A feature ontology to support construction cost estimating

2003 ◽  
Vol 17 (2) ◽  
pp. 133-154 ◽  
Author(s):  
SHERYL STAUB–FRENCH ◽  
MARTIN FISCHER ◽  
JOHN KUNZ ◽  
KOS ISHII ◽  
BOYD PAULSON
Keyword(s):  
Construction Cost ◽  
Formal Ontology ◽  
Cost Estimating ◽  
Construction Costs ◽  
Building Product ◽  
Product Models ◽  
Current Product ◽  
Feature Based ◽  
Construction Knowledge ◽  
The Cost

Construction cost estimators are confronted with the challenging task of estimating the cost of constructing one of a kind facilities. They must first recognize the design conditions of the facility design that are important (i.e., incur a cost) and then determine how the design conditions affect the cost of construction. Current product models of facility designs explicitly represent components, attributes of components, and relationships between components. These designer-focused product models do not represent many of the cost-driving features of building product models, such as penetrations and component similarity. Previous research efforts identify many of the different features that affect construction costs, but they do not provide a formal and general way for practitioners to represent the features they care about according to their preferences. This paper presents the formal ontology we developed to represent construction knowledge about the cost-driving features of building product models. The ontology formalizes three classes of features, defines the attributes and functions of each feature type, and represents the relationships between the features explicitly. The descriptive semantics of the model allow estimators to represent their varied preferences for naming features, specifying features that result from component intersections and the similarity of components, and grouping features that affect a specific construction domain. A software prototype that implements the ontology enables estimators to transform designer-focused product models into estimator-focused, feature-based product models. Our tests show that estimators are able to generate and maintain cost estimates more accurately, consistently, and expeditiously with feature-based product models than with industry standard product models.

scholarly journals Assessment of Construction Project Cost Estimating Accuracy in Egypt

2021 ◽  
Vol 15 (1) ◽  
pp. 290-298
Author(s):  
Ahmed H. Ibrahim ◽  
Lamiaa M. Elshwadfy
Keyword(s):  
Construction Project ◽  
Relative Weight ◽  
Control Process ◽  
Construction Cost ◽  
Cost Estimate ◽  
Assessment Model ◽  
Success Factor ◽  
Cost Estimating ◽  
Construction Project Cost ◽  
The Cost

Background: The accuracy of the cost estimate is a key success factor for any construction project. It is the base for an effective tendering process. It can also be considered as the cornerstone of the cost control process. Objective: This paper aims to develop a model that can be used to assess the expected cost estimating accuracy of construction projects. This model is named as Construction Cost Estimate Accuracy Index (CCEAI). Methods: A questionnaire survey that contains fifteen factors clustered into four categories was carried out among 90 experts based on the construction cost estimate. Only sixty-six questionnaires were returned. The Analytical Hierarchy Process (AHP) was used to identify the relative weights of the different cost estimates. Results: The questionnaire results were analyzed using the AHP technique to calculate the relative weight for each of the input factors and categories. A Construction Cost Estimating Accuracy Assessment model (CCEAI) was developed based on the calculated relative weights. Then, three projects were used as case study applications to check the validity of the proposed model. The results showed that the CCEAI model is greatly reliable in predicting the expected accuracy of the cost estimate. Conclusion: The results of this research and the developed model are very important and can be considered as a powerful tool to predict and improve the expected accuracy of any future construction cost estimate.

scholarly journals Determinants of Building Construction Costs in South Africa

2017 ◽  
Vol 1 (1) ◽  
pp. 8-13
Author(s):  
Abimbola Windapo ◽  
Sunday Odediran ◽  
Alireza Moghayedi ◽  
Abdul Adediran ◽  
David Oliphant
Keyword(s):  
South Africa ◽  
Construction Industry ◽  
Predictive Modelling ◽  
Construction Cost ◽  
Building Construction ◽  
Construction Equipment ◽  
Construction Costs ◽  
Cost Index ◽  
Cross Sectional ◽  
The Cost

