Project Cost Estimation Research Articles

Development and implementation of cost control strategies in oil and gas engineering projects

This review delves into the development and implementation of cost control strategies in oil and gas engineering projects, an area critical for maintaining project viability and profitability amidst fluctuating market conditions. Effective cost control is essential in the oil and gas sector, where projects are often capital-intensive and subject to economic and operational uncertainties. This review examines various cost control methodologies and their application throughout the project lifecycle, from initial planning and budgeting to execution and closure. The paper highlights key cost control strategies, including detailed project cost estimation, budget forecasting, and variance analysis. It discusses the use of advanced project management tools and technologies, such as software for real-time cost tracking and predictive analytics, which enhance decision-making and financial oversight. The review also covers the importance of risk management practices in identifying and mitigating potential cost overruns, emphasizing the role of contingency planning and risk assessment in maintaining financial control. Case studies demonstrate how successful implementation of these strategies can lead to significant cost savings, improved project efficiency, and enhanced financial performance. The challenges associated with cost control, including dealing with unexpected price fluctuations, scope changes, and regulatory compliance issues, are also addressed. Solutions to these challenges, such as adopting flexible budgeting techniques and leveraging data-driven insights, are discussed. The review concludes with recommendations for refining cost control practices in oil and gas engineering projects, including the need for continuous monitoring and adjustment of cost control measures, integrating cost management with overall project strategy, and fostering collaboration among project stakeholders to ensure alignment and accountability.

Retraction Note: Energy financing, energy projects retrofit and energy poverty: a scenario-analysis approach for energy project cost estimation and energy price determination.

Retraction Note: Energy financing, energy projects retrofit and energy poverty: a scenario-analysis approach for energy project cost estimation and energy price determination.

Human-animal contact to inform zoonotic disease risk across gradients of agricultural land use change in the Central River Region (CRR) of The Gambia (ZooContact): a formative study.

Pilot studies are important initial steps in research, providing a preliminary assessment of the practicality, feasibility, and potential challenges of a proposed study. This study attempts to assess the feasibility, practicality, and acceptability of a study that integrates a human-animal contact (HAC) questionnaire, animal biodiversity survey using acoustic analysis, and zoonotic disease investigation in animals among rural households in the Central River Region (CRR) of The Gambia. The pilot study revealed granular insights that would otherwise go unnoticed, providing vital information that directly guided the design and implementation of the subsequent full-scale study on zoonotic disease risk. A pilot study was conducted in five villages in the CRR of The Gambia. Community sensitization was carried out together with the village leadership, followed by a familiarization tour of the study setting. Questionnaire-based interview was conducted among participants (n = 50) randomly selected to assess the acceptability and reliability of the questionnaire. The feasibility and acceptability of biodiversity surveys and animal sampling were assessed using verbal inquiries from participants and community leaders. The recruitment rate was 96%, and most participants, 50 out of 52, were willing to participate without compensation for lost time during interviews. For animal sampling, 45 out of 50 participants were willing to allow the study team to sample blood and feces from their animals without any form of incentive. All five village heads agreed to the usage of sound recorders to be placed within their community for animal biodiversity assessment. For the survey effort, one field assistant interviewed 25 participants per week. It took a total of 1 h to complete an interview, including random household selection, consenting, and questionnaire interview. The pilot study confirmed the feasibility of the research and informed the design of the larger study. Key parameters, such as community access, acceptability, recruitment success, and logistical requirements, contributed to robust sample size calculations and realistic project cost estimates. Additionally, the study enabled the research team to familiarize themselves with the communities and refine the methods for the full study.

Solving Construction Project Delays as SDGS: Evidence from Indonesia

Objectives: For the service provider, the contract will be terminated by the Government, and it will be noted that they cannot participate in project tenders in the coming year. This study analyzes Service Providers who need resource readiness to complete the Project Schedule to Build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation as SDGs Theoretical Framework: The theory used is project management by Kerzner (2013), cost management stages by expert Gunn (2017), and risk management to be effective by Santosa (2009). Methods: The method is descriptive qualitative. Data analysis by conducting interactive analysis, data reduction steps, data presentation, and drawing conclusions or verification. Results and Discussion: This study indicates that the project work schedule must be completed according to the mutually agreed agreement letter. The Regional Government must coordinate and communicate with service providers so that they can complete the project by the Agreement, especially on blocklist sanctions against service providers and the Implementation of statutory provisions on construction services, risk management, and project financing management. Conclusions: Applying the provisions of laws and regulations regarding Construction Services by implementing the terms of the agreement, apply risk management to the ad hoc project selection committee and the Public Works Department so that the risks of slow projects can be anticipated, and Implementing Funding and Time Management with resource planning with careful project cost estimation, cost budgeting, and cost control of changes to the project budget and Implement the project schedule according to the plan.

