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East, E W and Liu, L Y (2006) Multiproject Planning and Resource Controls for Facility Management. Journal of Construction Engineering and Management, 132(12), 1294–305.

Elazouni, A M (2006) Classifying Construction Contractors Using Unsupervised-Learning Neural Networks. Journal of Construction Engineering and Management, 132(12), 1242–53.

Elmisalami, T, Walters, R and Jaselskis, E J (2006) Construction IT Decision Making Using Multiattribute Utility Theory for Use in a Laboratory Information Management System. Journal of Construction Engineering and Management, 132(12), 1275–83.

Menches, C L and Hanna, A S (2006) Conceptual Planning Process for Electrical Construction. Journal of Construction Engineering and Management, 132(12), 1306–13.

Menches, C L and Hanna, A S (2006) Quantitative Measurement of Successful Performance from the Project Manager’s Perspective. Journal of Construction Engineering and Management, 132(12), 1284–93.

Moussa, M, Ruwanpura, J and Jergeas, G (2006) Decision Tree Modeling Using Integrated Multilevel Stochastic Networks. Journal of Construction Engineering and Management, 132(12), 1254–66.

Sharma, V, Al-Hussein, M and AbouRizk, S M (2006) Residential Construction Lot Grading Approval Process Optimization: Case Study of City of Edmonton. Journal of Construction Engineering and Management, 132(12), 1225–33.

  • Type: Journal Article
  • Keywords: Buildings, residential; Computer aided simulation; Automation; Canada; Case reports;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2006)132:12(1225)
  • Abstract:
    Rapid growth of residential construction in the city of Edmonton, Alberta, Canada has led to an increased demand for lot grading (LG) inspectors. The traditional inspection process has contributed to inspection delays, backlog, and decreased customer satisfaction. The aim of the research presented in this paper is to study, evaluate, and optimize the existing LG approval process. Data from past years were collected and analyzed to establish a baseline performance level. Flowcharts were developed to visualize the process and a survey was conducted to determine potential areas of improvement from the perspectives of different shareholders. Lean thinking principles were applied to identify and reduce the nonvalue added activities and improve performance. The final phase of the research involved the simulation of the process to evaluate the impact of the implementation of various recommendations. Based on the simulation results, final recommendations were made and later implemented with the help from the city’s Information technology department. These modifications to the existing process produced significant gains in quality and productivity, as predicted by the simulation model.

Song, Y and Chua, D K H (2006) Modeling of Functional Construction Requirements for Constructability Analysis. Journal of Construction Engineering and Management, 132(12), 1314–26.

Su, Y Y, Hashash, Y M A and Liu, L Y (2006) Integration of Construction As-Built Data Via Laser Scanning with Geotechnical Monitoring of Urban Excavation. Journal of Construction Engineering and Management, 132(12), 1234–41.

Zhang, H, Tam, C M, Li, H and Shi, J J (2006) Particle Swarm Optimization-Supported Simulation for Construction Operations. Journal of Construction Engineering and Management, 132(12), 1267–74.