Proper Cost Estimate, Monitor and Control (CEM&C) are vital for the success of construction projects. Starting from preliminary design to project closing, CEM&C progressively becomes more complex and challenging. Visualization can add another dimension to monitor and control where major deviations can be visually detected and analyzed. However, literature related to visualization in construction and integrating it with cost control is still in its early stages. Building Information Modeling (BIM) can have promising impact in that domain. In this paper, a comprehensive cost estimating and monitoring model is presented. The model is integrated with BIM to provide the user with the capability of visualizing actual cost expended in different building elements and compare it with that budgeted at different time intervals. It provides construction practitioners with vital data that help them in taking appropriate corrective actions in case of any deviation from the budget. An example application is presented to demonstrate the capability and applicability of the model.
The Automation of Critical Path Method using Machine Learning: A Conceptual S...Dr. Amarjeet Singh
This research aims to shed light on the use of machine learning in improving, developing and automating the critical path method, solving its problems, studying this effect and its dimensions, and discussing that from many aspects.
The research is divided into two theoretical and practical parts. The theoretical part is concerned with studying the critical path method and its advantages, problems and challenges, as well as studying machine learning and artificial intelligence and its dimensions, reviewing materials and sources related to this, and then presenting suggestions and future solutions based on this study. As for the practical section, it is a questionnaire that targeted a segment of engineers, in particular, and others who have sufficient experience in both the critical path method and machine learning, and seeking their opinions on both topics.
The result of the theoretical research was 14 theories or proposals that were presented based on the foregoing study. As for the practical questionnaire, a sample of 127 was taken. Through statistical analysis, the results were analyzed and discussed separately, and then a conclusion was drawn regarding them.
'Applying System Science and System Thinking Techniques to BIM Management' Alan Martin Redmond, PhD
Redmond, A. and Alshawi, M. (2017) 'Applying System Science and System Thinking Techniques to BIM Management' Developments in eSystems Engineering, IEEE CELEBRATING 10 YEARS OF ADVANCING E-SYSTEMS ENGINEERING RESEARCH AND DEVELOPMENT, Paris, France, 14th – 16th June 2017,
Earned Value Management (EVM) is a technique
that forecasts the project giving an early warning of cost &
schedule. It not onely measures the project performance but also
measure the progress of the schedule. It is an effective tool to
measure cost, schedule & performance of the project. The EVA is
useful in various fields such as IT, Industries and Construction
companies etc.
The value of Earned Value Analysis (EVA) is dependent on
two key areas i.e. Precise Cost information and pragmatic
progress of project. If these two key areas are efficient then
benefit of the project will definitely get valued. This paper
summarizes the evolution, basic terminologies of Earned value
Analysis and effective use of it in the construction industries by
MS Project. There are many ways to implement EVA in the
construction project. MS Project is a tool to determine the EV
and its parameters in an efficient way with accuracy and within
time constraints.
Estimation maturity model using function pointsBhupinder Singh
While there are many models for measuring maturity of software organizations, little attention has been paid to factoring estimation maturity into these models. This true even for CMMI, which is an otherwise very a rigorous model.
This presentation suggests adopting an Estimation Maturity model suggested by Galorath and using the Function Point estimation technique to achieve this goal.
An Automated Input Data Management Approach for Discrete Event Simulation App...IJERA Editor
Slipforming operation’s linearity is a source of planning complications, and operation is usually subjected to bottlenecks at any point, so careful planning is required in order to achieve success. On the other hand, Discrete-event simulation concepts can be applied to simulate and analyze construction operations and to efficiently support construction scheduling. Nevertheless, preparation of input data for construction simulation is very challenging, time consuming and human prone-error source. Therefore, to enhance the benefits of using DES in construction scheduling, this study proposes an integrated module to establish a framework for automating the generation of time schedules and decision support for Slipform construction projects, particularly through the project feasibility study phase by using data exchange between project data stored in an Intermediate database, DES and Scheduling software. Using the stored information, proposed system creates construction tasks attribute [e.g. activities durations, material quantities and resources amount], then DES uses all the given information to create a proposal for the construction schedule automatically. This research is considered a demonstration of a flexible Slipform project modeling, rapid scenario-based planning and schedule generation approach that may be of interest to both practitioners and researchers.
The Automation of Critical Path Method using Machine Learning: A Conceptual S...Dr. Amarjeet Singh
This research aims to shed light on the use of machine learning in improving, developing and automating the critical path method, solving its problems, studying this effect and its dimensions, and discussing that from many aspects.
The research is divided into two theoretical and practical parts. The theoretical part is concerned with studying the critical path method and its advantages, problems and challenges, as well as studying machine learning and artificial intelligence and its dimensions, reviewing materials and sources related to this, and then presenting suggestions and future solutions based on this study. As for the practical section, it is a questionnaire that targeted a segment of engineers, in particular, and others who have sufficient experience in both the critical path method and machine learning, and seeking their opinions on both topics.
The result of the theoretical research was 14 theories or proposals that were presented based on the foregoing study. As for the practical questionnaire, a sample of 127 was taken. Through statistical analysis, the results were analyzed and discussed separately, and then a conclusion was drawn regarding them.
'Applying System Science and System Thinking Techniques to BIM Management' Alan Martin Redmond, PhD
Redmond, A. and Alshawi, M. (2017) 'Applying System Science and System Thinking Techniques to BIM Management' Developments in eSystems Engineering, IEEE CELEBRATING 10 YEARS OF ADVANCING E-SYSTEMS ENGINEERING RESEARCH AND DEVELOPMENT, Paris, France, 14th – 16th June 2017,
Earned Value Management (EVM) is a technique
that forecasts the project giving an early warning of cost &
schedule. It not onely measures the project performance but also
measure the progress of the schedule. It is an effective tool to
measure cost, schedule & performance of the project. The EVA is
useful in various fields such as IT, Industries and Construction
companies etc.
The value of Earned Value Analysis (EVA) is dependent on
two key areas i.e. Precise Cost information and pragmatic
progress of project. If these two key areas are efficient then
benefit of the project will definitely get valued. This paper
summarizes the evolution, basic terminologies of Earned value
Analysis and effective use of it in the construction industries by
MS Project. There are many ways to implement EVA in the
construction project. MS Project is a tool to determine the EV
and its parameters in an efficient way with accuracy and within
time constraints.
Estimation maturity model using function pointsBhupinder Singh
While there are many models for measuring maturity of software organizations, little attention has been paid to factoring estimation maturity into these models. This true even for CMMI, which is an otherwise very a rigorous model.
This presentation suggests adopting an Estimation Maturity model suggested by Galorath and using the Function Point estimation technique to achieve this goal.