Analyzing The Causes of Project Failure and Cost Overruns in Building Construction Industry by Using a Mixed-Methods Approach

This study investigated the reasons for project failures and cost overruns in building construction. The building construction industry is well known for chronic issues such as fragmentation, cost overruns, poor working conditions, and insufficient quality, all of which result in project failure. Project failure and cost are the two most essential indicators of success in a construction project because they have an equal impact on all project participants, both favorably and negatively. These problems have been evident for many years across the global construction industry, requiring the identification of the primary causes to address these challenges. The use of both quantitative and qualitative approaches was important, as it made it easier to accomplish the overall goal of solving the problem because quantitative data were collected via surveys and qualitative data were collected through interviews. Data was gathered from 104 team members in Pakistan's building construction industry. The top five reasons for project failure were poor project management, poor design, frequent design changes, design errors, bureaucracy, corruption, poor quality, and poor site management. The top five reasons for cost overruns were poor start-up planning, poor project cost estimation, poor weather conditions, political situations, and the economic instability of the country. Minimizing these factors can contribute to a greater probability of project success and overall improvement in the construction industry.

Comparative Analysis of Traditional Methods and Building Information Modeling (BIM) in Construction Project Cost Estimation

Abstract: Building Information Modeling (BIM) has revolutionized the construction industry by providing digital images of the physical and functional aspects of the site. This article explores the use of BIM in project management and compares it to traditional methods. The study focused on parameters such as efficiency, cost, accuracy, and coordination. Research shows that BIM increases efficiency, accuracy, and coordination while reducing costs and risks. However, challenges remain, such as developing regulations and reaching consensus on requirements among stakeholders. Despite these challenges, the article concludes that BIM has the potential to transform project management.

External quality assurance of cost estimates in major public projects: empirical evidence on cost performance

PurposeValue creation for society from public projects requires that the overall benefits exceed the use of taxpayers' money. At the same time, cost overruns in public projects are a well-documented feature in the literature, but practical guidance on reducing the extent and magnitude of overruns is rare. In 2000, Norway introduced a governance regime that includes mandatory external quality assurance (QA) of cost estimates for major public projects. This paper compares the cost performance of public projects on each side of this QA scheme.Design/methodology/approachWe use an original dataset covering 1,704 projects from 2000 to 2021, reported first-hand from Norwegian public agencies. We apply quantitative methods in the form of descriptive statistics, regression models, and statistical testing of hypotheses to answer our research questions.FindingsThe mean cost overrun across projects in our dataset is smaller than several previous international studies have reported. We find no statistical support for different cost performances between QA and non-QA projects. Secondly, cost overruns seem to vary between different public sectors. A third finding is a small development with lower cost overruns over time for the non-QA projects, and we raise the question of whether the QA scheme has contributed to overall learning effects. The fourth finding is that cost deviations are quite independent of project size.Originality/valueThe paper offers novel insights for decision-makers and researchers on the effects of external quality assurance on cost performance in public projects.

Applying Building Information Modelling (BIM) Technology in Pre-Tender Cost Estimation of Construction Projects: A Case Study in Iran

The pre-tender cost estimation serves as the foundation for determining the project cost in the early stages and is crucial for all parties involved in the tendering process. It is expected to be highly accurate. However, industry surveys have advocated that in the Iranian construction industry, the pre-tender estimated costs of construction projects are not sufficiently accurate during the bidding stage. Building information modelling (BIM) technology is a modern digital tool deployed in the construction industry that has seen substantial growth of application. It employs useful tools in different sectors and has extended its involvement in various stages of the project lifecycle, including feasibility studies, planning, design, construction, and operation and maintenance. This study examines and assesses the status of BIM development in Iran for its applicability in the pre-tender cost estimating process in construction projects. The findings of this study indicate that while there is a limited number of Iranian building projects’ BIM models that possess the required quality and capabilities for BIM-based cost estimation, the results obtained are more precise when compared to existing manual methods. Additionally, utilising BIM-based cost estimation significantly reduces the time required for this process by enhancing the speed of cost estimation operations. An innovative evaluation framework for assessing the quality and functionalities of BIM models is presented, which improves the accuracy of cost estimation before the bidding process in Iran’s construction industry. The research findings demonstrate the enhanced accuracy and effectiveness of BIM as compared to conventional approaches. It also suggests the incorporation of AI technology for model evaluation, which has the potential to become an established global industry standard.

