Kareem Mostafa, Tarek Hegazy, Robert D. Hunsperger and Stepanka Elias
This paper aims to use convolutional neural networks (CNNs) to provide an objective approach to classify deteriorated building assets according to the type and extent of damage…
Abstract
Purpose
This paper aims to use convolutional neural networks (CNNs) to provide an objective approach to classify deteriorated building assets according to the type and extent of damage. This research supports automated inspection of buildings and focuses on roofing elements as one of the most critical and externally distressed elements in buildings.
Design/methodology/approach
In this paper, 5,000+ images of deteriorated roofs from several buildings were collected to design a CNN system that automatically identifies and sizes roofing defects. Experimenting with different CNN formulations, the best accuracy is achieved using two-stage CNNs. The first-stage CNN classifies images into defect/no defect, while the second stage classifies the defected images according to the damage type. Based on the image classification, optimization is used to prioritize roof repairs by maximizing the return from limited rehabilitation funds.
Findings
The developed CNNs reached 95% and 97% accuracy for the first and second phases, respectively, which is higher than achieved in previous literature efforts. Using the proposed model to automate inspection and condition assessment activities proved to be faster than conventional methods. Repair/replace strategy for a case study of 21 campus buildings based on their condition and budgetary constraints was suggested.
Research limitations/implications
Future research includes testing different data acquisition technologies (e.g. infrared imaging), performing severity-based classification and integrating with BIM for defect localization.
Originality/value
This study provides an objective approach to automate asset condition assessment and improve funding decisions using a combination of image analysis and optimization techniques. The proposed approach is applicable toward other asset types and components.
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TAREK HEGAZY and OSAMA MOSELHI
Compiling bid proposals for construction projects is a process that depends on extensive computation as well as on experience‐based judgement. Despite the proliferation of…
Abstract
Compiling bid proposals for construction projects is a process that depends on extensive computation as well as on experience‐based judgement. Despite the proliferation of estimating tools, bid proposals focus primarily on the computational component and leave the more difficult aspects of risk assessment and mark‐up estimation to estimators' judgement. This may lead to unrealistic estimates that do not account for the operational environment of projects. Such estimates often result in either losing bids or inflicting undesirable cost overruns. In an effort to circumvent such drawbacks, this paper presents a structured system for cost estimation and bid preparation. Unlike current tools, the proposed system supports a holistic bid‐preparation process, accounting for a number of quantitative as well as qualitative factors that are used in practice for bid preparation. The system incorporates three principal features: 1 Integrated cost and schedule computation 2 Adequate risk assessment and mark‐up estimation 3 Optimum bid unbalancing and cash flow optimization. The developments made in the integrated system are described along with a PC‐based prototype Estimator, developed to automate the process. An example application is presented to illustrate the capabilities and essential features of the prototype and demonstrate its practicality.
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The purpose of this paper is to propose a microeconomic-based approach to support fund-allocation decisions for a large number of assets. Under the prevailing financial…
Abstract
Purpose
The purpose of this paper is to propose a microeconomic-based approach to support fund-allocation decisions for a large number of assets. Under the prevailing financial constraints and rapid deterioration of facilities, arriving at optimum fund allocation for capital renewal projects has become very challenging. Due to the complexity of modeling multi-year life cycle cost analysis, existing fund-allocation methods have serious drawbacks when handling a large portfolio of assets, and their results are difficult to justify.
Design/methodology/approach
This paper adopts well-established theories from microeconomics and proposes a new microeconomic-based decision support framework that has two novel components: a heuristic procedure to optimize and justify fund-allocation decisions by balancing the funding among the different asset categories; and a visual what-if analysis approach inspired by the economic indifference maps.
Findings
Applying the proposed framework on a real case study of 800 building components proved that optimum decisions can be achieved through an equilibrium state at which fair and equitable allocations are made such that the utility per dollar is balanced for all asset categories. The visual what-if analysis approach presented a powerful graphical tool to visualize decisions, along with their costs and benefits, and facilitate sensitivity analysis under changes in budget levels.
Originality/value
This paper, using the proposed microeconomic framework, sheds a new light on how fund-allocation optimization problems can be simplified, from an economic perspective, to arrive at accurate and justifiable decisions for a large portfolio of facilities.
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Tarek Hegazy, Mohamed Abdel-Monem and Dina Atef Saad
This paper aims at improving progress tracking and control of repetitive projects by developing a novel framework that automates the documentation of as-built information directly…
Abstract
Purpose
This paper aims at improving progress tracking and control of repetitive projects by developing a novel framework that automates the documentation of as-built information directly into the project schedule and also introduces enhanced linear scheduling formulation to support project control decisions.
Design/methodology/approach
The proposed framework uses e-mail technology to facilitate detailed tracking of daily as-built events of all parties through bidirectional communication between site and head office. It also provides a new formulation for more accurate critical path and linear scheduling computation to accurately update the project's time and cost during construction.
Findings
Using a case study of a road project, the paper proves that the proposed framework reduces as-built documentation effort and its schedule updates are more responsive to all as-built events than traditional scheduling techniques.