An Automated Input Data Management Approach for Discrete Event Simulation App...IJERA Editor
Slipforming operation’s linearity is a source of planning complications, and operation is usually subjected to bottlenecks at any point, so careful planning is required in order to achieve success. On the other hand, Discrete-event simulation concepts can be applied to simulate and analyze construction operations and to efficiently support construction scheduling. Nevertheless, preparation of input data for construction simulation is very challenging, time consuming and human prone-error source. Therefore, to enhance the benefits of using DES in construction scheduling, this study proposes an integrated module to establish a framework for automating the generation of time schedules and decision support for Slipform construction projects, particularly through the project feasibility study phase by using data exchange between project data stored in an Intermediate database, DES and Scheduling software. Using the stored information, proposed system creates construction tasks attribute [e.g. activities durations, material quantities and resources amount], then DES uses all the given information to create a proposal for the construction schedule automatically. This research is considered a demonstration of a flexible Slipform project modeling, rapid scenario-based planning and schedule generation approach that may be of interest to both practitioners and researchers.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
The objective of this paper is to present and discuss the main obstacles and benefits of the use of the Earned Value Analysis in projects, including factors to be improved and implemented during the project plan and actions to be taken while the project is accomplished and controlled. Also, through a real case study in civil construction field, the applicability of the technique is faced with a theoretical reference, in order to identify aspects of the applicability of the tool tested in case study.
The job structure of the bottom (lower Structure) has the weight of the work
amounted to 8% of the total cost of the construction of high
delay in implementation
analysis conducted by using the Relative Important Index (RII) Obtained 15 influential
factors ie Comparison of measurement and prediction, the adequacy of the plan
Specifications, fix and schedules and plans, instrumentation and
monitoring, evaluation of static pole Data , Data collection, soil conditions, scope of
work, Issues, accuracy of data, problem identification, Solution Optimization,
validation projects, Improve communication, skilled workforce. While the resu
the analysis of the case study foundations work efficiency powerboats Obtained results
using PERT of 4.85% and optimization for quality using Six Sigma of 99. 56%.
Risk Contingency Evaluation in International Construction Projects (Real Case...IJLT EMAS
Most construction companies operating in the global construction industry would undertake international projects to maximize their profitability through benefitting from the new attractive markets and reducing the dependence upon local markets. As a result of the nature of construction works the company and project's conditions actually include massive risks and uncertainty. So the risk sensitivity of projects costs should be assessed in a realistic manner. The comprehensive risk assessment method was introduced as a decision making supporting tool to be employed for international constructive projects through applying a risk model that will aid the procedures of evaluating risks and prioritizing such projects and assessing risk contingency value. Both the Analytic Hierarchy Process (AHP), applied for evaluating risk factors weight (likelihood), and FUZZY LOGIC approach, applied for evaluating risk factors influence (Risk consequences) employing software aids such as EXECL and MATLAB software, were used for developing the risk model. The reliability of the developed software has been verified by applications on a real construction projects. The proposed methodology and decision support tool have been proved to be reliable for the estimation of cost overrun resulting from risk on basis of actual final reports of projects. Six actual case studies from different countries were chosen to determine the highest risk factors and to implement the designed models, test their results and evaluate risk cost impact. The proposed models result showed that: the highest and lowest risk contingency percentage of 48 % and 16 % were in Project no (5), (6) respectively in Egypt. On the other hand, the projects no (1, 2, 4,7) in Saudi Arabia, UAE, Libya and Jordan, the risk contingency of 29%, 39%, 20% and 28% respectively. The actual results are close to those of the proposed program.
Review on cost estimation technque for web application [part 1]Sayed Mohsin Reza
Prepared by Sayed Mohsin Reza
Part 1
Source Book: Cost Estimation Techniques for Web Projects
BOOK AUTHOR: EMILIA MENDES UNIVERSITY OF AUCKLAND, NEW ZEALAND
Difference about Web and Software Projects
Introduction to Web Cost Estimation
Accuracy of an Effort Model?
Sizing Web Applications
The Building Information Model track is planned for EVM World this spring. In the last edition of The Measureable News we had a bibliography of BIM papers. Here are some more.
A Study of A Method To Provide Minimized Bandwidth Consumption Using Regenera...IJERA Editor
Cloud storage systems to protect data from corruptions, redundant data to tolerate failures of storage and lost data should be repaired when storage fails. Regenerating codes provide fault tolerance by striping data across multiple servers, while using less repair traffic than traditional erasure codes during failure recovery. In previous research implemented practical Data Integrity Protection (DIP) scheme for regenerating-coding based cloud storage. Functional Minimum-Storage Regenerating (FMSR) codes and it construct FMSR-DIP codes, which allow clients to remotely verify the integrity of random subsets of long-term archival data under a multi server setting. The problem is to optimize bandwidth consumption when repairing multiple failures. The cooperative repair of multiple failures can help to further save bandwidth consumption when multiple failures are being repaired.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
The objective of this paper is to present and discuss the main obstacles and benefits of the use of the Earned Value Analysis in projects, including factors to be improved and implemented during the project plan and actions to be taken while the project is accomplished and controlled. Also, through a real case study in civil construction field, the applicability of the technique is faced with a theoretical reference, in order to identify aspects of the applicability of the tool tested in case study.
The job structure of the bottom (lower Structure) has the weight of the work
amounted to 8% of the total cost of the construction of high
delay in implementation
analysis conducted by using the Relative Important Index (RII) Obtained 15 influential
factors ie Comparison of measurement and prediction, the adequacy of the plan
Specifications, fix and schedules and plans, instrumentation and
monitoring, evaluation of static pole Data , Data collection, soil conditions, scope of
work, Issues, accuracy of data, problem identification, Solution Optimization,
validation projects, Improve communication, skilled workforce. While the resu
the analysis of the case study foundations work efficiency powerboats Obtained results
using PERT of 4.85% and optimization for quality using Six Sigma of 99. 56%.
Risk Contingency Evaluation in International Construction Projects (Real Case...IJLT EMAS
Most construction companies operating in the global construction industry would undertake international projects to maximize their profitability through benefitting from the new attractive markets and reducing the dependence upon local markets. As a result of the nature of construction works the company and project's conditions actually include massive risks and uncertainty. So the risk sensitivity of projects costs should be assessed in a realistic manner. The comprehensive risk assessment method was introduced as a decision making supporting tool to be employed for international constructive projects through applying a risk model that will aid the procedures of evaluating risks and prioritizing such projects and assessing risk contingency value. Both the Analytic Hierarchy Process (AHP), applied for evaluating risk factors weight (likelihood), and FUZZY LOGIC approach, applied for evaluating risk factors influence (Risk consequences) employing software aids such as EXECL and MATLAB software, were used for developing the risk model. The reliability of the developed software has been verified by applications on a real construction projects. The proposed methodology and decision support tool have been proved to be reliable for the estimation of cost overrun resulting from risk on basis of actual final reports of projects. Six actual case studies from different countries were chosen to determine the highest risk factors and to implement the designed models, test their results and evaluate risk cost impact. The proposed models result showed that: the highest and lowest risk contingency percentage of 48 % and 16 % were in Project no (5), (6) respectively in Egypt. On the other hand, the projects no (1, 2, 4,7) in Saudi Arabia, UAE, Libya and Jordan, the risk contingency of 29%, 39%, 20% and 28% respectively. The actual results are close to those of the proposed program.