Completing project within cost is the target of most clients on any construction project. However, the achievement of this desire is just an imagination in the construction industry, because procurement and execution environments for projects are hostile and unpredictable. This study examines the determinants of building construction costs in South Africa and whether changes in the cost of certain resource factors such as construction equipment, labour and materials can be related to changes in building construction costs. The study employs a longitudinal cross-sectional quantitative research design approach and makes use of literature review and historical data obtained from institutional and governmental databases to identify the determinants. The data collected were analysed using time series analysis to confirm the trends in the cost of the resource factors and its alignment to the changes in building construction cost. After that, it makes use of an appropriate predictive modelling tool or causal analysis in establishing the determinants of construction cost. The results show that the price indices of construction equipment (EI), labour (LI) and materials (MI) have a gentler slope when compared with the Building Cost Index (BCI). It also emerged that later levels of the BCI are significantly and positively related to EI. The findings infer that the key determinant of increase in building construction costs in South Africa is equipment costs. Contractors and public or private sector clients in South Africa must utilize construction equipment optimally on projects, and these pieces of equipment should not be left idle on project sites or plant yards. Appropriate provisions should be made of equipment utilization policies which allow the joint ownership of equipment by contractors to mitigate the problems of cost increases. There are widely unexamined assumptions as to what resource factors are responsible for the growth in building construction costs in South Africa. Also is the similar high risk and uncertainty affecting the South African construction industry as a result of these fluctuations. The results of the study extend the knowledge of the resource factors responsible for building construction costs increases.     

scholarly journals A BIM-DATABASE-INTEGRATED SYSTEM FOR CONSTRUCTION COST ESTIMATION

2021 ◽  
Vol 11 (1) ◽  
pp. 45-59
Author(s):  
Hang Thu Thi Le ◽  
Veerasak Likhitruangsilp ◽  
Nobuyoshi Yabuki
Keyword(s):  
Relational Database ◽  
Cost Estimation ◽  
Database Management ◽  
3D Models ◽  
Construction Cost ◽  
Integrated System ◽  
Information Modeling ◽  
Cost Estimating ◽  
The Cost ◽  
Relational Database Management

This paper presents a building information modeling (BIM)-database-integrated system for estimating the construction costs of building projects. The proposed system consists of four main modules: (1) the relational database management module, (2) the visualized BIM-integrated module, (3) the cost estimation module, and (4) the BIM-integrated report module. The relational database management module is designed to store and update the necessary data, which are extracted from BIM models. The visualized BIM-integrated module assists users in visualizing the complex building elements while performing cost estimating. The cost estimation module computes construction cost components. It can also automatically adjust to the change of the building element parameters while estimating costs. This module can minimize human errors associated with manual data input and calculation. The BIM-integrated report module allows users to access and comprehend the results conveniently. As compared to traditional 2D CAD drawings, the proposed system offers a more efficient methodology for construction cost estimating through 3D models. It can also minimize time, costs, and errors in the cost estimating process for building procurement.

scholarly journals The Analysis of Small Investors’ Demands on a Thermal Insulation System for a Family House: A Case Study

2021 ◽  
Vol 13 (5) ◽  
pp. 2491
Author(s):  
Alena Tažiková ◽  
Zuzana Struková ◽  
Mária Kozlovská
Keyword(s):  
Decision Making ◽  
Thermal Insulation ◽  
Construction Cost ◽  
Environmental Cost ◽  
Multi Criteria Decision Making ◽  
Insulation System ◽  
Insulation Systems ◽  
Small Investors ◽  
The Cost ◽  
Family House