Research limitations/implications
The proposed method applies to linear projects (e.g. highways) and can be extended to other repetitive projects such as high-rise buildings. It can also be extended to include voice features and procedures for forensic schedule analysis.
Practical implications
The developed methodology presents a low-cost approach to document timely progress information for decision makers of massive linear projects (often associated with infrastructure) to have better control over the execution of projects, save documentation time and cost, and avoid disputes and problems.
Originality/value
This research contributes in improving construction productivity by collecting timely as-built information using affordable communication technologies. It also presents novel advancements to the existing scheduling and control techniques to suit linear projects, which are most challenging.
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Huy Minh Vo, Jyh-Bin Yang and Veerakumar Rangasamy
Construction projects commonly encounter complicated delay problems. Over the past few decades, numerous delay analysis methods (DAMs) have been developed. There is no consensus…
Abstract
Purpose
Construction projects commonly encounter complicated delay problems. Over the past few decades, numerous delay analysis methods (DAMs) have been developed. There is no consensus on whether existing DAMs effectively resolve delays, particularly in the case of complex concurrent delays. Thus, the primary objective of this study is to undertake a comprehensive and systematic literature review on concurrent delays, aiming to answer the following research question: Do existing delay analysis techniques deal with concurrent delays well?
Design/methodology/approach
This study conducts a comprehensive review of concurrent delays by both bibliometric and systematic analysis of research publications published between 1982 and 2022 in the Web of Science (WoS) and Scopus databases. For quantitative analysis, a bibliometric mapping tool, the VOSviewer, was employed to analyze 68 selected publications to explore the co-occurrence of keywords, co-authorship and direct citation. Additionally, we conducted a qualitative analysis to answer the targeted research question, identify academic knowledge gaps and explore potential research directions for solving the theoretical and practical problems of concurrent delays.
Findings
Concurrent delays are a critical aspect of delay claims. Despite DAMs developed by a limited number of research teams to tackle issues like concurrence, float consumption and the critical path in concurrent delay resolution, practitioners continue to face significant challenges. This study has successfully identified knowledge gaps in defining, identifying, analyzing and allocating liability for concurrent delays while offering promising directions for further research. These findings reveal the incompleteness of available DAMs for solving concurrent delays.
Practical implications
The outcomes of this study are highly beneficial for practitioners and researchers. For practitioners, the discussions on the resolution process of concurrent delays in terms of identification, analysis and apportionment enable them to proactively address concurrent delays and lay the groundwork for preventing and resolving such issues in their construction projects. For researchers, five research directions, including advanced DAMs capable of solving concurrent delays, are proposed for reference.
Originality/value
Existing research on DAMs lacks comprehensive coverage of concurrent delays. Through a scientometric review, it is evident that current DAMs do not deal with concurrent delays well. This review identifies critical knowledge gaps and offers insights into potential directions for future research.
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Tarek Hegazy, Shipra Singh Ahluwalia and Mohamed Attalla
Sustaining the safety and operability of the civil infrastructure assets, including buildings, is a complex undertaking that requires a perpetual cycle involving inspection, and…
Abstract
Purpose
Sustaining the safety and operability of the civil infrastructure assets, including buildings, is a complex undertaking that requires a perpetual cycle involving inspection, and further decisions for renewal fund allocation. Inspection, which is the basis for all subsequent decisions, however, is subjective, costly, and time‐consuming. To circumvent inspection problems, this paper aims to develop indicators of the condition of building components, without inspection, using reactive‐maintenance data.
Design/methodology/approach
For that purpose, sample reactive‐maintenance data of 88 schools are obtained from the Toronto District School Board in Canada. The data are then analysed to identify two condition indicators for building components: the number of reactive‐maintenance work orders per year; and the cost of reactive‐maintenance work orders per year. The analysis then identifies threshold values that differentiate the good, fair, poor, and critical conditions of components. Accordingly, a condition prediction system has been developed and discussed in this paper.
Findings
The system has great potential benefits in saving the time and cost associated with indiscriminate inspections, and in providing accurate and timely data for asset renewal decisions.
Originality/value
The paper introduces an essential component of a comprehensive framework for building asset management: condition prediction and inspection planning.
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Tarek Salama and Osama Moselhi
The purpose of this paper is to present a newly developed multi-objective optimization method for the time, cost and work interruptions for repetitive scheduling while considering…
Abstract
Purpose
The purpose of this paper is to present a newly developed multi-objective optimization method for the time, cost and work interruptions for repetitive scheduling while considering uncertainties associated with different input parameters.
Design/methodology/approach
The design of the developed method is based on integrating six modules: uncertainty and defuzzification module using fuzzy set theory, schedule calculations module using the integration of linear scheduling method (LSM) and critical chain project management (CCPM), cost calculations module that considers direct and indirect costs, delay penalty, and work interruptions cost, multi-objective optimization module using Evolver © 7.5.2 as a genetic algorithm (GA) software, module for identifying multiple critical sequences and schedule buffers, and reporting module.