Review on cost estimation technque for web application [part 1]Sayed Mohsin Reza
Prepared by Sayed Mohsin Reza
Part 1
Source Book: Cost Estimation Techniques for Web Projects
BOOK AUTHOR: EMILIA MENDES UNIVERSITY OF AUCKLAND, NEW ZEALAND
Difference about Web and Software Projects
Introduction to Web Cost Estimation
Accuracy of an Effort Model?
Sizing Web Applications
The Building Information Model track is planned for EVM World this spring. In the last edition of The Measureable News we had a bibliography of BIM papers. Here are some more.
A Study of A Method To Provide Minimized Bandwidth Consumption Using Regenera...IJERA Editor
Cloud storage systems to protect data from corruptions, redundant data to tolerate failures of storage and lost data should be repaired when storage fails. Regenerating codes provide fault tolerance by striping data across multiple servers, while using less repair traffic than traditional erasure codes during failure recovery. In previous research implemented practical Data Integrity Protection (DIP) scheme for regenerating-coding based cloud storage. Functional Minimum-Storage Regenerating (FMSR) codes and it construct FMSR-DIP codes, which allow clients to remotely verify the integrity of random subsets of long-term archival data under a multi server setting. The problem is to optimize bandwidth consumption when repairing multiple failures. The cooperative repair of multiple failures can help to further save bandwidth consumption when multiple failures are being repaired.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Approach To Power Harvesting With Piezoelectric MaterialIJERA Editor
Nowadays, most of the research in the energy field is to develop sources of energy for the future, With oil resources being over, tapped and eventually bound to end, it is time to find renewable Piezoelectric materials are being more and more studied as they turn out to be very unusual materials with very specific and interesting properties. In fact, these materials have the ability to produce electrical energy from mechanical energy, for example, they can convert mechanical behavior like vibrations into electricity. Recent work has shown that these materials could be used as power generators, the amount of energy produced is still very low, hence the necessity to optimize them. The objective of this work is to study the all of the piezoelectric material systems and calculated the possible power generated from it, and a special case to design and build a fully functional floor tile device that when stepped on will generate enough energy to light an LED, The system will be charge a temporary energy storage device, a capacitor bank, and then use this stored energy to power an LED.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Brief Study of Video Encryption AlgorithmsIJERA Editor
Video is a set of images .Video encryption is encrypting those set of images .Thus video encryption is simply hiding your video from prying eyes .Video monitoring has always been in concerned .Multimedia security is very important for multimedia commerce on Internet such as video on demand and Real time video multicast. There are various video encryption algorithm. All have some kind of weakness .In this paper classification of various existing algorithm, its advantages and disadvantages is discussed.
Review of Jobran Khalil Jobran's works from Romantic FeaturesIJERA Editor
Jobran Khalil Jobran great immigrant writer and poet have been known with different view of his contemporary
to romantic poetry text format and reflective language of his time. This great poet had a wonderful impression
in new Arab literature and this caused the creation of a special style which at that time address the entity and
existence by mysticism and kind of intuition retrieved from its receiver view in solution of social ,emotional
and religious situation, as he shined with his myth and other great works. The aim of this article is that the
romantic feature of his works and elegance lyrics was investigated from different view of critics, and that
influence is the presence of woman, especially his mother in his romantic phenomena. This is a propellant and
different factor that we cannot neglect it according to the strategic important impact has had on his careers and
creation of a his world style. Social and environmental conditions changed the route of his career. These
conditions affected him and inevitably reflected them in his poem. If conditions are suitable, the feeling
manifested and appears and the talent shows off in the best way.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Evaluation of Antioxidant Phytochemicals in Different Genotypes of PotatoIJERA Editor
Potato (Solanum tuberosum L.) is considered a natural source of phytochemicals that help lower the risk of chronic diseases. Thus, ascorbic acid, total phenolic content and antioxidant activities of Indian potato genotypes were studied. ‘Kufri Pukhraj’ was the best genotype in terms of nutritional components, since it contained the highest amount of ascorbic acid (19.42 mg/100g), and total phenolic content (68.20 mg GAE/100g). Also ‘Kufri Pukhraj’ had the highest DPPH radical scavenging activity of 67.30%. On the other hand, genotype ‘Kufri Chipsona-1’, most commonly used cultivar for processing, displayed the lowest content of total phenolics (31.30 mg GAE/100g) and total antioxidant activity (28.80%). Correlation analysis between total phenolic content and antioxidant activity (r=0.8502) showed a high degree of correlation indicating that these bioactive components contributes to the total antioxidant activity in potato genotypes.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Performance of RGB and L Base Supervised Classification Technique Using Multi...IJERA Editor
In the present growth of sensor technology is to improve the new chance and applications in GIS. This enhances the technology law a new method that should not focus on real time available products, but it must automatically lead to new ones. The aim of the paper is to make a maximum use of remote sensing data and GIS techniques to access land use and land cover classification in the Kiliyar sub basin sector in palar river of northen part of Tamil Nadu.IRS P6 LISS III is merged data to perform the classification using ERDAS Imaging. The RGB and L base supervised classification was based up on a Multispectral analysis, land use and land cover information‟s (maps and existing reports), which involves advanced technology and complex data processing to find detailed imagery in the study region. Ground surface reflects more radar energy emitted by the sensor from the study region, which makes it easy to distinguish between the water body, hilly, agriculture, settlement and wetland.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Construction Cost Prediction by Using Building Information ModelingIJERA Editor
The increased interest in using Building Information Modeling (BIM) in detailed construction cost estimates calls for methodologies to evaluate the effectiveness of BIM-Assisted Detailed Estimating (BADE) tools in generating detailed construction cost estimates. The focus of this research is on developing a quantified evaluation method to measure the impact of these BADE tools. Further, in order to understand the cognitive details of the estimator, this research also tested and evaluated the impact of the visualization factor and the compound impact of the visualization factor and aggregated calculation factor on the construction cost estimating process.Two cases study were tested, building and bridge. Three methods were applied on each case study,method 1the manual estimating method, method 2 used a BADE tool without a calculation function (i.e., the quantities of the individual building components can be read as properties of the component), method 3 used a BADE tool with calculation functions that allowed the user to directly calculate/aggregate the query results of the BIM database in the MS Excel spreadsheet.Results obtained from the test cases helped to reinforce the reliability of the observations and the evaluation. Four parameters were used to evaluate the performance results individually in the first step: generality, flexibility, efficiency, and accuracy. Then a multiattribute utility model, which took into account the four individual parameters, was developed and used to evaluate the overall performance of BIM assisted estimating versus the performance of the traditional estimating method on quantity takeoffs. The research concluded that the BIM-assisted estimate demonstrated better performance over traditional estimating methods. Both the visualization and aggregation functions of the BADE tool had significant impact on the performance of the detailed estimate.
