Design Cost Estimates Research Articles

Impact of Building Information Modelling in achieving Sustainable Efficiency

This review paper explores into the impact of Building Information Modelling (BIM) implementation on sustainable efficiency within construction projects. It systematically examines BIM’s influence on sustainable project performance, its utilization in construction organizations, and the identification of barriers and enablers affecting the integration of sustainable practices through BIM, with recommendations to overcome these barriers. Methodologically, the review synthesizes extensive literature on BIM in construction field is conducted through systematic searches across databases like Scopus and Google Scholar from 2006 to 2024. The findings reveal BIM’s transformative role in the construction industry’s digital evolution, enhancing collaboration, design clash detection, cost estimation, and scheduling, with promising potential for environmentally conscious design through its integration with sustainable practices. Nonetheless, challenges such as high adoption costs, expertise limitations, and software compatibility hinder widespread BIM implementation, particularly in sustainability-focused projects. The study underscores the immense potential of BIM in supporting sustainability within construction, emphasizing the necessity for guidance, training, modified business models, and collaborative efforts to unlock its full potential. This review bridges the gap between BIM’s potential and practical implementation, providing insights into leveraging BIM for sustainable construction practices, thereby promising a more environmentally conscious future for the construction industry.

Machine Learning Approach for Early Assembly Design Cost Estimation: A Case from Make-to-Order Manufacturing Industry

Machine Learning Approach for Early Assembly Design Cost Estimation: A Case from Make-to-Order Manufacturing Industry

Product Design Cost Estimation for Make-to-Order Industry: A Machine Learning Approach

This research addresses the need for accurate design cost estimation in the Make-To-Order (MTO) industry. The complexity of product customization is key to differentiation. While many studies focus on manufacturing cost estimation, few explore design cost estimation. To improve the accuracy of design cost estimation, this research proposes a new cost driver based on design features available in Computer-Aided Design (CAD) data. The design feature is analyzed to the actual industry cost using machine learning methods, including Artificial Neural Networks (ANNs) and Support Vector Regression (SVR). The cost drivers identified as significant consisted of twenty-six 3D CAD features and four 2D CAD features. The results showed that the ANN models outperformed the SVR models in correctly estimating product design costs, as evidenced by the high R2values in the training and testing phases. The proposed method allows early identification of cost drivers, a significant advantage at the order initiation stage when detailed design features are often ambiguous. The novelty of this research is the use of 3D CAD technology for cost estimation, which quantifies costs based on product design complexity, providing valuable insights into the impact of design adjustments on costs early in the design process. Doi: 10.28991/ESJ-2024-08-03-022 Full Text: PDF

Reassessment of the Dimensions and Layout of Roadside Canals

Until now, there have been puddles on several sections of the Grand Depok City Boulevard road, which are located in the Sukmajaya and Cilodong Districts. This study aims to review the drainage system at three inundation locations (A, B, and C), which includes layout, runoff discharge, channel design discharge, channel dimensions, culverts, and cost estimation. The results showed that the drainage system was built inadequately, so an outlet channel was needed at location A and culverts at locations A and C. The calculated runoff discharge ranged from 0.16-0.73 m3/second, with a planned channel discharge ranging from 0.38-1.10 m3/sec. With this discharge value, it is necessary to deepen the canal at location A, which was originally 0.5 m to 0.7 m, and to reduce the slope of the canal bottom at location B, which was originally 3% to 2%. The culverts required at location A are 18.5 m long and 0.6 m in diameter, and there are 39 at location C, each 8 m long and 0.2 m in diameter. The estimated total cost is IDR 155,492,000. Construction of canals and culverts should use precast concrete materials and be done at night. Keywords: Reviewing, Roadside channel, Runoff.

