Purpose Several factors influence the costs of buildings. Thus, identifying the cost significant factors can assist to improve the accuracy of project cost forecasts during the planning phase. This paper aims to identify the cost significant parameters and explore the potential for improving the accuracy of cost forecasts for buildings using machine learning techniques and large data sets. Design/methodology/approach The Australian State of Victoria Building Authority data sets, which comprise various parameters such as cost of the buildings, materials used, gross floor areas (GFA) and type of buildings, have been used. Five different machine learning regression models, such as decision tree, linear regression, random forest, gradient boosting and k-nearest neighbor were used. Findings The findings of the study showed that among the chosen models, linear regression provided the worst outcome (r2 = 0.38) while decision tree (r2 = 0.66) and gradient boosting (r2 = 0.62) provided the best outcome. Among the analyzed features, the class of buildings explained about 34% of the variations, followed by GFA and walls, which both accounted for 26% of the variations. Originality/value The output of this research can provide important information regarding the factors that have major impacts on the costs of buildings in the Australian construction industry. The study revealed that the cost of buildings is highly influenced by their classes.
{"title":"Machine learning regression for estimating the cost range of building projects","authors":"A. Gurmu, Mani Pourdadash Miri","doi":"10.1108/ci-08-2022-0197","DOIUrl":"https://doi.org/10.1108/ci-08-2022-0197","url":null,"abstract":"\u0000Purpose\u0000Several factors influence the costs of buildings. Thus, identifying the cost significant factors can assist to improve the accuracy of project cost forecasts during the planning phase. This paper aims to identify the cost significant parameters and explore the potential for improving the accuracy of cost forecasts for buildings using machine learning techniques and large data sets.\u0000\u0000\u0000Design/methodology/approach\u0000The Australian State of Victoria Building Authority data sets, which comprise various parameters such as cost of the buildings, materials used, gross floor areas (GFA) and type of buildings, have been used. Five different machine learning regression models, such as decision tree, linear regression, random forest, gradient boosting and k-nearest neighbor were used.\u0000\u0000\u0000Findings\u0000The findings of the study showed that among the chosen models, linear regression provided the worst outcome (r2 = 0.38) while decision tree (r2 = 0.66) and gradient boosting (r2 = 0.62) provided the best outcome. Among the analyzed features, the class of buildings explained about 34% of the variations, followed by GFA and walls, which both accounted for 26% of the variations.\u0000\u0000\u0000Originality/value\u0000The output of this research can provide important information regarding the factors that have major impacts on the costs of buildings in the Australian construction industry. The study revealed that the cost of buildings is highly influenced by their classes.\u0000","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62051375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fábio Matoseiro Dinis, R. Rodrigues, João Pedro da Silva Poças Martins
Purpose Despite the technological paradigm shift presented to the architecture, engineering, construction and operations sector (AECO), the full-fledged acceptance of the building information modelling (BIM) methodology has been slower than initially anticipated. Indeed, this study aims to acknowledge the need for increasing supportive technologies enabling the use of BIM, attending to available human resources, their requirements and their tasks. Design/methodology/approach A complete case study is described, including the development process centred on design science research methodology followed by the usability assessment procedure validated by construction projects facility management operational staff. Findings Results show that participants could interact with BIM using openBIM processes and file formats naturally, as most participants reached an efficiency level close to that expected for users already familiar with the interface (i.e. high-efficiency values). These results are consistent with the reported perceived satisfaction and analysis of participants’ discourses through 62 semi-structured interviews. Originality/value The contributions of the present study are twofold: a proposal for a virtual reality openBIM framework is presented, particularly for the semantic enrichment of BIM models, and a methodology for evaluating the usability of this type of system in the AECO sector.