Assessment of Project Monitoring and Control Techniques in Ondo State Agency ...Dr. Amarjeet Singh
Monitoring and control is an essential process in
construction project management and delivery. It is
therefore imperative for construction companies to employ
the usage of the most effective monitoring and control
techniques available to meet project objectives. This study
examined project management techniques employed by
Ondo State Agency for Road Maintenance and
Construction, a construction company in Ondo State,
Nigeria.The research design that was used for this study is
the survey method where copies of a well-structured
questionnaire were distributed to elicit appropriate
information from respondents. The results showed
thatthere is a relationship existing between the type of
project monitoring and control technique used by a
construction company and project delivery/success and that
the use of Program Evaluation and Review Technique
(PERT) for time/schedule control and Earned Value
Management (EVM) (alongside other monitoring and
control techniques) for cost control as used by the company
are very effective in meeting set project objectives.Based on
the findings, a number of recommendations were made.
Among these are, that monitoring and control units should
be established withinconstruction companies and welltrained workers/professionals should be put in charge of
handling these units and the techniques and tools used
therein.
Advantages and Challenges of Using BIM: a Cost Consultant's PerspectiveMichael Cook
It will be essential for firms to act promptly, in order to meet the government’s
2016 target (BIS, 2011), as well as keeping future fee proposals competitive and not loose -out to ‘early investing’
companies.
Project management tools and techniques- tutorsindia.comTutors India
In this topic, we have discussed the project management tools and techniques. The present article helps the USA, the UK, Europe and the Australian students pursuing their master’s degree to identify the best project management tools and techniques, which are usually considered to be challenging. Tutors India offers UK dissertation in various Domains.
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Cost Effective Methods in Construction Engineeringcivejjour
The economic impact of construction cost overrun is a possible loss of the economic justification for the
project. The financial impact of a cost overrun results in demand for construction investment credits.
Therefore reliable estimates of construction cost are an important aspect to the contemporary construction
companies especially during the conceptual phase of lifecycle management. In this paper a cost-effective
analysis is done using one of the cost effective construction technique called Rat Trap Bond versus Flemish
bond and when estimated with CPWD 2012 schedule of rates it is proved that Low cost techniques such as
rat trap bond provides better cost effectiveness as compared to conventional Flemish bond construction
method.
Cost Effective Methods in Construction Engineeringcivejjour
The economic impact of construction cost overrun is a possible loss of the economic justification for the project. The financial impact of a cost overrun results in demand for construction investment credits. Therefore reliable estimates of construction cost are an important aspect to the contemporary construction companies especially during the conceptual phase of lifecycle management. In this paper a cost-effective analysis is done using one of the cost effective construction technique called Rat Trap Bond versus Flemish bond and when estimated with CPWD 2012 schedule of rates it is proved that Low cost techniques such as rat trap bond provides better cost effectiveness as compared to conventional Flemish bond construction method.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
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BIM-Based Cost Estimation/ Monitoring For Building Construction
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BIM-Based Cost Estimation/ Monitoring For Building Construction Emad Elbeltagi1, Ossama Hosny2, Mahmoud Dawood1 and Ahmed Elhakeem3 1Civil Engineering Department, Mansoura University 2Construction and Architectural Engineering Department, The American University in Cairo 3Civil Engineering Department, Faculty of Engineering-Mataria, Helwan University Abstract Proper Cost Estimate, Monitor and Control (CEM&C) are vital for the success of construction projects. Starting from preliminary design to project closing, CEM&C progressively becomes more complex and challenging. Visualization can add another dimension to monitor and control where major deviations can be visually detected and analyzed. However, literature related to visualization in construction and integrating it with cost control is still in its early stages. Building Information Modeling (BIM) can have promising impact in that domain. In this paper, a comprehensive cost estimating and monitoring model is presented. The model is integrated with BIM to provide the user with the capability of visualizing actual cost expended in different building elements and compare it with that budgeted at different time intervals. It provides construction practitioners with vital data that help them in taking appropriate corrective actions in case of any deviation from the budget. An example application is presented to demonstrate the capability and applicability of the model. Keywords: Cost monitoring and Control, Cost Variances, Cost Estimate, BIM, Visualization.
I. INTRODUCTION
Accurate cost estimate and effective cost monitoring and control are essential elements to construction project success. Project managers need reliable cost estimating systems to initiate budgets and develop financial management plans. Cost estimate can be defined as the process of predicting cost to perform the scope of work specified for a project. The cost estimate level of accuracy depends on the method used, availability of cost data and level of project definition (Jrade 2000). The Association for the Advancement of Cost Engineering (AACE) defines cost estimate as; "A predictive process used to quantify cost and/or price of resources required by the scope of an asset investment option, activity, or project" (AACE International 2011). While Rad (2002) defines it as: "the art and science of using historical data, personal expertise, institutional memory, and the project scope statement to predict the resource expenditure, and total cost of a project".
However, estimating without proper monitoring and control may result in complete project failure. During project construction, procedures for project monitoring, recording and control are essential elements for project managers. Monitoring is the process of tracking various operations during the construction stage. Cost control indicates the direction of the changes in preliminary planning variables compared with actual performance with the aim of avoiding unacceptable variations. Cost control includes “monitoring” costs and recording data, then analyzing the data in order to take appropriate corrective actions before it is too late. Once the project starts; control becomes the major task of the contractor, because contractor’s profit depends to a great extent on the effectiveness of its cost monitoring and control system (Olwan 2004). Project control system indicates the direction of change in preliminary planning variables compared with actual performance (Rozenes et al. 2006). It assures that all changes to the scope baseline are controlled in a structured manner. This prevents the baseline plan from becoming obsolete. Several research have focused on cost and schedule variances (eg., Li 2004). Cheung et al. (2004) developed a web-based system for monitoring the performance of construction Projects. The system measures several performance measures that include: cost, time, quality, health,safety and others to evaluate the performance of project progress. Other researchers focused on describing how to collect the required data to control projects (e.g., Abudayyeh et al. 2001; Navon, and Goldschmidt 2003; Sacks et al 2003; Perera and Imyiyas 2004; Eldin and Lloyd 2005). Hegazy and Abdel-Monem (2012) introduced an e- mail based system for documenting as built information for progress monitoring and analysis. The system facilitates efficient communication and feedback between construction personal and head office.
Building Information Modeling (BIM) is a new technology in the field of CAD, which contains not only geometric data, but can accommodate great amount of engineering data over the lifecycle of a
RESEARCH ARTICLE OPEN ACCESS
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building (Xudong and Jie 2007). It simulates the
construction of the building in a virtual environment.
BIM assists planners in making crucial decisions by
enabling visualization of the details of the
prospective work at any specified time (Chau et al.
