main problems for a MTO manufacturing system manager, i.e. those related to order acceptance and machine control, are solved by the new control method. The solutions are highlighted by presenting the conceptual flowchart of the proposed method, followed by a case study, where three time and cost modeling techniques—namely analytical, neural, and k-NN regression techniques—are applied. The models of earning power at operation, job, and order level are further built and analyzed. The results show that the method could lead to a significant increase of the manufacturing system performance.

Towards the derivation of an integrated process cost-modelling technique for complex manufacturing systems

Cost modelling is used to support business decisions, especially, when the objective is to remain competitive on price and be able to realise outputs at low cost. Many researchers and industrialists have proposed and experimented with different cost-modelling techniques with a view to influencing design and production decisions at an early stage of the development process. This has led to cost-modelling methods which have been broadly classified in this paper as qualitative and quantitative. The paper identifies current best practice cost-modelling techniques and their performance in complex and dynamic manufacturing environments. The review served as a platform to support the recommendation for an integrated cost-modelling methodology. The integrated methodology is based on the strengths of cost engineering, enterprise modelling, system dynamics and discrete event simulation modelling techniques. The method can help in the redesign and re-engineering of products and processes for better cost and value indications; support investment decision analysis; help determine appropriate business and manufacturing paradigms; influence ‘make, buy or outsourcing’ decisions and serve as a key process improvement tool.

Cost modelling in polymer composite applications: Case study – Analysis of existing and automated manufacturing processes for a large wind turbine blade

Cost modelling is typically one of the first steps in the design and development of a new or existing product and can show clear avenues for effective manufacturing. This paper provides an overview of existing cost modelling techniques and details the process term technical cost modelling (TCM), which is a combined parametric and process flow simulation method used widely throughout the manufacturing industry where historical data is either not available or does not exist. A focus is drawn on the manufacture of a 40m wind turbine blade with the effects of part size, production volume, materials costs and tooling being detailed. A case study is presented which investigates the cost effectiveness of a range of existing manual production methods (hand-lay prepreg, VI, LRTM) and compares this to automated manufacturing (ATL, AFP, overlay braiding). ATL and AFP are shown to reduce manufacturing costs by up to 8% despite the high capital costs associated with automated equipment. The cost centres are isolated and clearly indicate the dominance of materials and labour. Material deposition in the tool is only one of a string of labour intensive processes in the manufacture of a large wind turbine blades and a holistic automated blade manufacturing approach is perhaps required to see the true labour saving benefits.