Cost Monitoring and Management Algorithms in the Construction Process of Building Projects

Construction project cost estimation is an essential activity in construction-based fields; it offers a valuable source for the project feasibility studies and the design plan comparisons, and the accuracy can directly influence project investment decisions. A successful implementation of project cost forecasts makes it easier to control and manage project costs. Therefore, this paper presents the Ladybug Reptile Search Algorithm_ Deep Maxout Network (LRSA_DMN) (LRSA_DMN) to estimate construction costs. Additionally, LRSA is included to correct DMN weights. Furthermore, Bootstrap scheme is used to augment data and use this data to input the DMN for cost estimation. In addition, features are selected using a Weighted Correlation Coefficient to choose the best features for further processing. The test results show that LRSA_DMN performs better regarding MSE, RMSE, and Accuracy by 0.092, 0.371, and 0.907, respectively

Examining factors influencing delay of construction projects in Tanzania: A case of Gerenzani- Mbagala BRT road

This study examined the factors influencing the delay in the Gerezani-Mbagala BRT road construction project in Dar es Salaam. Specifically, the study examined client and consultant related factors that resulted in the delay in road construction in the study area. The study was guided by resource-based theory. The study used a descriptive research design and adopted purposive and stratified sampling techniques to select 50 members of the sample of the study. On the other hand, a questionnaire and interview tools were used to solicit information from the respondents. Additionally, the appropriate model for data analysis was the logistic regression model. The findings showed that limited funds provided by the client and poor communication had statistically significant associations with project delays in the Gerezani-Mbagala BRT construction project. Also, the results revealed that a delay in approving major changes and a lack of experience among the consultants had a statistically significant influence on the delays in the Gerezani-MbagalaBRT construction project. The study further revealed that delays in payments from the client and rework due to errors made by the construction personnel were significantly associated with project delays in the Gerezani-Mbagala BRT construction project. The study concludes that client-related and consultantrelated significantly caused the delays in the Gerezani-Mbagala BRT construction project. The study recommends that the client should provide enough time to produce project briefs and other feasibility studies, as this would lessen the impact of inaccurate project cost estimation, unforeseen site circumstances, and slow site clearances on the delivery of the construction project.

Design and economic implications of using steel fibers in elevated slabs of multi‐story buildings

AbstractThis paper presents a comprehensive comparison between conventional reinforced concrete (RC) and steel fiber‐reinforced concrete (SFRC) slabs. Twenty‐two‐way rectangular RC and SFRC slabs are designed with varying dimensions, aspect ratios, and boundary conditions, following verified international standards to compare the steel quantities in a unique study. SFRC slabs with larger aspect ratios and discontinuous edges required significantly higher steel percentages than square slabs, as the random three‐dimensional distribution of steel fibers suited the load distribution pattern of square slabs. To further conduct a detailed design and economic feasibility case study on a realistic building model, two 12‐story buildings are computationally designed with RC and SFRC alternatives. The results indicate that SFRC slabs required approximately 25% more steel than RC slabs due to the uniform distribution of steel fibers throughout the section. Project cost and time estimates were conducted based on standard productivity manuals and cost databases in two distinct economies, India and the USA. Despite the higher steel requirements, the 12‐story SFRC building showed time savings of 34.1 days (5.44%) and cost savings of 4.88% and 1.27% when constructed in the USA and India, respectively. The results are compared with limited available data in literature. In conclusion, the study suggests that SFRC slabs in multi‐story buildings could be more economically favorable in countries with higher labor costs.