2004). When a project is planned and built virtually,
most of its relevant aspects can be considered and
communicated before the instructions for
construction are finalized (Li et al. 2006). According
to Khemlani (2010), BIM is a revolutionary
technology that goes well beyond the design phase to
impact construction and lifecycle management of the
project. BIM can be used in the preconstruction phase
in cost and quantity estimates, and in integration and
coordination among building components and their
scheduling data. It can also be used as a life cycle
information management process for safety planning
(Sulankivi et al. 2010). Elbeltagi and Dawood (2011)
developed a time control model for repetitive
construction projects based on BIM technology.
Sacks et al (2011) developed a matrix that links the
functionalities in BIM with the prescriptive principles
of lean construction. They identified fifty six
constructive interactions between them. Fard et al.
(2009) developed a 4D simulation model based on
time-Lapsed photographs to visualize construction
progress. The authors used color coding images for
progress tracking where different colors were given
to project components based on their progress status.
They claim that color coding provides end users with
more realistic picture of project progress leaving
more time for decision makers to take corrective
actions.
1.1 Problem Statement
Timely and accurate feedback of actual cost
enables project managers to take appropriate
corrective actions that would minimize cost overrun
in a timely manner. As project progress, the process
of construction monitoring and control gets more
sophisticated, complex and challenging due to the
huge amount of information that need to be measured
and analyzed. An effective monitoring and control
system should include a data management system to
cover the large sets of data associated with the
different project components. Accordingly,
developing an integrated visualized cost estimate and
control models to track construction projects
performance would be an important advance in the
area of construction project monitoring and control.
This research aims to introduce a model that
integrates cost estimate and monitoring processes
with the advances in data visualization to provide
decision makers with a tool for better monitoring and
control of their construction projects.
II. INTEGRATED COST ESTIMATE
AND Monitoring Framework
Figure 1 shows the framework of the proposed
model. The framework consists of three interacting
modules; cost estimate and schedule module, cost
monitoring and control module, and BIM module.
The three modules interact together as illustrated in
the figure through the intersected areas of these
modules. The project Work breakdown Structure
(WBS) is used to link the estimate/scheduling (i.e.,
planning) with the BIM where the project was broken
down into a set of activities that are mapped to their
corresponding building components During
construction the actual cost (ACWP) for each
resource/activity is compared with its corresponding
original budget (BCWS) and the Earned Value (EV).
Then, cost variances in the different components are
visualized through the BIM module.
Figure 1: Proposed BIM based Cost Estimate /
Monitoring Framework
Advanced spreadsheet modeling with Visual
Basic for Applications macro programming is
utilized to create the cost estimate model, store actual
progress data and perform cost variance analyses in
addition to, automate the data exchange with BIM to
visualize construction cost progress. In the current
research, BIM is used as a platform of visualization,
quantity takeoffs, counts, and measurements to
perform cost estimate and control then visualize cost
variances. A cost estimation module is developed to
calculate the activities’ direct cost (indirect cost is out
of scope of this research). A mathematical cost
monitoring/control module is also developed to
measure work progress, track resource changes
(quantities, productivities, crews, and costs), and to
perform detailed cost variance analyses (details are in
section 2.2) to enable decision makers take timely
corrective actions. The proposed framework can be
used to help all construction parties to reduce/recover
any deviation, if any, from the original plan.
Figure 2 however shows the framework main
processes. Developing a reasonable Work
Breakdown Structure (WBS) is the first step for
implementation. The WBS is the base for developing
a custom Building Information Model (BIM)
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representing the building. On the other hand, the
WBS is used in preparing the initial project
plan/schedule on any Project Management software
(e.g., MS Project).
Figure 2: Framework Main Process
Quantities, based on the BIM model, are
extracted and exported to a database (e.g., MS
Access) as an intermediate database which is linked
to the cost estimate module/model in the proposed
framework. The cost estimate/control model is
developed using Excel. The model imports the initial
plan/schedule from MS Project to realize project
activities and imports also the matching quantities
from BIM through MS Access then integrates the
resources basic cost data to estimate activities’ time
and cost. The calculated time and cost are exported
back to MS Project to develop the schedule and
determine the BCWS at the project level. Actual
resources data are collected from the construction site
during the construction phase using structured
acquisition forms (e.g., Figure 3 for crew daily time
and cost). The forms are plugged into the
estimate/control spreadsheet model. By comparing
initial cost estimate against actual progress, detailed
cost variances are automatically calculated. Variance
analysis is exported back to the BIM model to allow
the user visual the construction progress by viewing
favorable/unfavorable cost variances in coloring
schemes. The next sections will discuss in details the
proposed model.
Figure 3: Actual Daily Crew Time and Cost Card
2.1 Cost Estimate and Schedule Module
Cost estimate can be viewed as the task of
determining the quantities of work to be performed,
with the production rate and cost of the resources
required to perform that work (Al-Mashta 2010).
Cost estimating process internal steps do not have a
commonly adapted structure. Consequently, experts
and researchers do not adhere to exact specific steps
during the cost estimating process. The preparation of
cost estimate depends mainly on developing a Work
Breakdown Structure (WBS) that breaks down the
project into subsets of items or packages.
Traditionally, cost estimation for building
projects starts with quantification (Sabol 2008).
Quantification is a time consuming task, it consumes
from 50% to 80% of the cost estimator’s time on a
project (Autodesk 2007). In order to develop quantity
takeoffs, estimators typically begin by digitizing the
drawings or doing manual takeoffs. All these
methods introduce the potential for human error and
propagate any inaccuracies there may be in the
original drawings. By using a Building Information
Model instead of drawings, the takeoffs, counts, and
measurements can be generated directly from the
underlying model. Therefore the information is
always consistent with the design. And, when a
change is made in the design, it will automatically
ripple to all related construction documentation and
schedules, as well as all the takeoffs, counts, and
measurements that are used by the estimator.
Preparing of BIM model, based on the WBS that
is previously developed, can reduce the time needed
to achieve a high quality building by improving
design and construction integration and quantity take-off
accuracy. Therefore, it is most beneficial to
convert the design into BIM software to allow
extracting more detailed spatial and material
quantities directly from the building model in a
timely manner. All BIM tools provide capabilities for
extracting counts of components, area and volume of
spaces, material quantities, and to report these in
various schedules. Several software packages are
available in the market (e.g. Revit, Tekla Structure,
Archicad, etc.). Revit is used as the BIM engine for
the current application. Quantity surveying, in the
proposed model, is done by exporting the BIM model
to an Access database file that is then sent to Excel
spreadsheets (core of the cost estimate engine) as
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shown in Figure 4. These quantities are used to
calculate the total project cost estimate.
Figure 4: BIM Manipulation and Data Exchange via
MS Access
The next step is the cost data collection
regarding the direct cost based on historical data or
resource enumeration. Historical data can be
collected from previously executed projects or
obtained from third parties: manufacturers,
subcontractors or database references (e.g. RS Means
in North America). Cost data regarding project
resources are organized in Excel sheets. Finally, data
manipulation or calculation to produce the cost
estimate is performed. Computing is an easy part of
the cost estimate process (although it is prone to
mistakes when done manually). In general it depends
on simple mathematics. By using the powerful data
management features of Excel, simplified
spreadsheets are used to estimate project cost. The
design of spreadsheets involved the setup of several
data lists and establishing the relationships among
them (Figure 5).