Evaluation of the economic implications of varied pressure drawdown strategies generated using a real-time, rapid predictive, multi-fidelity model for unconventional oil and gas wells

Experience has suggested that pressure maintenance in hydraulically fractured reservoirs via lower, more sustained production drawdowns may offer improved cumulative recovery and overall resource extraction efficiency compared to more rapid drawdown approaches aimed at generating high initial production. However, given the inherent variability of oil and natural gas markets, operators pursue production strategies that maximize profitability over resource extraction efficiency. This study focuses on evaluating the implications of contrasting pressure drawdown strategies on the long-term production and resulting economics for a real, producing unconventional gas well in the Marcellus Shale of the Appalachian Basin using a techno-economic analysis approach. Our research combines elements of well-specific horizontal well design, production forecasting, equipment sizing and capital cost estimation, operating cost estimation, and revenue and tax calculations. Gas production forecast outlook scenarios were generated under varying pressure drawdowns using two approaches: 1) a novel physics-informed machine learning workflow and 2) traditional reservoir simulation. A discounted cash flow model was used to evaluate the resulting economic implications for each drawdown scenario—generating output for exploring the coupled effect of factors like the timing and volume of gas production, prevailing economic and market conditions for natural gas, and overall estimated ultimate recovery on profitability metrics such as internal rate of return and net present value. Results show that there is potential to maximize the cumulative gas produced in the specific case study well by employing a lower pressure drawdown. Conversely, the greatest profitability is achieved using rapid drawdown as signified by a small, specific subset of our outlook scenarios. On an averaging basis, we find that the combinations of highest cumulative producing and most profitable scenarios occur under lower drawdowns with long (>40 years) producing timeframes, but require higher relative gas price and lower discounting considerations. The machine learning predictive outlooking capability proved effective for enabling rapid generation of a multitude of scenario forecasts. As a result, a variety of prominent example cases could be generated to strike the balance of greater productivity and economic return given their associated producing features and economic conditions when compared to similar producing scenarios—critical insight that offers improved decision support for unconventional oil and gas operations.

Computational fluid dynamics study of the rear geometry influence on aerodynamic load coefficients of heliostats in stow position

The study of heliostat load coefficients in stow position has become more extensive because of the importance of this scenario in the design process and cost estimation of an entire Concentrating Solar Thermal Power Tower plant. When in stow position, in the presence of high-velocity wind flow, heliostats behavior can be compared to an airfoil; as the air flows at different velocities over the upper and lower sections, significant pressure imbalances need to be considered. This paper presents a Large Eddy Simulation study of how four different geometries in the rear area of a squared heliostat at a horizontal inclination affect the magnitudes of the hinge moment (CMHy), drag (CFx), lift (CFz) and overturning (CMy) coefficients. Results show maximum differences of more than 128% for peak CFx when comparing type A and B geometries at the same 45° wind orientations. Also, for types A and B at β = 180°, peak CMy and CMHy presented differences of 47% and 36%, respectively, between heliostat models. Also, considering force's change in direction (i.e. lift vs downforce), a 219% maximum difference was observed for peak CFz between type A and type D models at β = 45°. The results show how the differences in shapes and size proportions between the front and rear heliostat sections affect the stow position's aerodynamic load coefficients (ALC). It was also observed that the ratio of the chord length to the maximum vertical distance from the rear mirror surface to the farthest point of structure geometry of the heliostat is directly correlated with ALC variations for analyzed heliostats.

BIM Education in Higher Learning Institutions: A Scientometric Review and the Malaysia Perspective

Over the last decade, digital applications and Building Information Modelling (BIM) have been introduced in the construction industry to realize a smart construction ecosystem. However, the construction industry has not completely accepted BIM as a standard, and the concept of using BIM applications in universities has not been thoroughly researched. This paper addresses the first scientometric study of BIM education in universities, identifying the state of BIM education practices, skillsets, and the level of BIM education in universities. The paper used scientometric analysis and the VOSviewer mapping technique to assess the most impactful publication sources with the most important impact on BIM education by searching “BIM Education” and using 250 bibliographic data extracted from the Scopus database from 2011-2020 to identify the existing research gaps and research direction. Second, a structured questionnaire was distributed to 343 Year 2 and Year 3 students from two public and two private Malaysian universities that use BIM in their learning. Descriptive data analysis using cross-tabulation in SPSS and relative importance index (RII) were used to analyze the data. The paper revealed two stages of BIM education research; and identified research gaps in the fields of BIM education, architectural education, e-learning, curriculum and information management. The paper also revealed Revit, Cost X and the Glodon Cubicost software as the most used applications, while the common skillsets are design authoring, modelling, and cost estimation. However, both public and private university students mainly design 3D models at BIM Stage 1. The study recommends that institutions and other stakeholders provide continuous BIM training, purchase BIM software, and integrate BIM into the curriculum of Built Environment higher learning institutions for the next generation to be the generation that uses virtual collaborative platforms

