Assessing the impact of materials tracking technologies on construction craft productivity

Grau, David; Caldas, Carlos H.; Haas, Carl T.; Goodrum, Paul M.; Gong, Jie

doi:10.1016/j.autcon.2009.04.001

Cited by 122 publications

(69 citation statements)

References 18 publications

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“…The identified practices related to PM practices specified by the PMI (2000) and the CII (2011). Construction practices like the use of a material tracking system have been shown to significantly improve CLP (Grau et al 2009;Chanmeka et al 2012); however, such practices have not been properly integrated into CLP analysis and modeling efforts. In this research, the practices will be used to clearly define the context (external environment) of each project, helping to explain why CLP varies from project to project.…”

Section: Research Methodology For Identification Of Key Parametersmentioning

confidence: 99%

Identification and comparative analysis of key parameters influencing construction labour productivity in building and industrial projects

Assefa

Robinson

2014

Can. J. Civ. Eng.

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Parameters (factors and practices) influencing construction labour productivity are multi-faceted and project dependent. A proven measurement scheme and modeling approach to investigate the effect of parameters on construction labour productivity has not yet been developed. This study identifies key parameters influencing labour productivity using contextsensitive surveys that reveal contextual differences between key parameters. The study relies on data collected through 141 surveys administered to project management and trade respondents from six Canadian projects in either of two contexts: building and industrial. Analysis revealed the top parameters influencing labour productivity on building and industrial projects. Consensus between project management and trade level respondents regarding parameters' effects within and between contexts was evaluated using statistical analysis; results indicated some differences in perception. The methodology and findings from this paper are useful for identifying enablers of and barriers to better productivity, developing context-sensitive labour productivity models for use in analysis, and developing productivity improvement strategies.Key words: construction labour productivity, parameters, practices, factors, surveys, context analysis.Résumé : Les paramètres (facteurs et pratiques) influençant la productivité de la main d'oeuvre dans le domaine de la construction ont plusieurs volets et sont fonction du type de projet. Aucune mesure éprouvée ni approche de modélisation n'ont été développées pour examiner l'effet de ces paramètres sur la productivité de la main d'oeuvre dans le domaine de la construction. La présente étude identifie des paramètres clés influençant la productivité de la main d'oeuvre en utilisant des sondages sensibles au contexte qui révèlent les différences contextuelles entre les paramètres clés. L'étude se base sur des données colligées dans 141 sondages envoyés à des répondants en gestion de projet et des métiers dans six projets canadiens dans l'un ou l'autre des contextes suivants : construction en bâtiments et industrielle. L'analyse a révélé les principaux paramètres influençant la productivité de la main d'oeuvre dans les projets industriels et de bâtiments. Le consensus entre les répondants en gestion de projet et des métiers sur les effets des paramètres dans chaque contexte et entre eux a été évalué par analyse statistique. Les résultats montrent certaines différences dans la perception. La méthode et les conclusions du présent article seront utiles pour identifier les catalyseurs et les barrières à une meilleure productivité, développer des modèles de productivité de la main d'oeuvre sensibles au contexte qui seront utilisés dans les analyses et pour développer des stratégies d'amélioration de la productivité. [Traduit par le Rédaction] Mots-clés : productivité de la main d'oeuvre dans le domaine de la construction, paramètres, pratiques, facteurs, sondages, analyse contextuelle.

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Section: Research Methodology For Identification Of Key Parametersmentioning

confidence: 99%

Identification and comparative analysis of key parameters influencing construction labour productivity in building and industrial projects

Assefa

Robinson

2014

Can. J. Civ. Eng.

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“…And the most popular researching topic is about influences of the high technology on construction labor productivity, represented by information technology. Grau et al compare the productivity differences between traditional material management and automated material management with updated in-formation technology [4]. The result indicates that automated management significantly improves labor productivity.…”

Section: Reviews Of Development In Construction Labor Productivitymentioning

confidence: 99%

Overview and Prospect of Construction Labor Productivity

Shang¹,

Zhai²

2016

Proceedings of the 6th International Conference on Electronic, Mechanical, Information and Management Society

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Abstract. The paper classifies construction labor productivity from macro industry level to micro activity level and combs the research status at home and abroad of it, including the definition, calculation, evaluation system, affecting factors and affecting capacities. These help researchers to have a comprehensive and three-dimensional understanding of construction labor productivity and lay a solid foundation for the future theoretical studies and practical studies on it. At last, 4 future research topics are suggested.

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“…Recent lean process control systems, for example Sacks et al [29], try to design and test a BIMbased workflow information system to help construction personnel implement lean pull flow strategies. A reason that they exist is that it is often very difficult to coordinate the work of multiple subcontractors in the working interface when only a traditional master plan and schedule is used [30][31].…”

Section: Workpace Modeling and Visualizationmentioning

confidence: 99%

Global Positioning System Data to Model and Visualize Workspace Density in Construction Safety Planning

Zhang¹,

Teizer²,

Pradhananga

2015

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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Safety as well as productivity performance in construction is often poor due to congested site conditions. We lack a formalized approach in effective activity-level construction planning to avoid workspace congestion. The objective of this study is to investigate and prototype a new Building Information Modeling (BIM) enabled approach for activity-level construction planning that can proactively improve construction safety. The presented method establishes automated workspace visualization in a building information model, using workspace modeling as an integral part of construction safety planning. Algorithms were developed for extracting activity-specific workspace parameters from workforce location tracking data. Global Positioning System (GPS) data loggers were attached to the workers' hardhats during the stripping activities of formwork of columns. Workspaces were then visualized on a BIM platform. The developed method can support project stakeholders, such as engineers, planners, construction managers, and site workers with the identification and visualization of required and congested workspaces, hence improving the foundation on how decisions are made related to construction site safety and health, as well as its potential impact on a productive, unobstructed work environment.

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Assessing the impact of materials tracking technologies on construction craft productivity

Cited by 122 publications

References 18 publications

Identification and comparative analysis of key parameters influencing construction labour productivity in building and industrial projects

Identification and comparative analysis of key parameters influencing construction labour productivity in building and industrial projects

Overview and Prospect of Construction Labor Productivity

Global Positioning System Data to Model and Visualize Workspace Density in Construction Safety Planning

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