2.2 Cost Monitoring Module
The earned value management technique is
considered as a powerful project management tool
that supports the management of project scope, time,
and cost (Leu et al. 2005). Using the earned value
process, contractors can easily compare how much
work has actually been completed with the amount of
work planned to be accomplished. Earned value
provides work progress status, and the relationship of
planning to the actual cost. Jung and Kang (2007)
developed a system to standardize progress
measurement. Shen et al. (2005) developed a scoring
system to measure the environmental performance
done by the contractor. Barraza et al. (2000)
developed a model based on stochastic S-curve to
monitor project performance.
Figure 5: Cost Estimate Module Components
There are three key indicators that are used in
performance measurement: (1) budgeted cost of work
scheduled (BCWS), (2) budgeted cost of work
performed (BCWP), (3) and actual cost of work
performed (ACWP). The performance measurement
computes variances from baseline. Figure 6
represents cost variance analysis breakdown tree
(Adapted from Dawood 2011). Cost variance for the
activity/project is quantified from its three main
resources: material, crew (labor and equipment), and
subcontractor.
Figure 6: Cost Variance Analysis Tree
Figure 7 shows the ACWP and BCWP using a
mirror fashion (in front of each other). For each
activity the ACWPs and BCWPs for the main
resources are shown in addition to the corresponding
CVs (total of eight curves). This representation
provides a better illustration for various CVs related
to an activity and its resources.
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Figure 7: Cost Variance Major Components
Following are the mathematical formulation for
different elements cost variances (Dawood 2011).
Activity-based Cost Variance (CV)
The CV is computed for each activity to show
the deviation of its actual cost from the baseline
estimate. It is the difference between the budgeted
cost of work performed (BCWP) and the actual cost
of work performed (ACWP).
CVi BCWPi ACWPi
Where: i CV is the cost variance for activity i,
i BCWP is the budgeted cost of work performed for
activity i, i ACWP is the actual cost of work
performed for activity i.
The CV is caused due to deviation in the actual
cost of key resources (material, crews, subcontractors
and/or overhead) from those estimated. Therefore,
further analysis has to be performed to define the
reasons for the CV. Consequently, the CV of any
activity can be expressed as:
M crew Sub Over CV CV CV CV CV
Where: CVM, is the variance in the material cost,
CVcrew, is the variance in the crews cost, CVSub, is the
variance in the subcontractor work and CVOver is the
cost variance in the overhead. Overhead cost is
beyond the scope of this research.
Material Cost Variance
Materials are the major component of
construction cost. It contributes to more than half of
the project cost. Material cost variance is the
difference between budgeted material costs and
actual material costs. Material cost variance can be
calculated as follows:
ij ij ij M M M CV BCWP ACWP
Where:
ij M CV is the material cost variance for
material type j in activity i,
ij M BCWP is the budgeted
material cost of work performed;
ij M ACWP is the
actual material cost of work performed.
As shown in Figure 8, material variance may occur
due to changes in quantity and/or changes in unit
price. The following subsections describe the reasons
for variances in the material cost.
Figure 8: Components of Materials Cost Variance
Material Quantity Variance
Material quantity variance (CVM.Q) is the cost
variance that arises due to a change in actual
quantities of consumed materials to perform the work
in any activity (i) from the budgeted quantities.
Material quantity variance can be computed as
follows:
ij
.
. . .
.
ij
ij ij ij
ij
a M
M Q b M a b M
b M
Q
CV C P C
Q
Where:
ij M.Q CV is the material quantity cost
variance for material type j in activity i,
. ij b M C is the
budgeted material cost, . ij b M Q is the budgeted
quantity of materials,
. ij a M Q is the actual quantity of
performed materials to date and
i a P is the actual
completed percent to date.
Material Price Variance
Material price variance (CVM price) is the difference
between the budgeted cost and actual cost for the
quantity of material used. Material price is the cost
per unit quantity (e.g. $/m3). Material price variance
could be computed as follows:
. .
. .
. .
ij ij
ij ij i
ij ij
b M a M
M P b M a
b M a M
C C
CV Q P
Q Q
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Where:
. ij M P CV is the material price cost variance
for material type j in activity i,
. ij a M C is the actual
material costs to data.
Material Quantity-Price Joint Variance
Material quantity-price joint variance is the cost
variance due to the deviation of the budgeted cost and
the budgeted quantity of material used
simultaneously. It can be computed as follows:
. .
. . .
. .
ij ij
ij ij i ij
ij ij
a M b M
M Q P b M a a M
a M b M
C C
CV Q P Q
Q Q
Where:
. ij M Q P CV
is the material quantity-price joint
variance for material type j in activity i
Material cost variance can be calculated by the
summation of material quantity, material price and
material quantity-price joint variances. If the variance
value is positive it will be favorable. If negative, it
will be unfavorable.
Crew Cost Variance
Crew cost variance is the difference between the
budgeted crew cost and actual
cost over a period of time. It could be computed by
the following equation:
ij ij ij C C C CV BCWP ACWP
Where:
ij C CV is the crew cost variance for crew j in
activity i,
ij C BCWP is the budgeted cost for a crew
of work performed,
ij C ACWP is the actual crew
cost of work performed.
Crew cost variance can be attributed to several
factors as shown in Figure 9. It is mainly due to the
following reasons: (1) changing of quantity of work
performed (e.g., m3); (2) deviation of crew rate per
unit quantity (e.g., $/m3); and (3) changing in both
quantity and crew rate (e.g., $/m3). On the other
hand, crew rate variance is mainly due to three
reasons: (1) variance in production rate (e.g.,
hour/m3); (2) variance in cost per hour ($/hour); and
(3) variance in both production rate and cost per
hour. The following subsections describe crew’s
variances that may rise due to previous reasons.
Crew Quantity Variance
Crew quantity variance is due to the deviation of the
actual quantity performed from the budgeted. It can
be computed as follows:
.
.
ij
ij ij i ij
ij
b C
C Q b a a
b
C
CV Q P Q
Q
Where:
. ij C Q CV is the crew quantity cost variance for
crew j in activity i and
. ij b C C is the crew’s budgeted
cost.
Figure 9: Components of Crews/Subcontractors Cost
Variances
Crew Rate Variance
Crew rate variance is due to the difference between
crew’s actual cost and crew’s budgeted cost per unit
of measure. Crew rate is the crew’s cost per unit of
quantity performed (e.g., $/m3). Crew rate variance
can be computed as follows:
. .
.
ij ij
ij ij i
ij ij
b C a C
C R b a
b a
C C
CV Q P
Q Q
Where:
. ij C R CV is the crew rate variance for crew j in
activity i,
. ij a C C is the actual crew cost to date.
Crew Quantity-Rate Joint Variance
Crew quantity-rate joint variance is due to a variance
in rate and a variance in quantity, simultaneously.