Preliminary Component Design and Cost Estimation of a Novel Electric-Thermal Energy Storage System Using Solid Particles

Abstract Energy storage will become indispensable to complement the uncertainty of intermittent renewable resources and to firm the electricity supply as renewable power generation becomes the mainstream new-built energy source and fossil fuel power plants are phased out to meet carbon-neutral utility targets. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system is projected to have promising cost and performance characteristics to meet the future growing energy storage needs. This paper introduces the system and components required for particle TES to become technically and economically competitive. The system integrates electric particle heaters, particle TES within insulated concrete silos, and an efficient air-Brayton combined-cycle power system to provide power for storage durations up to several days via low-cost, high-performance storage cycles. Design specifications and cost estimation of major components in a commercial-scale system are presented in this paper. A techno-economic analysis based on preliminary component designs and performance indicates that particle TES integrated with an air-Brayton combined-cycle power system has a path to achieve the targeted levelized cost of storage of 5 ¢/kWh-cycle at a round-trip efficiency of 50% when taking low-cost energy-specific components and leveraging basic assets from existing thermal power plants. The cost model provides insights for further development and economic potentials for long-duration energy storage.

Hand Gesture Recognition of Methods-Time Measurement-1 Motions in Manual Assembly Tasks Using Graph Convolutional Networks

ABSTARCT Gesture recognition is gaining popularity in many fields, including gesture control, robotics, or medical applications. However, the technology is barely used in industrial manufacturing processes due to high costs, a time-consuming configuration, and changes in the workflow. This paper proposes a minimally invasive approach to recognize workers' hand motions in manual assembly tasks. The novelty of this approach is the use of only one camera instead of any other sensors and the application of state-of-the-art graph neural networks. The method relies on monocular RGB video data to predict the basic motions of the industry standard motion-time system Methods-Time Measurement-1. Our two-stage neural network composed of hand key point extraction and adaptive graph convolution delivers accurate classification results in real-time. To train and validate the model, we created a dataset containing 22,000 frames of real-world assembly tasks. The data produced by this method in a production line can be used for motion time verification, assembly-line design, or assembly cost estimation. In a use-case study, we show that the proposed approach can generate Methods-Time Measurement analysis tables. These have so far only been accurately created by human experts. Source code: https://github.com/alexriedel1/Hand-Gesture-Recognition-in-manual-assembly-tasks-using-GCN

The Engineering Machine-Learning Automation Platform (EMAP): A Big-Data-Driven AI Tool for Contractors’ Sustainable Management Solutions for Plant Projects

Plant projects, referred to as Engineering Procurement and Construction (EPC), generate massive amounts of data throughout their life cycle, from the planning stages to the operation and maintenance (OM) stages. Many EPC contractors struggle with their projects due to the complexity of the decision-making processes, owing to the vast amount of project data generated during each project stage. In line with the fourth industrial revolution, the demand for engineering project management solutions to apply artificial intelligence (AI) in big data technology is increasing. The purpose of this study was to predict the risk of contractor and support decision-making at each project stage using machine-learning (ML) technology based on data generated in the bidding, engineering, construction, and OM stages of EPC projects. As a result of this study, the Engineering Machine-learning Automation Platform (EMAP), a cloud-based integrated analysis tool applied with big data and AI/ML technology, was developed. EMAP is an intelligent decision support system that consists of five modules: Invitation to Bid (ITB) Analysis, Design Cost Estimation, Design Error Checking, Change Order Forecasting, and Equipment Predictive Maintenance, using advanced AI/ML algorithms. In addition, each module was validated through case studies to assure the performance and accuracy of the module. This study contributes to the strengthening of the risk response for each stage of the EPC project, especially preventing errors by the project managers, and improving their work accuracy. Project risk management using AI/ML breaks away from the existing risk management practices centered on statistical analysis, and further expands the research scalability of related works.

