Faris Elghaish, Sandra T. Matarneh, Saeed Talebi, Soliman Abu-Samra, Ghazal Salimi and Christopher Rausch
The massive number of pavements and buildings coupled with the limited inspection resources, both monetary and human, to detect distresses and recommend maintenance actions lead…
Abstract
Purpose
The massive number of pavements and buildings coupled with the limited inspection resources, both monetary and human, to detect distresses and recommend maintenance actions lead to rapid deterioration, decreased service life, lower level of service and increased community disruption. Therefore, this paper aims at providing a state-of-the-art review of the literature with respect to deep learning techniques for detecting distress in both pavements and buildings; research advancements per asset/structure type; and future recommendations in deep learning applications for distress detection.
Design/methodology/approach
A critical analysis was conducted on 181 papers of deep learning-based cracks detection. A structured analysis was adopted so that major articles were analyzed according to their focus of study, used methods, findings and limitations.
Findings
The utilization of deep learning to detect pavement cracks is advanced compared to assess and evaluate the structural health of buildings. There is a need for studies that compare different convolutional neural network models to foster the development of an integrated solution that considers the data collection method. Further research is required to examine the setup, implementation and running costs, frequency of capturing data and deep learning tool. In conclusion, the future of applying deep learning algorithms in lieu of manual inspection for detecting distresses has shown promising results.
Practical implications
The availability of previous research and the required improvements in the proposed computational tools and models (e.g. artificial intelligence, deep learning, etc.) are triggering researchers and practitioners to enhance the distresses’ inspection process and make better use of their limited resources.
Originality/value
A critical and structured analysis of deep learning-based crack detection for pavement and buildings is conducted for the first time to enable novice researchers to highlight the knowledge gap in each article, as well as building a knowledge base from the findings of other research to support developing future workable solutions.
Details
Keywords
Faris Elghaish, Sepehr Abrishami, M. Reza Hosseini and Soliman Abu-Samra
The amalgamation of integrated project delivery (IPD) and building information modelling (BIM) is highly recommended for successful project delivery. However, IPD lacks an…
Abstract
Purpose
The amalgamation of integrated project delivery (IPD) and building information modelling (BIM) is highly recommended for successful project delivery. However, IPD lacks an accurate cost estimation methodology at the “front-end” of projects, when little project information is available. This study aims to tackle this issue, through presenting analytical aspects, theoretical grounds and practical steps/procedures for integrating target value design (TVD), activity-based costing (ABC) and Monte Carlo simulation into the IPD cost structure, within a BIM-enabled platform.
Design/methodology/approach
A critical review was conducted to study the status of cost estimation within IPD, as well as exploring methods and tools that can enhance the cost estimation process for IPD. Thereafter, a framework is developed to present the proposed methodology of cost estimation for IPD throughout its entire stages. A case project is used to validate the practicality of the developed solution through comparing the profit-at-risk percentage for each party, using both traditional cost estimation and the proposed solution.
Findings
After applying the proposed IPD's cost estimation framework, on a real-life case project, the findings demonstrated significant deviations in the profit-at-risk value for various work packages of the project (approximately 100% of the finishing package and 22% of openings package). By providing a precise allocation of overhead costs, the solution can be used in real-life projects to change the entire IPD cost structure and ensure a fair sharing of risk–rewards among the involved parties in IPD projects.
Practical implications
Using the proposed methodology of cost estimation for IPD can enhance the relationship among IPD's core team members; all revealed financial deficiencies will be considered (i.e. compensation structure, profit pooling), hence enhancing the IPD performance.
Originality/value
This paper presents a comprehensive solution for integrating BIM and IPD in terms of cost estimation, offering three main contributions: (1) an innovate approach to utilise five-dimensional (5D) BIM capabilities with Monte Carlo simulation, hence providing reliable cost estimating during the conceptual TVD stage; (2) mathematical models that are developed through integrating ABC into the detailed 5D BIM to determine the three IPD's cost structure limbs; and (3) a novel mechanism of managing cost saving (rewards) through distinguishing between saved resources from organisation level, to daily task level, to increase trust among parties.
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Ayuba Jerry Likita, Mostafa Babaeian Jelodar, V Vishnupriya and James Olabode Bamidele Rotimi
The construction industry is inefficient in terms of quality products, productivity and performance worldwide, including in Australia and New Zealand. The construction industry is…
Abstract
Purpose
The construction industry is inefficient in terms of quality products, productivity and performance worldwide, including in Australia and New Zealand. The construction industry is becoming more innovative, competitive and complex; and more participants are involved in construction projects. There are new attempts to implement the Lean construction philosophy, integrated project delivery method and building information modelling (BIM) technology in construction industry to improve productivity and efficiency. This paper aims to identify Lean and BIM integration benefits in construction industry globally and in the New Zealand.
Design/methodology/approach
A systematic literature review and case studies were used to identify various benefits of the integrating Lean and BIM in construction industry. It focused on articles published between 1995 and 2021.
Findings
Lean and BIM benefits identified in the study were documented such as benefits over the traditional approach, critically increased efficiency and visualization, better building process, better building performance, mitigating risk and reduce cost. Also, several factors were identified as major benefits such as improved onsite collaboration, better coordination, improve onsite communication, increase productivity, mitigating risk, reducing waste and reduced cost. The study showed integrating Lean and BIM in construction management practice will help reduce several challenges which affect expected goals and customer anticipation. The research outcome ultimately will assist different stakeholders in applying Lean and BIM in construction management practice.
Originality/value
This study practically focused on using the integration of BIM and Lean principles to improve the construction industry productivity and performance.