Abstracts – Browse Results

Search or browse again.

Click on the titles below to expand the information about each abstract.
Viewing 14 results ...

AbouRizk, S M and Wales, R J (1997) Combined Discrete-Event/Continuous Simulation for Project Planning. Journal of Construction Engineering and Management, 123(01), 11–20.

Crowley, L G (1997) Robust Statistical Estimators for Use within Competitive Bid Data. Journal of Construction Engineering and Management, 123(01), 53–63.

Daoud, O E K (1997) The Architect/Engineer's Role in Rehabilitation Work. Journal of Construction Engineering and Management, 123(01), 1–5.

Elazouni, A M (1997) Constructability Improvement of Steel Silos during Field Operations. Journal of Construction Engineering and Management, 123(01), 21–25.

Everett, J G and Farghal, S H (1997) Data Representation for Predicting Performance with Learning Curves. Journal of Construction Engineering and Management, 123(01), 46–52.

Farghal, S H and Everett, J G (1997) Learning Curves: Accuracy in Predicting Future Performance. Journal of Construction Engineering and Management, 123(01), 41–45.

  • Type: Journal Article
  • Keywords:
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(1997)123:1(41)
  • Abstract:
    Many repetitive construction field operations exhibit a phenomenon known as the learning or experience effect. A learning curve is generated when the time or cost required to complete one cycle of an activity is plotted as a function of the cycle number. For practicing construction engineers and managers, the greatest potential value of learning curves lies in their ability to predict future performance, instead of fitting historical data. This paper presents a new method for using learning curves to predict the time or cost to complete the remaining cycles of an activity in progress, to assess the accuracy of this method, and to compare the accuracy of this method with the standard forecasting technique used in construction cost reporting. Using the proposed method, the accuracy of predicting the time or cost required to complete an ongoing activity improves dramatically for about the first 25–30% of the activity and then levels off to within 15–20% of the actual value. Compared to the standard method using the cumulative average, the new learning curve method is shown to be more accurate. The analysis quantifies the trade-off between accuracy of predicting future performance and the timeliness and potential value of such a prediction.

Kangari, R and Miyatake, Y (1997) Developing and Managing Innovative Construction Technologies in Japan. Journal of Construction Engineering and Management, 123(01), 72–78.

Kartam, S, Ballard, G and Ibbs, C W (1997) Introducing a New Concept and Approach to Modeling Construction. Journal of Construction Engineering and Management, 123(01), 89–97.

Mondorf, P E, Kuprenas, J A and Kordahi, E N (1997) Segmental Cantilever Bridge Construction Case Study. Journal of Construction Engineering and Management, 123(01), 79–84.

Russell, J S, Jaselskis, E J and Lawrence, S P (1997) Continuous Assessment of Project Performance. Journal of Construction Engineering and Management, 123(01), 64–71.

Shi, J and AbouRizk, S M (1997) Resource-Based Modeling for Construction Simulation. Journal of Construction Engineering and Management, 123(01), 26–33.

Songer, A D and Molenaar, K R (1997) Project Characteristics for Successful Public-Sector Design-Build. Journal of Construction Engineering and Management, 123(01), 34–40.

Tiong, R L K and Alum, J (1997) Final Negotiation in Competitive BOT Tender. Journal of Construction Engineering and Management, 123(01), 6–10.

Touran, A, Sheahan, T C and Ozcan, E (1997) Rational Equipment Selection Method Based on Soil Conditions. Journal of Construction Engineering and Management, 123(01), 85–88.