An Enterprise Management Framework for Costs Engineering Estimation Models Based on Scopus Scientometrics. An Aerospace Engineering Case Study

The cutting-edge industrial product creation faces battling goals. There is an additional expenditure need to enhance new product reliability, and nevertheless, an enterprise should reduce product costs to receive the long-term development funds. This conflict resolution depends on a design engineer, who should take into account the future product costs as early, as possible. So, the purpose of this article is to elicit the most widespread cost estimation models at all design stages. I purposely investigate the models' limits to propose their common frame. The research methodology is Scopus scientometrics. First, I elicit the most authoritative reviews on the design cost estimation topic. Then I made the reviews content analysis and summarize the models’ limitations. Findings show that the design cost estimation models significantly vary. They do not eliminate or substitute for each other. Each model is suitable in an appropriate designing process place. Scientometric analysis points that advanced cost estimation models are poorly evolved for enterprise efficiency prediction including the aerospace industry. To overcome these obstacles, I propose an enterprise goal model. This study’s novelty is that a fitting combination of cost estimation models ensures the whole enterprise's economical effectiveness.

Structural Analysis of Factors Influencing the Costs of Facade System Implementation

External facades of buildings and other structures shape the image of every building, creating the architecture of cities. Traditional concrete forms, as a symbol of durability and stability, have been replaced by lightweight enclosures—for example, in the form of aluminium–glass facades and ventilated facades. In this paper, the authors attempt to verify the strength of influence and relations between the identified factors shaping the costs of facade system implementation using structural analysis. On the basis of the collected quantitative and qualitative data obtained as a result of research on design documentation and cost estimates of implemented public buildings, as well as on the basis of interviews conducted among experts, factors which have a real impact on the costs of facade systems in the form of aluminium and glass facades and ventilated facades were identified. The indicated factors were analysed and classified using the method of structural analysis, namely the MICMAC method (refers to the French acronym for Cross-Impact Matrix Multiplication Applied to Classification). Particular influences and relations between factors were examined. Finally, six groups of factors influencing the costs of facade systems were identified, including regulatory factors that do not have a very strong impact on the level of costs, but which show a strong correlation with other factors; determinants that have a very strong impact on the costs; and a group of external factors that show the smallest influence on the estimation of façade cost.

Long-Term Care Insurance: Information Frictions and Selection

This paper conducts a stated-choice experiment where respondents are asked to rate various insurance products aimed to protect against financial risks associated with long-term care needs. Using exogenous variation in prices from the survey design and individual cost estimates, these stated-choice probabilities are used to predict market equilibrium for long-term care insurance. Our results are twofold. First, information frictions are pervasive. Second, measuring the welfare losses associated with frictions in a framework that also allows for selection, it is found that information frictions reduce equilibrium take-up and lead to large welfare losses, while selection plays little role. (JEL D82, D83, G22, I13)

The design and manufacturing of fluidic oscillators for composite aircraft structures

Active flow control devices have been proven to reduce drag and delay stall on commercial aircraft. This leads to lower fuel usage and thus reduced flight costs. However, there is a large uncertainty as to how to integrate active flow control devices into aircraft, specifically those with composite structures. In addition, the cost of manufacturing active flow control devices for large-scale production has not been previously studied. In this article, design concepts for the attachment of a fluidic oscillator to a composite aircraft structure are investigated. A systematic approach from the conceptual design to the final design is performed using different design tools. A cost analysis is performed to select the most cost-effective design configuration based on large volume fluidic oscillator production. Through design validation and cost estimation, the final design is shown to be feasible for large volume manufacturing.

From Chip to Converter: A Complete Cost Model for Power Electronics Converters

The unified knowledge on power converter design and manufacturing technology establishes a powerful tool, where the cost and topology realization can be analyzed simultaneously. This paper collects the design practice and cost estimation of various components in a power electronics converter and unites that to a choice of the assembling and manufacturing processes and resulting cost of the complete converter. The outcome of this work specifies the power converter at predefined power level and cooling condition and demonstrates the cost drivers of the complete unit depending on production volumes. As a case study, the cost of an inverter for a full electric or hybrid vehicle application is estimated and the results are compared with figures available in the literature, yielding the conclusion that the validity of such figures is highly dependent on production volumes and power levels. The essence of this paper is a set of general, reliable, and fast design models and production charts, in accordance with realistic cost estimates for the sake of system optimization and development of cost effective electric drives from small series to large volumes.

