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Al-Hussein, M, Alkass, S and Moselhi, O (2005) Optimization Algorithm for Selection and on Site Location of Mobile Cranes. Journal of Construction Engineering and Management, 131(05), 579–90.
Bernold, L E (2005) Paradigm Shift in Construction Education is Vital for the Future of Our Profession. Journal of Construction Engineering and Management, 131(05), 533–9.
Dunston, P S, Gambatese, J A and McManus, J F (2005) Assessing State Transportation Agency Constructability Implementation. Journal of Construction Engineering and Management, 131(05), 569–78.
El-Diraby, T E and Kashif, K F (2005) Distributed Ontology Architecture for Knowledge Management in Highway Construction. Journal of Construction Engineering and Management, 131(05), 591–603.
Georgy, M E, Chang, L and Zhang, L (2005) Prediction of Engineering Performance: A Neurofuzzy Approach. Journal of Construction Engineering and Management, 131(05), 548–57.
Georgy, M E, Chang, L and Zhang, L (2005) Utility-Function Model for Engineering Performance Assessment. Journal of Construction Engineering and Management, 131(05), 558–68.
- Type: Journal Article
- Keywords: Performance evaluation; Productivity; Measurement; Construction industry;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)0733-9364(2005)131:5(558)
- Abstract:
Engineering and design activities constitute a critical link in a project’s life cycle. Thus, an efficient project control system requires an instrument to measure and assess engineering performance among different projects. In conventional industry practices, the measurement of engineering performance is usually tied to the production of design documents during the detailed design phase of the project. Realizing the far-reaching impacts of engineering activities, researchers in the past have investigated other comprehensive measures of engineering performance that address the entire project life cycle. As part of a study for the Construction Industry Institute, this particular research employs a multiple attribute utility function method for the collective assessment of engineering performance in construction projects. The paper begins with a summary of previous studies in the area of engineering performance measurement and assessment. Afterwards, the concept of engineering performance is thoroughly explained. The paper then reviews the background and basic theories of using utility functions in assessing engineering performance, along with an illustrative example of the functionality of this approach. The paper goes on to show the development of the utility function model for the industrial construction sector through expert opinion and real project data. The use of the model is further illustrated in the assessment of total and relative engineering performance. Lastly, conclusions of this study are drawn and potential future work is pointed out.
Hegazy, T and Zhang, K (2005) Daily Windows Delay Analysis. Journal of Construction Engineering and Management, 131(05), 505–12.
Hegazy, T, Elbeltagi, E and Zhang, K (2005) Keeping Better Site Records Using Intelligent Bar Charts. Journal of Construction Engineering and Management, 131(05), 513–21.
Kim, K and de la Garza, J M (2005) Evaluation of the Resource-Constrained Critical Path Method Algorithms. Journal of Construction Engineering and Management, 131(05), 522–32.
Lueke, J S and Ariaratnam, S T (2005) Surface Heave Mechanisms in Horizontal Directional Drilling. Journal of Construction Engineering and Management, 131(05), 540–7.
Sacks, R, Navon, R, Brodetskaia, I and Shapira, A (2005) Feasibility of Automated Monitoring of Lifting Equipment in Support of Project Control. Journal of Construction Engineering and Management, 131(05), 604–14.