This study deals with small investors’ demands on thermal insulation systems when choosing the most suitable solution for a family house. By 2050, seventy percent of current buildings, including residential buildings, are still expected to be in operation. To reach carbon neutrality, it is necessary to reduce operational energy consumption and thus reduce the related cost of building operations and the cost of the life cycle of buildings. One solution is to adapt envelopes of buildings by proper insulation solutions. To choose an optimal thermal insulation system that will reduce energy consumption of building, it is necessary to consider the environmental cost of insulation materials in addition to the construction cost of the materials. The environmental cost of a material depends on the carbon footprint from the initial origin of the material. This study presents the results of a multi-criteria decision-making analysis, where five different contractors set the evaluation criteria for selection of the optimal thermal insulation system. In their decision-making, they involved the requirements of small investors. The most common requirements were selected: the construction cost, the construction time (represented by the total man-hours), the thermal conductivity coefficient, the diffusion resistance factor, and the reaction to fire. The confidences of the criteria were then determined with the help of the pairwise comparison method. This was followed by multi-criteria decision-making using the method of index coefficients, also known as the method of basic variant. The multi-criteria decision-making included thermal insulation systems based on polystyrene, mineral wool, thermal insulation plaster, and aerogels’ nanotechnology. As a result, it was concluded that, currently, in Slovakia, small investors emphasize the cost of material and the coefficient of thermal conductivity and they do not care as much about the carbon footprint of the material manufacturing, the importance of which is mentioned in this study.

scholarly journals Development of Material Combination Model Considering Economics and Construction Efficiency for G-SEED Certification

2021 ◽  
Vol 13 (6) ◽  
pp. 3535
Author(s):  
Byung-Ju Jeon ◽  
Byung-Soo Kim
Keyword(s):  
Structural Design ◽  
Material Selection ◽  
Selection Model ◽  
Construction Costs ◽  
Seed Certification ◽  
Evaluation Scores ◽  
The Cost ◽  
Material Information ◽  
Business As Usual ◽  
Construction Efficiency

The Korean government proposed a goal to reduce its greenhouse gas emissions by 37% compared to business-as-usual levels by 2030 and launched the Green Standard for Energy and Environmental Design (G-SEED) certification system. The certification requires meeting the required score and material selection with a secured economy and construction efficiency. However, most buildings only focus on obtaining the certification scores instead of choosing economical materials with high construction efficiency. This research focused on developing a material selection model that considers both the construction efficiency and economy of the materials and the acquisition of material and resource evaluation scores from the G-SEED certification. This research, therefore, analyzed actual data to automate the material selection and compare alternatives to using a genetic algorithm to obtain optimized alternatives. This model proposes an alternative to constructability and economy when the required score and material information is entered. When the model was applied to actual cases, the result revealed a reduction in construction costs of about 37% compared to the cost with the traditional methods. The material selection model from this research can benefit construction project owners in terms of cost reduction, designers in terms of structural design time, and constructors in terms of construction efficiency

scholarly journals Hospital Construction Cost Affecting Their Lifecycle: An Italian Overview

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 888
Author(s):  
Leopoldo Sdino ◽  
Andrea Brambilla ◽  
Marta Dell’Ovo ◽  
Benedetta Sdino ◽  
Stefano Capolongo
Keyword(s):  
Healthcare Services ◽  
Construction Cost ◽  
Design Stage ◽  
Quality Healthcare ◽  
Healthcare Facilities ◽  
Early Design Stage ◽  
Hospital Facility ◽  
Italian Context ◽  
The Cost ◽  
Cost Components

The need for 24/7 operation, and the increasing requests of high-quality healthcare services contribute to framing healthcare facilities as a complex topic, also due to the changing and challenging environment and huge impact on the community. Due to its complexity, it is difficult to properly estimate the construction cost in a preliminary phase where easy-to-use parameters are often necessary. Therefore, this paper aims to provide an overview of the issue with reference to the Italian context and proposes an estimation framework for analyzing hospital facilities’ construction cost. First, contributions from literature reviews and 14 case studies were analyzed to identify specific cost components. Then, a questionnaire was administered to construction companies and experts in the field to obtain data coming from practical and real cases. The results obtained from all of the contributions are an overview of the construction cost components. Starting from the data collected and analyzed, a preliminary estimation tool is proposed to identify the minimum and maximum variation in the cost when programming the construction of a hospital, starting from the feasibility phase or the early design stage. The framework involves different factors, such as the number of beds, complexity, typology, localization, technology degree and the type of maintenance and management techniques. This study explores the several elements that compose the cost of a hospital facility and highlights future developments including maintenance and management costs during hospital facilities’ lifecycle.