Crew joint variance can be computed as follows:
. .
.
ij ij
ij ij i ij
ij ij
a C b C
C Q R b a a
a b
C C
CV Q P Q
Q Q
Where:
. ij C Q R CV
is the crew quantity-rate joint
variance for crew j in activity i.
Crew rate variance can be divided into three types:
(1) crew production rate variance; (2) crew cost per
hour variance; and (3) crew production rate cost per
hour joint variance.
Crew Production rate Variance
Crew production rate variance occurs when the actual
production rate differs from budgeted value. Crew
production rate is reported in hours per unit quantity
(e.g., hour/m3). Crew production rate variance can be
computed as follows:
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. . . . ij
ij ij i ij
ij
b
C H b C a a C
a
Chrs
CV C P C
Chrs
.
.
ij ij ij
ij ij i
ij ij ij
b C b a
C P b a
b b a
C Chrs Chrs
CV Q P
Chrs Q Q
Where:
. ij C P CV is the crew production rate cost
variance for crew j in activity i,
ij a Chrs is the actual
number of working hours required to perform the
activity, and
ij b Chrs is the budgeted number of
working hours required to perform the same activity.
Crew Cost per hour Variance
Crew cost per hour variance is due to deviations
that occur when the actual cost per hour differs from
the budgeted cost per hour. Crews cost per hour is
reported in $/hour. Crew cost per hour variance can
be computed as follows:
Where:
. ij C H CV is the crew cost per hour variance
for crew j in activity i.
Crew Production rate Cost per hour Joint Variance
Crew production rate cost per hour joint variance is
due to a variance in the production rate of crews and
a variance in the crews cost per hour at the same
time. Crew production rate cost per hour joint
variance can be computed as follows:
. .
.
ij ij ij ij
ij ij i
ij ij ij ij
b a a C b C
C P H b a
b a a b
Chrs Chrs C C
CV Q P
Q Q Chrs Chrs
Where:
. ij C P H CV is the crew production rate cost
per hour joint variance for crew j in activity i.
Crew cost variance equals crew quantity variance
plus crew rate variance plus crew quantity-rate joint
variance. On the other hand, crew rate variance
equals crew production rate variance plus crew cost
per hour variance plus crew production rate cost per
hour joint variance. If the variance is positive it will
be favorable, the bad thing is to have a negative
variance.
Subcontractor Cost Variance
Subcontractor cost variance is the difference
between the budgeted and actual sub-contractor costs
for a period of time. It could be computed as follows:
i i i S S S CV BCWP ACWP
Where:
i S CV is the subcontractor cost variance,
i S BCWP is the budgeted subcontractor cost of
work performed;
i S ACWP is the actual
subcontractor cost of work performed.
As shown in Figure 9, subcontractor cost
variance is the total variance that can be attributed to
many factors such as: (1) changes in quantity of work
performed (m3); (2) deviation of subcontractor rate
per unit quantity (e.g., $/m3); and/or (3) changes in
both quantity and subcontractor rate. The following
subsections describe the most important elements
resulting in subcontractor variance.
Subcontractor Quantity Variance
Subcontractor quantity variance is due to the
deviation of actual quantity from budgeted quantity
of work performed by the sub-contractor.
Subcontractor quantity variance can be computed as
follows:
. . .
i
i i i i
a
S Q b S a b S
bi
Q
CV C P C
Q
Where: . i S Q CV is the subcontractor cost variance,
and . i b S C is the budgeted sub-contractor cost.
Subcontractor Rate Variance
Subcontractor rate variance is due to the difference
between the subcontractor actual cost and the
subcontractor budgeted cost per unit of measure.
Subcontractor rate is the subcontractor cost per unit
of quantity performed (e.g., $/m3). Subcontractor rate
variance can be computed as follows:
. . .
i
i i i i
i
b
S R b S a a S
a
Q
CV C P C
Q
Where: . i S R CV is the subcontractor rate variance,
. i a S C is the actual Subcontractor cost to date.
Subcontractor Quantity Rate Joint Variance
Subcontractor quantity rate joint variance is due to a
variance in rate and a variance in quantity at the same
time. Subcontractor joint variance can be computed
as follows:
. .
.
i i
i i i i
i i
a S b S
S Q R b a a
a b
C C
CV Q P Q
Q Q
Where: . i S Q R CV is the subcontractor quantity rate
joint cost variance.
Subcontractor rate variance can be divided into three
types; (1) sub-contractor production rate variance, (2)
subcontractor cost per hour variance and (3) sub-contractor
production rate cost per hour joint
variance. These are illustrated next.
Subcontractor Production Rate Variance
Subcontractor production rate variance is due to
deviations between actual and budgeted
subcontractor production rate. Production rate is
reported in hours per each unit quantity (e.g.,
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hour/m3). Subcontractor production rate variance can
be computed as follows:
. . .
i i
i i i i i
i i
a b
S P b S a b S a
b a
Shrs Q
CV C P C P
Shrs Q
Where: . i S P CV is the subcontractor production rate
cost variance,
i a Shrs is the actual number of
subcontractor working hours to date, and
i b Shrs is
the budgeted number of sub-contractor working
hours.
Subcontractor Cost per Hour Variance
Subcontractor cost per hour variance is due to
deviations that occur when the actual cost per hour
differs from the budgeted one. Subcontractor cost per
hour is reported in $/hour. Subcontractor cost per
hour variance can be computed as follows:
. . .
i
i i i i i
i
b
S H b S a a S a
a
Shrs
CV C P C P
Shrs
Where: . i S H CV is the subcontractor cost per hour
variance.
Subcontractor Production rate Cost per Hour Joint
Variance
Subcontractor production rate cost per hour joint
variance is due to a variance in subcontractor
production rate and a variance in subcontractor cost
per hour at the same time. Subcontractor production
rate cost per hour joint variance can be computed by
the following equation:
. .
.
ij ij ij ij
ij ij ij
ij ij ij ij
b a a S b S
S P H b a
b a a b
Shrs Shrs C C
CV Q P
Q Q Shrs Shrs
Where:
. ij S P H CV is the subcontractor cost per
hour joint variance.
Cost variance is broken into more detailed
variances for all resources. Cost variance equals the
total variance in material cost plus crews cost plus
subcontract cost. These detailed variances mainly
occur due to deviations in quantities, rates, resources,
and production rate of used resources.
With the highly compatible spreadsheet
format/modeling of the cost estimate model and the
acquisition forms for resources progress data,
variances calculations according the aforementioned
equations are facilitated using simple spreadsheet
formulas. This is illustrated in Figure 10. During the
progress monitoring, these variances will be
calculated frequently then sent to the BIM model for
visualization. Visualization will facilitate pinpointing
problems to take corrective actions in a timely
manner.