{"title":"Development and validation of natural user interfaces for semantic enrichment of BIM models using open formats","authors":"Fábio Matoseiro Dinis, R. Rodrigues, João Pedro da Silva Poças Martins","doi":"10.1108/ci-12-2022-0348","DOIUrl":"https://doi.org/10.1108/ci-12-2022-0348","url":null,"abstract":"\u0000Purpose\u0000Despite the technological paradigm shift presented to the architecture, engineering, construction and operations sector (AECO), the full-fledged acceptance of the building information modelling (BIM) methodology has been slower than initially anticipated. Indeed, this study aims to acknowledge the need for increasing supportive technologies enabling the use of BIM, attending to available human resources, their requirements and their tasks.\u0000\u0000\u0000Design/methodology/approach\u0000A complete case study is described, including the development process centred on design science research methodology followed by the usability assessment procedure validated by construction projects facility management operational staff.\u0000\u0000\u0000Findings\u0000Results show that participants could interact with BIM using openBIM processes and file formats naturally, as most participants reached an efficiency level close to that expected for users already familiar with the interface (i.e. high-efficiency values). These results are consistent with the reported perceived satisfaction and analysis of participants’ discourses through 62 semi-structured interviews.\u0000\u0000\u0000Originality/value\u0000The contributions of the present study are twofold: a proposal for a virtual reality openBIM framework is presented, particularly for the semantic enrichment of BIM models, and a methodology for evaluating the usability of this type of system in the AECO sector.\u0000","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42273608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-17DOI: 10.15282/construction.v3i1.9217
Usmani Mohammed Umar, K. Muthusamy
In recent times, there has been growing interest in utilizing waste materials as coarse lightweight aggregates in the production of lightweight aggregate concrete. This approach has been gaining momentum as it has the potential to address the environmental concerns that come with conventional construction practices. The objective of this review paper is to evaluate the viability and potential of waste materials as coarse lightweight aggregates for producing lightweight aggregate concrete. This paper reviews the current research on various types of waste materials, including waste plastic, recycled concrete aggregate, slag, fly ash, and expanded polystyrene, as potential candidates for coarse lightweight aggregates. The paper highlights the properties and characteristics of these waste materials and their suitability for use as coarse lightweight aggregates. Additionally, the evaluation explores the mechanical characteristics of lightweight aggregate concrete that is generated using waste materials as coarse lightweight aggregates. Specifically, it compares the compressive strength, splitting tensile strength, flexural strength, and modulus of elasticity of lightweight aggregate concrete that includes waste materials with those of typical concrete. Furthermore, the paper discusses the sustainability benefits of using waste materials as coarse lightweight aggregates. By using waste materials in construction, not only are resources conserved, but waste is also diverted from landfills, reducing the negative impact on the environment. In conclusion, this review paper demonstrates that the use of waste material as coarse lightweight aggregate for lightweight aggregate concrete production is a viable and sustainable approach. The application of waste materials as coarse lightweight aggregates in lightweight aggregate concrete demonstrates mechanical characteristics that are similar to traditional concrete. Moreover, utilizing waste materials in this manner provides environmental advantages. This study offers valuable insights into the implementation of waste materials in construction, and it emphasizes the possibility of further exploration and advancement in this domain. For this review, a total of 15 articles were analyzed, with publication dates ranging from 2005 to 2021. The study contributes to several Sustainable Development Goals (SDG 9/11/12/13) set by the United Nations such as providing insights into the role of industry, innovation, infrastructure, sustainable cities, responsible consumption, production practices, and climate action.
