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Making Operational Strategies of Asphalt Teams Explicit to Reduce Process Variability
The on-site construction process undertaken by asphalt teams has a critical impact on pavement quality. Process improvement and learning require explicit information about the process. However, current on-site operational activities and key parameters are, in general, not systematically monitored and mapped. The lack of process information makes it difficult for contractors and asphalt teams to distinguish between good and poor practices and to improve. Although technologies to make the on-site process explicit are becoming widely available, their adoption has been slow. To overcome this knowledge gap regarding explicit information about the on-site construction process, this paper proposes a framework and utilizes technologies for the systematic monitoring and mapping of on-site activities and key parameters. Various technologies and sensors, such as a global positioning system (GPS), a laser linescanner, and infrared cameras, make it possible to track the on-site movements of machinery and asphalt temperatures during construction. This framework was applied and refined during 29 asphalting projects in the Netherlands, creating an extensive set of on-site process data. Considerable variability was found in the delivered asphalt temperatures, the asphalt cooling, the compaction process and density progression, and the movements of machinery. This variability offers opportunities where action could be taken to improve process quality by reducing process variability. The framework and explicit data can help asphalt teams to verbalize their tacit knowledge and make their own processes and choices transparent and further promotes learning processes. This paper contributes to a deeper understanding of the on-site construction process and highlights how to encourage technology adoption in construction.
Making Operational Strategies of Asphalt Teams Explicit to Reduce Process Variability
The on-site construction process undertaken by asphalt teams has a critical impact on pavement quality. Process improvement and learning require explicit information about the process. However, current on-site operational activities and key parameters are, in general, not systematically monitored and mapped. The lack of process information makes it difficult for contractors and asphalt teams to distinguish between good and poor practices and to improve. Although technologies to make the on-site process explicit are becoming widely available, their adoption has been slow. To overcome this knowledge gap regarding explicit information about the on-site construction process, this paper proposes a framework and utilizes technologies for the systematic monitoring and mapping of on-site activities and key parameters. Various technologies and sensors, such as a global positioning system (GPS), a laser linescanner, and infrared cameras, make it possible to track the on-site movements of machinery and asphalt temperatures during construction. This framework was applied and refined during 29 asphalting projects in the Netherlands, creating an extensive set of on-site process data. Considerable variability was found in the delivered asphalt temperatures, the asphalt cooling, the compaction process and density progression, and the movements of machinery. This variability offers opportunities where action could be taken to improve process quality by reducing process variability. The framework and explicit data can help asphalt teams to verbalize their tacit knowledge and make their own processes and choices transparent and further promotes learning processes. This paper contributes to a deeper understanding of the on-site construction process and highlights how to encourage technology adoption in construction.
Making Operational Strategies of Asphalt Teams Explicit to Reduce Process Variability
Bijleveld, F. R. (Autor:in) / Miller, S. R. (Autor:in) / Dorée, A. G. (Autor:in)
07.01.2015
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Making Operational Strategies of Asphalt Teams Explicit to Reduce Process Variability
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