Figure 10: Planned Versus actual Variance
Visualization Flow Chart
III. MODEL IMPLEMENTATION
This section describes a computerized system
that is developed to automate the
estimating/monitoring process. The implementation
process depends on using commercial software
packages such as Microsoft Project and Microsoft
Excel. Microsoft Excel provides the capabilities
needed to reduce and analyze of the input data and
output results, so all of the data and results are loaded
into Excel spreadsheets. The software is used to
enable easy and accurate transfer of data from one
media to the other. The proposed system will be able
to perform the estimate/monitor at different levels to
satisfy the requirements of the different managerial
levels. The Visual Basic for Application (VBA) in
the Microsoft Excel media is used to develop the
desired integration and linking between Microsoft
Project and Microsoft Excel to achieve the desired
results.
Initially a scheduling module for the project is
developed using Ms Project software. The project is
an eight-storey building (Ground floor, 6 typical
floors and a roof) of a foot print area of 1000 m2 and
a built up area of 8200 m2. Visual Basic for
Applications (VBA) macro programming language of
Excel is used to retrieve the project schedule to the
Excel spreadsheets. It acquires the initial plan for the
project from Ms Project. By developing an initial
schedule and integrate it with the cost estimating
module, the total cost of the project is calculated as
well as the detailed cost for all activities and
resources. Actual cost data in addition to resources
data, which represent actual progress information,
can be plugged into the cost control module in Excel
environment by using friendly forms. Detailed
project cost variances are computed in the
background based on the previously discussed
equations. Actual cost data and detailed variances are
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then automatically transferred to the Microsoft
Project. The proposed model is capable of dealing
with any type of projects.
The automated cost monitoring module is a
prototype system that is developed to enable project
parties to identify critical control points and improve
their effectiveness in monitoring their projects.
Automated early progress cost performance
assessments are most susceptible to performance data
noise (change). Quantities measurements, crew’s
productivities and number of crew’s noise are
increasingly diluted as the project progresses. A new
menu is created in Excel to make it easy to enter
actual resources data and to calculate required
variances. Entering data into a large spreadsheet list
may become extremely tedious and prone to error.
The proposed forms in the created menu provide a
simple way for entering, editing or deleting existing
records in a list. Figure 11 shows screen shots for the
cost control and variance analysis module. These
screens allow the users to define parameters, edit
inputs, and define actual values. As shown in Figure
11, the user has the ability to input actual duration,
actual performed quantities, actual production rates
and actual costs regarding all project elements.
Accordingly cost variances are calculated and
presented.
Figure 11: Screen Shots for Automated Cost Control
Tool
IV. BIM BASED VISUALIZATION
PLATFORM
The ability to visualize construction projects
from the design phase, integrating it with project cost
estimate and control is a destination that is achieved
using the advances in the Building Information
Modeling (BIM). In developing a visualized nD
model, first of all, a three dimensional (3D) model
must be prepared in a BIM environment (e.g. Rivet).
Building the model in Revit does not only represent a
3D model but also extends it to nD modeling because
each object (e.g. walls, roofs, and etc.) has a database
containing all information pertaining to that object.
Project objects data can be exported from the BIM
environment to the central Access database. By
preparing the project cost estimate and implementing
cost control models in Excel spreadsheets, all
information is exported to the central database.
Accordingly, project elements information in Access
is updated by the cost estimate and control data. Also,
the project data stored in the database system could
be exported to BIM and linked to their corresponding
objects automatically.
Accordingly, a query can be done to visualize the
project components based on the imported data from
Access. Project objects in Revit, which corresponds
to project activities, now are stored in Revit with
their cost estimate and cost variances data. The filter
command in Revit enable the user to visualize the
project objects that have unfavorable cost variance
and those that have favorable cost variance in color
coding. Figure 12 shows the work progress at month
6. It can be noticed from the figure that the first and
second floor slabs were over budget while other
elements were either on budget or below budget.
Figure12: BIM-Based Visualized Cost Control
V. MODEL BENEFITS AND
LIMITATIONS
A visualized cost estimate/cost control model
provides reliable features to architects, owners,
engineers, contractors, and all participants involved
in the construction industry. It creates a single
building model that act as a repository for all
elements of the building. The model provides many
features that help project construction team to avoid
costly errors during construction of the project.
Element clashes can be detected from the design
phase saving considerable time delays and cost
overrun, in case of any discrepancy. At the same
time, visualization helps construction team to absorb
and understand project information.
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Computerized automated model could support decision making by enabling project parties to test and evaluate any alternative rapidly for the purpose of reaching an optimum solution. Ambiguities in the construction process can be highlighted by any team member and resolved before construction starts. Constructability issues can also be discussed and evaluated. Time that is normally spent in traditional tracking methods by construction team will be reduced considerably. In the other hand, the completeness of documents provided by the proposed model can be used not only for design and construction purposes, but also for delay analysis in post construction. Quantity takeoff is another area which can be immensely benefited from BIM. Autodesk Revit creates a building information model such that it identifies the model as building elements, such as walls, foundation, and floor not just few lines drawn but as assemblies made of real materials which can be viewed if a section is cut. Quantity takeoff using a BIM can be done by exporting the building object quantities to Ms Access database. One of the considerable limitations of the proposed model is the amount of computer memory and processing power required for interactive walk through and controlling repetitive construction projects. The proposed model is applicable for small to medium projects, but it is complex to apply to large projects in view of the memory and processing power required. The model has been introduced to several project management experts to provide the authors with an evaluation regarding the following points:
The simplicity of the model and the sufficiency of its outputs;
Its potential application in the area of cost monitoring and control
Its benefits and advantages over current cost monitoring/control practices and
Further suggestions for improvement.
Results show that the model/approach is perceived by construction experts to have a good potential and several benefits in simplifying the process of monitoring construction activities. They added that color coding help in pinpointing the areas that need immediate corrective actions. As for the suggestion for improvement, they recommended to have a split view to concurrently see the resources cost variances for an activity along with the overall cost variance. Currently BIM versioning as a core for split view is investigated by the authors to be included in a future research.
VI. SUMMARY AND CONCLUSIONS
Cost estimate and control are important tools to track and monitor construction projects. This research introduces a new approach to monitor/control construction projects. A mathematical methodology for evaluating construction performance with respect to cost has been developed. One of the model objectives is to introduce the major variables that affect controlling of project cost. Components of cost variances were presented in details. Based on the previous analysis, the proposed project monitoring system provides useful information for effective control of construction projects. A methodology for evaluating and visualizing construction performance with respect to cost has been developed. A BIM based visualization system has been introduced to facilitate tracking and monitoring construction progress. The proposed model can be effectively used in controlling small to medium projects. The main advantage of the system is that it enables nD visualization of the construction progress along with the geographical conditions. The system provides project participants with a framework to effortlessly view and evaluate construction progress. This paper emphasizes the importance of integration between project cost estimate, cost monitoring/control techniques and BIM platforms. The integration will add other dimensions to construction progress visualization. The developed framework can be considered as an effective tool for monitoring construction projects and providing decision makers with a visualization aid to enable them to take cost and progress related decisions in a timely manner. REFERENCES
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