{"title":"Potential of Waste Material as Coarse Aggregates for Lightweight Concrete Production: A Sustainable Approach","authors":"Usmani Mohammed Umar, K. Muthusamy","doi":"10.15282/construction.v3i1.9217","DOIUrl":"https://doi.org/10.15282/construction.v3i1.9217","url":null,"abstract":"In recent times, there has been growing interest in utilizing waste materials as coarse lightweight aggregates in the production of lightweight aggregate concrete. This approach has been gaining momentum as it has the potential to address the environmental concerns that come with conventional construction practices. The objective of this review paper is to evaluate the viability and potential of waste materials as coarse lightweight aggregates for producing lightweight aggregate concrete. This paper reviews the current research on various types of waste materials, including waste plastic, recycled concrete aggregate, slag, fly ash, and expanded polystyrene, as potential candidates for coarse lightweight aggregates. The paper highlights the properties and characteristics of these waste materials and their suitability for use as coarse lightweight aggregates. Additionally, the evaluation explores the mechanical characteristics of lightweight aggregate concrete that is generated using waste materials as coarse lightweight aggregates. Specifically, it compares the compressive strength, splitting tensile strength, flexural strength, and modulus of elasticity of lightweight aggregate concrete that includes waste materials with those of typical concrete. Furthermore, the paper discusses the sustainability benefits of using waste materials as coarse lightweight aggregates. By using waste materials in construction, not only are resources conserved, but waste is also diverted from landfills, reducing the negative impact on the environment. In conclusion, this review paper demonstrates that the use of waste material as coarse lightweight aggregate for lightweight aggregate concrete production is a viable and sustainable approach. The application of waste materials as coarse lightweight aggregates in lightweight aggregate concrete demonstrates mechanical characteristics that are similar to traditional concrete. Moreover, utilizing waste materials in this manner provides environmental advantages. This study offers valuable insights into the implementation of waste materials in construction, and it emphasizes the possibility of further exploration and advancement in this domain. For this review, a total of 15 articles were analyzed, with publication dates ranging from 2005 to 2021. The study contributes to several Sustainable Development Goals (SDG 9/11/12/13) set by the United Nations such as providing insights into the role of industry, innovation, infrastructure, sustainable cities, responsible consumption, production practices, and climate action.","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90836302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This paper aims to present a highly accessible and affordable tracking model for earthmoving operations in an attempt to overcome some of the limitations of current tracking models. Design/methodology/approach The proposed methodology involves four main processes: acquiring onsite terrestrial images, processing the images into 3D scaled cloud data, extracting volumetric measurements and crew productivity estimations from multiple point clouds using Delaunay triangulation and conducting earned value/schedule analysis and forecasting the remaining scope of work based on the estimated performance. For validation, the tracking model was compared with an observation-based tracking approach for a backfilling site. It was also used for tracking a coarse base aggregate inventory for a road construction project. Findings The presented model has proved to be a practical and accurate tracking approach that algorithmically estimates and forecasts all performance parameters from the captured data. Originality/value The proposed model is unique in extracting accurate volumetric measurements directly from multiple point clouds in a developed code using Delaunay triangulation instead of extracting them from textured models in modelling software which is neither automated nor time-effective. Furthermore, the presented model uses a self-calibration approach aiming to eliminate the pre-calibration procedure required before image capturing for each camera intended to be used. Thus, any worker onsite can directly capture the required images with an easily accessible camera (e.g. handheld camera or a smartphone) and can be sent to any processing device via e-mail, cloud-based storage or any communication application (e.g. WhatsApp).
{"title":"A close-range photogrammetric model for tracking and performance-based forecasting earthmoving operations","authors":"Wahib Saif, Adel Alshibani","doi":"10.1108/ci-12-2022-0323","DOIUrl":"https://doi.org/10.1108/ci-12-2022-0323","url":null,"abstract":"\u0000Purpose\u0000This paper aims to present a highly accessible and affordable tracking model for earthmoving operations in an attempt to overcome some of the limitations of current tracking models.\u0000\u0000\u0000Design/methodology/approach\u0000The proposed methodology involves four main processes: acquiring onsite terrestrial images, processing the images into 3D scaled cloud data, extracting volumetric measurements and crew productivity estimations from multiple point clouds using Delaunay triangulation and conducting earned value/schedule analysis and forecasting the remaining scope of work based on the estimated performance. For validation, the tracking model was compared with an observation-based tracking approach for a backfilling site. It was also used for tracking a coarse base aggregate inventory for a road construction project.\u0000\u0000\u0000Findings\u0000The presented model has proved to be a practical and accurate tracking approach that algorithmically estimates and forecasts all performance parameters from the captured data.\u0000\u0000\u0000Originality/value\u0000The proposed model is unique in extracting accurate volumetric measurements directly from multiple point clouds in a developed code using Delaunay triangulation instead of extracting them from textured models in modelling software which is neither automated nor time-effective. Furthermore, the presented model uses a self-calibration approach aiming to eliminate the pre-calibration procedure required before image capturing for each camera intended to be used. Thus, any worker onsite can directly capture the required images with an easily accessible camera (e.g. handheld camera or a smartphone) and can be sent to any processing device via e-mail, cloud-based storage or any communication application (e.g. WhatsApp).\u0000","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48316279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shamika Hasaranga De Silva, K. Ranadewa, A. Rathnasinghe