scholarly journals An Investigation into Factors Influencing Construction Costs Based on Japanese, UK and US Contractor Practice

2012 ◽  
Vol 2 (2) ◽  
pp. 27-35
Author(s):  
Hong Xiao ◽  
David Proverbs
Keyword(s):  
Indirect Costs ◽  
Construction Cost ◽  
Office Building ◽  
Construction Process ◽  
Close Attention ◽  
Construction Costs ◽  
Cost Performance ◽  
Factors Influencing ◽  
Site Design ◽  
The Uk

Construction cost is a major concern to both clients and contractors. Based on a hypotheticalconstruction project (a six-storey concrete framed office building), cost and otherrelated information was collected through a survey of contractors in Japan, the UK and theUS. Using multiple regression analysis it was found that lower overheads, less prefabricatedcomponents, and fewer design variations could reduce construction cost. Overheadslargely represent indirect costs to contractors and if reduced can lead to increased profitlevels and improved competitiveness. The use of prefabricated components may be problematicwhere there are delays in production, insufficient coordination between design andconstruction, and congested transportation on site. Design variations during constructionbring about uncertainties and are disruptive to the construction process. These factorshave paramount impact on construction cost and demand close attention and consideration.Contractors are advised to reduce the costs of their overheads and utilise prefabricationappropriately, while clients and designers should minimise the number of designvariations during construction if better cost performance is desired.

scholarly journals Manufacturability verification through feature-based ontological product models

2012 ◽  
Vol 226 (6) ◽  
pp. 1086-1098 ◽  
Author(s):  
Najam Anjum ◽  
Jennifer A Harding ◽  
Robert IM Young ◽  
Keith Case
Keyword(s):  
Product Models ◽  
Feature Based

scholarly journals UTILIZING SITE CHARACTERISTICS IN NEURAL NETWORK MODELLING OF PERCENTAGE COST-TIME OVERRUN OF BUILDING PROJECTS

2017 ◽  
Vol 8 (1) ◽  
pp. 1-15
Author(s):  
A. O. Ujene ◽  
A. A. Umoh
Keyword(s):  
Neural Network ◽  
Cost Overrun ◽  
Construction Costs ◽  
Network Modelling ◽  
Building Projects ◽  
The Neural Network ◽  
Site Characteristics ◽  
Neural Network Prediction ◽  
The Cost ◽  
Prediction Approach

This study evaluated the site characteristics influencing the time and cost delivery of building projects, determined the range of percentage cost and time overrun and developed a neural network model for predicting the percentage cost and time overrun using the site characteristics of building projects. The study evaluated twelve site characteristics and two performance indicators obtained from records of construction costs, contract documents, and valuation reports of 126 purposively sampled building projects spread across several cities in Nigeria. Analyses were with descriptive and artificial neural network. It was concluded that with fairly favourable site characteristics, cost overrun range reached 77.95% with a mean variation of 44.36%, while time overrun range reached 51.23% with a mean variation of 26.77%. It was found that the accuracy performance levels of 91.93% and 91.43% for the cost and time overrun predictions respectively were very high for the optimum models. Building projects have eight significant site characteristics which can be used to reliably predict the percentage overrun, among which the ground water level, level of available infrastructure and labour proximity around the site are the most important predictors of cost and time overrun. The study recommended that project owners, consultants, contractors and other stakeholders should always use the eight identified site characteristics in predicting percentage cost and time overrun, with more priority on the first three characteristics. The study also recommended the neural network prediction approach due to its prediction accuracy.

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