Comparison in terms of Material Quantity Between Non-Seismic and Seismic Design for Selected Buildings in Malaysia

Almost all buildings in Malaysia were previously designed for non-seismic loading. As such, the need to consider seismic load poses challenges for the engineers and project owners. In order to enlighten the stakeholders on the effect of adopting seismic design, the impact on building material cost and quantities must be investigated in advance. Although many studies have been conducted, the use of hypothetical building models and not considering the actual soil factors in Malaysia may yield unrealistic results. As such, this study is conducted with the aim to evaluate the change in the material quantities of the main frame members using six existing building models subjected to peak ground acceleration of 0.16g and situated on soil type D. The analysis, design and taking-off were conducted with the aid of Tekla Structural Designer software. The results showed significant increase in terms of the material quantity required for the main frame members when seismic design was considered. The increase in the concrete volume and reinforcement tonnage was calculated to be in the range of 6.92% to 404.86% and 3.23% to 563.94%, respectively. The development of high base shear force, the amplification of the seismic force by the soft soil, and relatively stringent detailing in DCM were identified as the contributing factors. With a broader spectrum of results, the stakeholder can anticipate the increase in the material cost for adopting seismic design that can be useful for design submission and project cost estimation.

Directions for the formation of «City Intelligent models» using artificial intelligence for the post-war reconstruction of historical buildings

Addressing the limitations of current digital simulations for historical buildings, this paper suggests a specific technical task for the development of a simulation analysis platform based on City Intelligent Modelling (CIM). The objective is to establish a systematic approach for digitally maintaining and managing historical dwellings. The technique presented in this paper focuses on constructing sophisticated parametric models that offer numerous modelling benefits, allowing for convenient updates to the Historic Building Information Modelling (HBIM). The text discusses various applications and integrations of Building Information Modelling (BIM) in urban planning, construction projects, and historic building renovations. CIM is presented as a comprehensive digital platform that visually represents cities, aiding urban planners in decision-making for sustainable development. The text delves into the use of advanced analytical tools within CIM for diverse data analysis, predictive modelling, and simulation to forecast trends. The focus shifts to the evolution of BIM, progressing from 3D to 5D models, influencing construction project management and cost estimation. The integration of BIM in historic building projects is explored, emphasising the challenges and proposing innovative solutions using HBIM. The paper also introduces the concept of Infrastructural Building Information Modelling (InfraBIM) in construction management, incorporating Virtual and Augmented Reality for enhanced visualisation.

Hybrid approach for cost estimation of sustainable building projects using artificial neural networks

Abstract Inaccurate estimation in sustainable construction projects is a significant challenge for appraisers, particularly when data and knowledge about the projects are lacking. As a result, there is a need to use cutting-edge technology to solve the issue of estimation inaccuracy. Iraq’s productivity estimates are now made using outdated, ineffective methodologies and procedures. In addition, it is essential to implement cutting-edge, quick, precise, and adaptable technology for productivity estimation. This study’s major goal is to calculate the overall costs of sustainable buildings using the cutting-edge technique known as artificial neural networks (ANNs). For Iraq’s construction industry to handle projects successfully, ANNs must be used as a new technology, a methodology developed to estimate the overall costs of sustainable construction projects. In this study, the process of cost estimation was modeled using ANNs. Investigations of a number of examples involving the creation of ANNs have also been made, including network design and internal elements and how much they impact the effectiveness of models built using ANNs. Equations were developed to determine structural productivity. These networks were shown to have extremely strong predictive power for both accounting coefficients (R) (93.33%) and the overall costs of sustainable construction projects, with a prediction accuracy of 87.00 and 93.33%, respectively.

Cost Management Practices and Performance of Ministry of Education Funded School Construction Projects in Marigat Sub County

Cost approaches to management are necessary for a construction project to operate more efficiently. This study looks at the intricate relationships that exist between cost-control strategies and the success of initiatives to develop the county of Marigat's educational infrastructure. This research attempts to determine the critical connections between cost management strategies and construction project results in light of the challenges associated with successfully completing projects within budgetary limits. The Marigat Sub County Ministry of Education Office reports that 23 out of 32 school construction projects—or 71% of the total are either stopped or falling short of expectations. Therefore, the problem addressed in this study is the significant of cost management practices employed in school construction projects and their influence on construction project performance within Marigat Sub County. The study's overall goal was to examine how cost management practices affect the performance of ministry of education-funded school construction projects in Marigat Sub County. Its specific goals are to evaluate the impact of project resource planning, project cost estimation, and project schedule planning on these construction projects, as well as the impact of each on the ministry of education-funded school construction projects in Marigat Sub County. The findings of the study contributed to existing research by giving insight and evidence-based knowledge regarding cost management practices on school construction projects and how this involvement influences the successful completion and performance school projects. The scope of this research was focused on 132 school projects funded by the Ministry of Education in Marigat Sub County, Baringo. The research adopted a descriptive survey design. The 132 educational programmes in Marigat Sub County that are financed by the ministry of education was the target population. The Yamane formula was used to determine the sample size of the respondents given the total population and the desired level of confidence to get 99 school projects, then a random sampling technique was used to select those 99 school projects from the target population. The study used a questionnaire as data collection tool that was administered to project managers who are school principals. Analysis of data was both descriptive and inferential statistics. The mean score of key performance indicators of project resource planning, cost estimation, cost budgeting, and cost control were above 3.5 out of a maximum of 5 respectively indicating that there was involvement of cost management practices in public school construction projects. The regression model predicts that project resource planning, project cost budgeting and project cost control leads to a .154, .208 and .225 increase in project performance respectfully while project cost estimation leads to .116 decrease. In conclusion, the researcher found that cost management practices influence the performance of ministry of education-funded school construction projects in Marigat Sub County. It is therefore recommended that managers of public-school projects to ensure there is proper cost management practices in undertaking of school construction projects.