Purpose Quality management barriers have been discovered in construction small- and medium-sized enterprises (SMEs), determining their long-term survival. Despite the recognition of Lean Six Sigma (LSS) as a valuable quality management technique for addressing the barriers faced by SMEs, LSS implementation within the construction SME context is alarmingly low. Therefore, this study aims to investigate the barriers for implementing LSS within construction SMEs and to determine the most effective strategies for overcoming these barriers. Design/methodology/approach A quantitative research approach was used, and data was collected in two stages: a questionnaire survey with 44 construction professionals and an expert opinion survey with 12 LSS specialists. The collected data was then analysed using the fuzzy TOPSIS method, achieving a higher degree of sensitivity. Findings The findings revealed the 15 most significant LSS barriers that need to be addressed. In addition, the ten most important strategies to be implemented in overcoming the identified barriers before LSS implementation were discovered and thematised, most notably the hiring of LSS specialists for project monitoring and the formation of a committee for strategic planning through LSS. Originality/value Previous research on LSS examined barriers and strategies for SMEs in general, but to the best of the authors’ knowledge, this study is the first of its kind, focusing especially on the construction SME context and involving the unique fuzzy TOPSIS approach.
{"title":"Barriers and strategies for implementing lean six sigma in small- and medium sized enterprises (SMEs) in construction industry: a fuzzy TOPSIS analysis","authors":"Shamika Hasaranga De Silva, K. Ranadewa, A. Rathnasinghe","doi":"10.1108/ci-09-2022-0225","DOIUrl":"https://doi.org/10.1108/ci-09-2022-0225","url":null,"abstract":"\u0000Purpose\u0000Quality management barriers have been discovered in construction small- and medium-sized enterprises (SMEs), determining their long-term survival. Despite the recognition of Lean Six Sigma (LSS) as a valuable quality management technique for addressing the barriers faced by SMEs, LSS implementation within the construction SME context is alarmingly low. Therefore, this study aims to investigate the barriers for implementing LSS within construction SMEs and to determine the most effective strategies for overcoming these barriers.\u0000\u0000\u0000Design/methodology/approach\u0000A quantitative research approach was used, and data was collected in two stages: a questionnaire survey with 44 construction professionals and an expert opinion survey with 12 LSS specialists. The collected data was then analysed using the fuzzy TOPSIS method, achieving a higher degree of sensitivity.\u0000\u0000\u0000Findings\u0000The findings revealed the 15 most significant LSS barriers that need to be addressed. In addition, the ten most important strategies to be implemented in overcoming the identified barriers before LSS implementation were discovered and thematised, most notably the hiring of LSS specialists for project monitoring and the formation of a committee for strategic planning through LSS.\u0000\u0000\u0000Originality/value\u0000Previous research on LSS examined barriers and strategies for SMEs in general, but to the best of the authors’ knowledge, this study is the first of its kind, focusing especially on the construction SME context and involving the unique fuzzy TOPSIS approach.\u0000","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41467041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Kedir, D. Hall, Sara Brantvall, Jerker Lessing, A. Hollberg, Ranjith K. Soman
Purpose This paper aims to conduct a qualitative assessment of synergies between information flows of a multifamily product platform used for industrialized housing and materials passports that can promote a circular economy in the construction industry. Design/methodology/approach Using a single case study method, the research assesses the availability and accessibility of materials passport-relevant information generated by a leading Swedish industrialized housing construction firm. Data is collected using semistructured interviews, document analysis and an extended research visit. Findings The research findings identify the functional layers of the product platform, map the information flow using a process diagram, assess the availability and accessibility of material passport relevant information by lifecycle stage and actor, and summarize the key points using a SWOT (strengths, weaknesses, opportunities and threats) analysis. Research limitations/implications The three main implications are: the technical and process platforms used in industrialized construction allow for generating standardized, digital and reusable information; the vertical integration of trades and long-term relationships with suppliers improve transparency and reduce fragmentation in information flows; and the design-build-operate business model strategy incentivizes actors to manage information flows in the use phase. Practical implications Industrialized construction firms can use this paper as an approach to understand and map their information flows to identify suitable approaches to generate and manage materials passports. Originality/value The specific characteristics of product platforms and industrialized construction provide a unique opportunity for circular information flow across the building lifecycle, which can support material passport adoption to a degree not often found in the traditional construction industry.