Allowance for variability of rock mass characteristics along the line of underground excavations in design calculations and cost estimation

Allowance for variability of rock mass characteristics along the line of underground excavations in design calculations and cost estimation

BUILDING INFORMATION MODELING (BIM) ROLES IN THE MALAYSIAN CONSTRUCTION INDUSTRY

Building Information Modeling (BIM) represents a new paradigm in the Malaysian architecture, engineering, and construction (AEC) industry. BIM technology provides virtual models (including 3-D models) to generate a building’s entire lifecycle. The model can also be used for analyzing design clashes, project scheduling, cost estimation, and facility management. The use of BIM in construction projects can reduce time to develop a project, reduce construction cost, and increase project quality. This paper aims to explore roles of BIM in the Malaysian construction industry. Semi-structured interviews were conducted with project consultants and BIM consultants involved in two government projects. The projects were the National Cancer Institute (NCI) Malaysia and Sultan Ibrahim Hall (formerly known as the Multipurpose Hall of Universiti Tun Hussein Onn Malaysia, or UTHM). The interviews revealed effects of BIM in both projects and potential improvement in implementing BIM in construction projects in Malaysia. A literature review and the interviews revealed that BIM is increasingly used and accepted by construction players in Malaysia, and is expected to grow in future.

A geometric reasoning approach to hierarchical representation for B-rep model retrieval

3D solid model similarity is dependency of many intelligent design applications, such as design reuse, part management, case-based reasoning, and cost estimation. Matching and comparing its intrinsic boundary representation (B-rep) is a critical issue to retrieval. In this paper, we proposed a geometric reasoning approach to generate hierarchy for B-rep model retrieval. We extracted the winged-edge data structure to support series algorithms for underlying geometric reasoning, which is mainly composed of 3 steps to build hierarchy: partitioning, assembling and simplifying. This hierarchical representation is featured with level of detail (LOD) retaining geometric and topological information which is proved to be efficient in both global and partial retrieval. Our approach is based on the standard for the exchange of product information (STEP), which is suitable for data exchange between heterogeneous CAD systems. The result of case studies from prototype implementation demonstrates its effectiveness and efficiency.

Design Manufacturing and Cost Estimation of Camshaft Used In Two Wheeler

The camshaft and its associated parts control the opening and closing of the two valves. The associated parts are push rods, rocker arms, valve springs and tappets. This shaft also provides the drive to the ignition system. The camshaft is driven by the crankshaft through timing gears. Cams are made as integral parts of the camshaft and are designed in such a way to open the valves at the correct timing and to keep them open for the necessary duration. In this project, a camshaft is designed for a two wheeler engine by using theoretical calculations. Cam profile is designed by using the calculations. A 3D model of the Camshaft is created using modeling software Pro/Engineer. For manufacturing cam shaft following manufacturing method are used by Machining, Casting and Forging. From above processes we selected casting processes because it’s used for bulk production. For the manufacture of Camshaft Core and Cavity is to be extracted from the model using manufacturing module in Pro/Engineer. Total Mould base is to be designed for the camshaft which is ready to go for production. CNC Program is to be generated for both core and cavity using roughing and finishing processes. This is also done in manufacturing module in Pro/Engineer. Total cost required for the manufacturing of die is estimated. From this project we will learn a manufacturing method for camshaft. Pro/ENGINEER is the standard in 3D product design, featuring industry-leading productivity tools that promote best practices in design.

BTI and HCI first-order aging estimation for early use in standard cell technology mapping

The performance degradation in digital integrated circuit (IC) caused by BTI and HCI aging effects has increased significantly at each new technology node, as well as their importance in terms of circuit reliability throughout the entire circuit lifetime. This work proposes an aging design cost estimation method to be exploited in standard cell IC design flow. This method must be simple and fast, although not so accurate, to be suitable for the intense interactive process during the technology mapping in the logic synthesis phase. The proposed aging cost has been verified and validated through SPICE simulations carried out over a large number of CMOS gates.