Developing two robust hybrid models for predicting tunnel deformation in squeezing prone grounds

The ground deformation under squeezing conditions has a considerable impact on the tunnel excavation process. In this study, we utilize a combination of particle swarm optimization (PSO) and the Entropy Weight Method (EWM) optimization algorithms to optimize the hyperparameters of Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms. This optimization process aims to accurately predict tunnel deformation in squeezing prone grounds, utilizing a dataset derived from 263 tunnel case histories. In the initial step, the database underwent processing utilizing the DBSCAN method to eliminate outlier data. Subsequently, XGBoost and RF algorithms were applied within the Python environment. The optimal hyperparameters for each model were then determined through two methods: PSO and EWM. The overburden depth (H), tunnel diameter (D), support stiffness (K), and rock mass quality index (Q) serve as inputs for the tunnel deformation estimation models. The performance evaluation of the developed models, based on 10-fold cross-validation, using three statistical indices (Normalized Root Mean Square Error/NRMSE, Coefficient of Determination/R2, and Variance Accounted For/VAF), shows that the proposed XGBoost-PSO model accurately predicts tunnel deformation with acceptable performance (R2 = 0.922, NRMSE = 0.344, and VAF = 91.675). Moreover, the results regarding the importance of the input parameters suggest that the rock mass quality index (Q) holds the most significant influence, while the tunnel diameter (D) exhibits the least impact on tunnel deformation in squeezing prone grounds. This study can be a reference for predicting tunnel deformation in the squeezing prone grounds, as well as estimating the severity of the squeezing phenomenon based on deformation. It aids in estimating project costs, selecting an appropriate support system, and determining the necessary methods to mitigate the risk of squeezing.

A Review - Factors Affecting on Time, Cost and Quality of Construction

Abstract: The primary goal of this study is to assess and explore time, cost, and quality management within the construction industry. The purpose of the study is to identify factors that impact time, cost, and quality management in construction projects. Quality stands out as a crucial aspect of all projects, and the success of construction projects hinges significantly on the performance of quality. However, accomplishing this objective is undeniably a challenging task. This study specifically investigates the factors that influence the control of cost and time in construction projects. The aim is to propose recommendations that can assist stakeholders in achieving enhanced cost and time performance in construction projects. The study acknowledges the intricate nature of balancing these key elements and strives to contribute valuable insights for improving overall project outcomes in the construction industry. This study is limited to the perspective of an appropriate sample of professionals in the construction industry. The data collection method involves the use of questionnaires and interviews, which will be subject to descriptive statistical analysis utilizing percentages, mean scores, and frequency of collected data. The primary factors influencing time, cost, and quality in a construction project were identified as planned and scheduled deficiencies, fraudulent methods, kickbacks, and the absence of clear evaluation standards. The research aims to scrutinize the factors that have both positive and adverse effects on construction projects. The study recommends that the construction team work diligently to ensure effective management of time, cost, and quality in construction projects. The objective of this study is to analyze how those involved in project teams perceive time, cost, and quality management on construction projects. Conclusions are drawn, and recommendations are made regarding time, cost, and quality management estimates for construction projects. In the construction industry, the concept of risk management is a less popular technique. There are three main stages in the systematic approach to risk management in the construction industry. A questionnaire, developed based on identified factors, was used to gather the opinions of construction experts. Quality is a critical aspect of any project, especially in construction. The success of construction projects is largely determined by the quality of work. Unfortunately, the construction industry is facing quality issues that result in ineffective and inefficient projects, leading to cost overruns, delays, and excessive rework. To address this issue, a research study was conducted to examine the factors that have positive and negative impacts on construction projects. A questionnaire was developed to gather feedback from construction experts, and statistical analysis tools such as chisquare and weighted mean method (WMM) were used to rank the significance of these factors. The definition of quality can vary depending on the perspective of those defining it. Some see it as meeting specific requirements, while others view it as delivering value for the price paid. For construction companies, quality is about satisfying customers and fulfilling their needs while staying within budget. Quality is an important factor in construction projects, as it can lead to cost overruns and delays. Quality control (QC) and quality assurance systems are established to meet specific requirements. In the construction industry, QC can be seen as achieving client satisfaction, managing costs, and allowing enough time to achieve the desired level of quality. An international standard organization (ISO) has developed a quality assurance system to improve quality and address quality-related issues. The ISO 9001 series has been created to apply to all types of organizations.