{"title":"Circular information flows in industrialized housing construction: the case of a multi-family housing product platform in Sweden","authors":"F. Kedir, D. Hall, Sara Brantvall, Jerker Lessing, A. Hollberg, Ranjith K. Soman","doi":"10.1108/ci-08-2022-0199","DOIUrl":"https://doi.org/10.1108/ci-08-2022-0199","url":null,"abstract":"\u0000Purpose\u0000This paper aims to conduct a qualitative assessment of synergies between information flows of a multifamily product platform used for industrialized housing and materials passports that can promote a circular economy in the construction industry.\u0000\u0000\u0000Design/methodology/approach\u0000Using a single case study method, the research assesses the availability and accessibility of materials passport-relevant information generated by a leading Swedish industrialized housing construction firm. Data is collected using semistructured interviews, document analysis and an extended research visit.\u0000\u0000\u0000Findings\u0000The research findings identify the functional layers of the product platform, map the information flow using a process diagram, assess the availability and accessibility of material passport relevant information by lifecycle stage and actor, and summarize the key points using a SWOT (strengths, weaknesses, opportunities and threats) analysis.\u0000\u0000\u0000Research limitations/implications\u0000The three main implications are: the technical and process platforms used in industrialized construction allow for generating standardized, digital and reusable information; the vertical integration of trades and long-term relationships with suppliers improve transparency and reduce fragmentation in information flows; and the design-build-operate business model strategy incentivizes actors to manage information flows in the use phase.\u0000\u0000\u0000Practical implications\u0000Industrialized construction firms can use this paper as an approach to understand and map their information flows to identify suitable approaches to generate and manage materials passports.\u0000\u0000\u0000Originality/value\u0000The specific characteristics of product platforms and industrialized construction provide a unique opportunity for circular information flow across the building lifecycle, which can support material passport adoption to a degree not often found in the traditional construction industry.\u0000","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42050951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Johnny Kwok-Wai Wong, Fateme Bameri, Alireza Ahmadian Fard Fini, M. Maghrebi
Purpose Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials. Design/methodology/approach A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials. Findings The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach. Originality/value The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.
目的准确、快速地跟踪和统计建筑材料对于管理现场施工过程和评估其进度至关重要。此类过程通常通过目视检查进行，因此耗时且容易出错。本文旨在提出一种基于视频的深度学习方法，用于建筑材料的自动检测和计数。设计/方法/方法使用最先进的深度学习方法开发了一个在低光照条件下准确计算室内建筑工地建筑材料的框架。现有的物体检测模型，即You Only Look Once version 4（YOLO v4）算法，适用于实现材料和现场操作人员的快速收敛和准确检测。然后，DenseNet被部署来识别这些物体。最后，将基于形态学运算和霍夫变换的材料计数模块应用于建筑材料堆垛的自动计数。发现在一个真实的室内建筑工地的视频片段中，通过计算现场作业人员和成堆的高架地砖来测试所提出的方法。与传统的YOLO v4方法相比，所提出的YOLO v4对象检测系统在更短的时间内提供了更高的平均精度。独创性/价值拟议的框架使在低光建筑环境中单独监测储存、安装和废弃材料变得可行。改进的YOLO v4检测方法优于现有的YOLO v4方法，并改进了现有的目标检测算法。该框架可以潜在地减少跟踪施工进度和清点材料所需的时间，从而提高在建工程评估的效率。它还显示出开发更可靠的建筑材料和活动监测系统的巨大潜力。
{"title":"Tracking indoor construction progress by deep-learning-based analysis of site surveillance video","authors":"Johnny Kwok-Wai Wong, Fateme Bameri, Alireza Ahmadian Fard Fini, M. Maghrebi","doi":"10.1108/ci-10-2022-0275","DOIUrl":"https://doi.org/10.1108/ci-10-2022-0275","url":null,"abstract":"\u0000Purpose\u0000Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.\u0000\u0000\u0000Design/methodology/approach\u0000A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.\u0000\u0000\u0000Findings\u0000The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.\u0000\u0000\u0000Originality/value\u0000The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.\u0000","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44766367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose Despite many studies on buildability from different perspectives and methods, the problems associated with buildability have not ceased from confronting the construction industry. This paper aims to determine the critical measures for improving the buildability of building designs in the construction industry. Design/methodology/approach A questionnaire was developed to address the aim of the study. Data were collected through the administration of questionnaires to purposively selected group of quantity surveyors, builders, engineers and architects. A total of 368 questionnaires were administered and a response rate of 60% (219 questionnaires were returned) was achieved. Data elicited were analysed using descriptive and inferential statistics. Findings The results revealed that “the benefits of improved buildability should be made known to designers”, “more technical literature for improving buildability should be provided to designers” and “more education and training on buildability should be given to designers” are the top most important three measures for improving the buildability of building designs in the construction industry. Originality/value This study highlights the measures for improving buildability of building designs which are considered significant by construction professionals. An understanding of these measures is essential for reducing buildability problems as well as for improving and embedding buildability as a practice in the construction industry.