Findings
For duration optimization that utilizes fuzzy inputs without interruptions or adding buffers, duration and cost generated by the developed method are found to be 90 and 99 percent of those reported in the literature, respectively. For cost optimization that utilizes fuzzy inputs without interruptions, project duration generated by the developed method is found to be 93 percent of that reported in the literature after adding buffers. The developed method accelerates the generation of optimum schedules.
Originality/value
Unlike methods reported in the literature, the proposed method is the first multi-objective optimization method that integrates LSM and the CCPM. This method considers uncertainties of productivity rates, quantities and availability of resources while utilizing multi-objective GA function to minimize project duration, cost and work interruptions simultaneously. Schedule buffers are assigned whether optimized schedule allows for interruptions or not. This method considers delay and work interruption penalties, and bonus payments.
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Ibrahim Bakry, Osama Moselhi and Tarek Zayed
Construction projects are complex projects taking place in dynamic environments, which necessitates accounting for different uncertainties during the planning stage. There is a…
Abstract
Purpose
Construction projects are complex projects taking place in dynamic environments, which necessitates accounting for different uncertainties during the planning stage. There is a significant lack of management tools for repetitive projects accounting for uncertainties in the construction environment. The purpose of this paper is to present an algorithm for the optimized scheduling of repetitive construction projects under uncertainty.
Design/methodology/approach
Fuzzy set theory is utilized to model uncertainties associated with various input parameters. The developed algorithm has two main components: optimization component and buffering component. The optimization component presents a dynamic programming approach that processes fuzzy numbers. The buffering component converts the optimized fuzzy schedule into a deterministic schedule and inserts time buffers to protect the schedule against anticipated delays. Agreement Index (AI) is used to capture the user’s desired level of confidence in the produced schedule while sizing buffers. The algorithm is capable of optimizing for cost or time objectives. An example project drawn from literature is analysed to demonstrate the capabilities of the developed algorithm and to allow comparison of results to those previously generated.
Findings
Testing the algorithm revealed several findings. Fuzzy numbers can be utilized to capture uncertainty in various inputs without the need for historical data. The modified algorithm is capable of optimizing schedules, for different objectives, under uncertainty. Finally AI can be used to capture users’ desired confidence in the final schedule.
Originality/value
Project planners can utilize this algorithm to optimize repetitive projects schedules, while modelling uncertainty in different input parameters, without the need for relevant historical data.
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Huthaifa AL-Smadi, Abobakr Al-Sakkaf, Tarek Zayed and Fuzhan Nasiri
The purpose of this study is to minimize cost and minimize building condition. Weibull distribution approach was employed to generate deterioration curves over time. The third…
Abstract
Purpose
The purpose of this study is to minimize cost and minimize building condition. Weibull distribution approach was employed to generate deterioration curves over time. The third floor of Concordia University’s Engineering And Visual Arts (EV) Complex in Montreal, Canada, served as a case study to test the maintenance model and determine the optimal maintenance activities to be performed.
Design/methodology/approach
This research has demonstrated that there is insufficient fund allocation for the maintenance of non-residential buildings. Therefore, this research focused on designing and developing a maintenance optimization model that provides the type of spaces (architectural system) in a building. Sensitivity analysis was used to calculate weights to validate the model. Particle swarm optimization, based explicitly on multiple objectives, was applied for the optimization problem using MATLAB.
Findings
Following 100 iterations, 13 non-dominant solutions were generated. Not only was the overall maintenance cost minimized, but the condition of the building was also maximized. Moreover, the condition prediction model demonstrated that the window system type has the most rapid deterioration in educational buildings.
Originality/value
The model is flexible and can be modified by facility managers to align with the required codes or standards.
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Samy Shaban, Abd Elaziz Fouda, Mohamed Elmorsi, Tarek Fayed and Omar Azazy
The purpose of this study is to inspect the corrosion inhibition of API N80 steel pipelines in uninhibited solution and inhibited with a synthesized surfactant compound…
Abstract
Purpose
The purpose of this study is to inspect the corrosion inhibition of API N80 steel pipelines in uninhibited solution and inhibited with a synthesized surfactant compound [N-(3-(dimethyl octyl ammonio) propyl) palmitamide bromide] (DMDPP), which is prepared through a simple and applicable method.
Design/methodology/approach
Weight loss was inspected at five different temperatures of 25°C, 30°C, 40°C, 50°C and 60°C Potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) and electrochemical frequency modulation were used at room temperature. Density functional theory was used to study the relation between the molecular structure and inhibition theoretically.
Findings
Adsorption of the prepared DMDPP fits the Langmuir isotherm model. The inhibition efficiency of the prepared DMDPP amphipathic inhibitor is directly proportional to temperature increase. Polarization results reveal that the investigated DMDPP amphipathic compound behaves as a mixed-type inhibitor. EIS spectra produced one individual capacitive loop.
Originality/value
The originality is the preparation of cationic surfactants through a simple method, which can be used as corrosion inhibitors in oil production. The synthesized inhibitors were prepared from low-price materials. The work studied the behavior of the synthesized surfactants in inhibiting the corrosion of the steel in an acidic medium. Electrochemical and theoretical studies were presented, besides gravimetric and surface examination.