An Improved Convolution Neural Network-Based Fast Estimation Method for Construction Project Cost

At present, most network models do not fully consider the prior information on construction project cost, and do not do much research to find out more information or effectively utilize the information the find on construction project cost; conversely, some previous networks mainly consider the depth of the network for the reconstruction results. In addition, there is no detailed discussion on the selection of loss functions for various algorithms, and some common error loss functions are directly used. In view of these shortcomings, a fast estimation model of construction cost based on an improved convolutional neural network is proposed. The construction project is decomposed according to the project characteristics. The project characteristic factors that have a greater impact on the project cost and the main project quantity are selected and analyzed. Then, the convolutional neural network principle is used to analyze the project characteristic factors, the project cost and main project quantities. We simulate and compare the established convolutional neural network models, verify the usability of the model, and finally get a model with high reliability. The establishment of this model provides a new method for the estimation of project cost and main economic indicators, which can meet the actual work requirements to a certain extent.

Design of Sustainable Construction Cost Estimation System Based on Grey Theory — BP Model

China’s construction industry is developing rapidly, and market investment is out of control. Therefore, accurate and rapid project cost estimation is the focus of the industry. The grey theory system is a method to study the uncertainty problem of little data and poor information. It can excavate different information hidden in the system observation data to achieve correct description and understanding. The research will improve the BP neural network based on grey theory, and verify the exactitude and advantage of the model from performance comparison and empirical analysis. This study can make the project cost forecast more reasonable. Results show that compared with the traditional model, the maximum error value decreased by 0.52, the research model’s maximum mean square error decreased by 0.09, and the variance decreased by 0.13. In the regression analysis, the [Formula: see text]-value of the model fitting was above 0.95, the [Formula: see text]-value of the verification fitting reached 0.9205. The [Formula: see text]-value of the overall fitting reached 0.9475, and the fitting effect was excellent. The convergence speed of the research model is faster than other models, and the fitness value is stable at 1.36. In the empirical analysis, this model can review project cost investment budgets in some areas and reduce project costs. This can improve work efficiency. The model also has certain practical significance for the sustainable development of construction project cost estimates.

Predicting advance rate and cutter life in TBM tunnelling using evolutionary algorithm

ABSTRACT Tunnelling with a Tunnel Boring Machine (TBM) offers several advantages over conventional tunnelling methods when covering long distances, particularly regarding time, safety, and environmental impact. Prior to starting a TBM project, performance analysis is a crucial stage necessary to inform the initial investment decision and project cost estimation. However, this analysis requires extensive fieldwork and laboratory studies. The Advance Rate (AR), calculated from the Utilization Factor (U) – the ratio of excavation time to total project time – is a widely accepted measure of TBM performance. Total project time encompasses various parameters, including boring time, cutter inspection and replacement times, and constant factors like re-gripping, service, and maintenance times. In this study, we employed analytical methods, statistical analysis, and genetic programming approaches to evaluate the AR and thus enhance TBM performance analysis. Gamma tests were conducted to identify interrelated parameters in TBM operations. The results from these tests showed that the Applied Force per Cutter (FN) and penetration values (together forming the Field Penetration Index or FPI) are useful in estimating cutter consumption. While FN can be determined through laboratory tests, its field determination is challenging. We have developed several charts and a function derived from genetic programming to estimate the AR of a TBM. The study demonstrated that this function, formulated using genetic programming, possesses strong predictive capability and can significantly improve TBM performance analysis.