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Ahn, C R and Lee, S (2013) Importance of Operational Efficiency to Achieve Energy Efficiency and Exhaust Emission Reduction of Construction Operations. Journal of Construction Engineering and Management, 139(04), 404–13.

Bowen, P, Edwards, P and Lingard, H (2013) Workplace Stress Experienced by Construction Professionals in South Africa. Journal of Construction Engineering and Management, 139(04), 393–403.

Fernandez-Solis, J L, Porwal, V, Lavy, S, Shafaat, A, Rybkowski, Z K, Son, K and Lagoo, N (2013) Survey of Motivations, Benefits, and Implementation Challenges of Last Planner System Users. Journal of Construction Engineering and Management, 139(04), 354–60.

Forcada, N, Macarulla, M and Love, P E D (2013) Assessment of Residential Defects at Post-Handover. Journal of Construction Engineering and Management, 139(04), 372–8.

Kang, Y, O’Brien, W J, Dai, J, Mulva, S P, Thomas, S P, Chapman, R E and Butry, D (2013) Interaction Effects of Information Technologies and Best Practices on Construction Project Performance. Journal of Construction Engineering and Management, 139(04), 361–71.

Lorterapong, P and Ussavadilokrit, M (2013) Construction Scheduling Using the Constraint Satisfaction Problem Method. Journal of Construction Engineering and Management, 139(04), 414–22.

Solis, F, Sinfield, J V and Abraham, D M (2013) Hybrid Approach to the Study of Inter-Organization High Performance Teams. Journal of Construction Engineering and Management, 139(04), 379–92.

Son, H and Kim, C (2013) Multiimaging Sensor Data Fusion-Based Enhancement for 3D Workspace Representation for Remote Machine Operation. Journal of Construction Engineering and Management, 139(04), 434–44.

Turkan, Y, Bosché, F, Haas, C T and Haas, R (2013) Toward Automated Earned Value Tracking Using 3D Imaging Tools. Journal of Construction Engineering and Management, 139(04), 423–33.

  • Type: Journal Article
  • Keywords: Building information models; Construction management; Construction costs; Standards and codes; Imaging techniques; Building information models (BIM); Four-dimensional; Five-dimensional; Construction progress control; Cost codes; Earned value; Laser scanni
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000629
  • Abstract:
    Accurate and frequent construction progress tracking provides critical input data for project systems such as cost, schedule control, and billing. Unfortunately, conventional progress tracking is labor intensive, sometimes subject to negotiation, and often driven by arcane rules. Attempts to improve progress tracking have recently focused on automation, using technologies such as three-dimensional imaging, global positioning systems, ultra wide band (UWB) indoor locating, handheld computers, voice recognition, wireless networks, and other technologies in various combinations. However, one limit of these approaches is their focus on counting objects or milestones rather than value. In this paper, a four-dimensional model recognition-driven automated progress tracking system that transforms objects to their earned values is examined via the analysis of data from the construction of a steel reinforced concrete structure and a steel structure. It is concluded that automated, object oriented recognition systems that convert each object to its earned value can substantially improve the accuracy of progress tracking, and thus, better support project systems like billing. The contribution of this study is an argument based on scientific results for refocusing future research onto automated earned value tracking, which is ultimately what is needed in practice.

Vaughan, J L, Leming, M L, Liu, M and Jaselskis, E (2013) Cost-Benefit Analysis of Construction Information Management System Implementation: Case Study. Journal of Construction Engineering and Management, 139(04), 445–55.