{"title":"Measures for improving the buildability of building designs in construction industry","authors":"I. Osuizugbo","doi":"10.1108/ci-08-2022-0223","DOIUrl":"https://doi.org/10.1108/ci-08-2022-0223","url":null,"abstract":"\u0000Purpose\u0000Despite many studies on buildability from different perspectives and methods, the problems associated with buildability have not ceased from confronting the construction industry. This paper aims to determine the critical measures for improving the buildability of building designs in the construction industry.\u0000\u0000\u0000Design/methodology/approach\u0000A questionnaire was developed to address the aim of the study. Data were collected through the administration of questionnaires to purposively selected group of quantity surveyors, builders, engineers and architects. A total of 368 questionnaires were administered and a response rate of 60% (219 questionnaires were returned) was achieved. Data elicited were analysed using descriptive and inferential statistics.\u0000\u0000\u0000Findings\u0000The results revealed that “the benefits of improved buildability should be made known to designers”, “more technical literature for improving buildability should be provided to designers” and “more education and training on buildability should be given to designers” are the top most important three measures for improving the buildability of building designs in the construction industry.\u0000\u0000\u0000Originality/value\u0000This study highlights the measures for improving buildability of building designs which are considered significant by construction professionals. An understanding of these measures is essential for reducing buildability problems as well as for improving and embedding buildability as a practice in the construction industry.\u0000","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46159368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. J. Likita, M. B. Jelodar, Priya Vishnupriya, J. Rotimi
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.
{"title":"Lean and BIM integration benefits construction management practices in New Zealand","authors":"A. J. Likita, M. B. Jelodar, Priya Vishnupriya, J. Rotimi","doi":"10.1108/ci-06-2022-0136","DOIUrl":"https://doi.org/10.1108/ci-06-2022-0136","url":null,"abstract":"\u0000Purpose\u0000The 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.\u0000\u0000\u0000Design/methodology/approach\u0000A 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.\u0000\u0000\u0000Findings\u0000Lean 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.\u0000\u0000\u0000Originality/value\u0000This study practically focused on using the integration of BIM and Lean principles to improve the construction industry productivity and performance.\u0000","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46140882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose This study aims to develop a constructability index (CI) that can ease the construction activities in a project based on the contractors’ experience and resources. The proposed CI is a vital decision support tool that quantifies the difficulty level for the contractor to execute certain activities with the contingency of other project elements. The virtual reality (VR) technology was used to provide additional data, communicate the contingency impact of other project elements on specific activities and provide sequential execution data to the contractors. This can minimize the risk of not being able to execute various activities on time and within the budget. Design/methodology/approach The VR-based CI was developed through two steps. Step 1 was to identify the factors affecting constructability by exploring the literature and consulting local construction experts. These factors were then organized through a hierarchy of main factors and subfactors and validated by local experts through predesigned surveys. The factors were classified into VR dependent or non-VR independent, and their relative weights were calculated using the analytical hierarchy process along with their reliability, which was determined using Cronbach’s alpha approach. Step 2 was to define the attributes for the constructability factors defined in Step 1 using the Multi Attribute Utility Theory to quantify the contractor’s compliance level of these factors by giving them the appropriate score. The utility factors for the VR-independent factors were obtained through standards, literature and local surveys, and they were quantified on a 1–10 scale. However, the VR-dependent factors were given their corresponding scores using the developed VR navigation environment generated by integrating Autodesk Revit and Navisworks software. Accordingly, the CI for each activity was evaluated, and the overall CI for the project was calculated by aggregating the CIs for all activities. Findings The developed CI quantifies the contractor’s ability to execute construction projects and addresses the lack of communication and coordination between the various construction units in the planning phase itself. Moreover, it can resolve possible hard (physical) and soft (time) construction clashes and minimize their impacts on project schedule and budget. Among the relative weights of the identified factors, prefabrication of building components was found to have the highest effect on constructability. Furthermore, applying the developed VR-CI, a real project showed that the utility values of the main factors quantified on a ten-point scale were between 6 and 9, which means routine supervisions and monitoring are required. Originality/value Though the concepts of constructability and VR have been used in different contexts, their integration to develop a comprehensive CI for the building construction industry is a unique contribution, which has not been reported previously.
{"title":"A virtual reality-based constructability index for construction projects","authors":"A. Qasem, Abdulaziz S. Almohassen","doi":"10.1108/ci-11-2021-0210","DOIUrl":"https://doi.org/10.1108/ci-11-2021-0210","url":null,"abstract":"\u0000Purpose\u0000This study aims to develop a constructability index (CI) that can ease the construction activities in a project based on the contractors’ experience and resources. The proposed CI is a vital decision support tool that quantifies the difficulty level for the contractor to execute certain activities with the contingency of other project elements. The virtual reality (VR) technology was used to provide additional data, communicate the contingency impact of other project elements on specific activities and provide sequential execution data to the contractors. This can minimize the risk of not being able to execute various activities on time and within the budget.\u0000\u0000\u0000Design/methodology/approach\u0000The VR-based CI was developed through two steps. Step 1 was to identify the factors affecting constructability by exploring the literature and consulting local construction experts. These factors were then organized through a hierarchy of main factors and subfactors and validated by local experts through predesigned surveys. The factors were classified into VR dependent or non-VR independent, and their relative weights were calculated using the analytical hierarchy process along with their reliability, which was determined using Cronbach’s alpha approach. Step 2 was to define the attributes for the constructability factors defined in Step 1 using the Multi Attribute Utility Theory to quantify the contractor’s compliance level of these factors by giving them the appropriate score. The utility factors for the VR-independent factors were obtained through standards, literature and local surveys, and they were quantified on a 1–10 scale. However, the VR-dependent factors were given their corresponding scores using the developed VR navigation environment generated by integrating Autodesk Revit and Navisworks software. Accordingly, the CI for each activity was evaluated, and the overall CI for the project was calculated by aggregating the CIs for all activities.\u0000\u0000\u0000Findings\u0000The developed CI quantifies the contractor’s ability to execute construction projects and addresses the lack of communication and coordination between the various construction units in the planning phase itself. Moreover, it can resolve possible hard (physical) and soft (time) construction clashes and minimize their impacts on project schedule and budget. Among the relative weights of the identified factors, prefabrication of building components was found to have the highest effect on constructability. Furthermore, applying the developed VR-CI, a real project showed that the utility values of the main factors quantified on a ten-point scale were between 6 and 9, which means routine supervisions and monitoring are required.\u0000\u0000\u0000Originality/value\u0000Though the concepts of constructability and VR have been used in different contexts, their integration to develop a comprehensive CI for the building construction industry is a unique contribution, which has not been reported previously.\u0000","PeriodicalId":45580,"journal":{"name":"Construction Innovation-England","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48925337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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