Model Development of Constructability

M. Malek


The choice of the construction system is a multivariate decision making with criteria that vary from one project to the other, depending on the particularities and constraints imposed on the builder. This research develops a tool that measures the constructability of various construction projects. The decision making logic is based on fuzzy set theory (FST). FST is used to address uncertainties in decision making. The tool is generic enough to allow the user to encompass the criteria of the project at hand and to select the construction system best suited for its execution. The objective of this research is the development of the decision support model and the demonstration of its use. This research also furnishes an extensive environment for further development. It provides the blueprint to achieve the overall goal of assessing the project constructability and smoothes the path for further refinement of the rules to be used at each step of the overall model. Through this model users are able to predict the feasibility of a project, and determine the most advantageous system to be used for its implementation. An analysis of the model illustrates that the results are accurate and the system demonstrates utility for practical use.


Fuzzy Set Theory; Constructability; Modus Ponen

Full Text:



Ammar, S., Alwa, F., & Wright, R. (1995). A fuzzy logic approach to performance evaluation. Maryland: Proceedings of ISMU-NAFIPS.

Anderson, S., Gupta, V et al. (1995). Total constructability management: a process-oriented framework. Project Management Journal.

Assakaf, 1.& Ayyub, B. (1995). Reliability-based design of unstiffened panels for ship structures. Maryland: Proceedings of ISMU-NAFIPS.

Bousbaine, A. (1991). An expert system prototype for construction planning and productivity analysis. Dissertation for Ph.D.

Boyce, W. (1991). Designing for constructability. Journal of Performance of Constructed Facilities, 2.

Boyce, W. (1994). Design for constructability. Hydrocarbon Processing Journal,73.

Cambron, K. & Evans, G. (1991). Layout design using the analytic hierarchy process. Computers Ind. Engng, 20(2): 211-229.

Chang, T., Ibbs, W. & Crandall, K. (1990). Network resource allocation with support of a fuzzy expert system. Journal of Construction Engineering and Management, 116.

Chou, K. (1995). Teaching of uncertainty analysis and risk assessment in civil engineering. Maryland: Proceedings ofISMU-NAFIPS.

Construction Management Committee of ASCE Construction Division. (1991).

Constructability and constructability programs: White paper. Journal of Construction Engineering and Management, 117(1).

Cook, T. & Russell, R. Introduction to Management Science(Fifth ed).

Cross,V. & Sudkamp, T. (1994) Patterns of fuzzy rule-based inference. International Journal of Approximate Reasoning, 11(11):235-255.

Grabisch, M. (1995, Feb.). Fuzzy integral in multicriteria decision making. Fuzzy Sets and Systems,69(3):279-298.

Klir, G. & Yuan, B. (1995). Fuzzy sets and fuzzy logic: Theory and applications. New Jersey: Prentice-Hall.

Kuan, et al. (1992). Fuzzy logic control of steam generators water level in pressurized water reactors. Journal of Nuclear Technolog, 100.

Mansour, P. & Usman, M. (1994). A study of construction quality by the analysis of rework costs. Salzburg, Austria: Proceedings of XXII IAHSIFIU World Congress.

McCauley Bell, P. (1993) A fuzzy linguistic artificial intelligence model for assessing risks of cumulative trauma disorders of the forearm and head. Dissertation for Ph.D.

Moore, D. (1993). Buildability and skill concept packages: Development of a possible design tool. Journal of Building Research and Information. 2.1.

Moore, D. & Tunnicliffe, A. (1994). Development of an automated design aid (ADA) for improved buildability and accelerated learning. Proceedings of Automation and Robotics in Construction.

Muhanna, R. & Ayyub, B. (1995, Sept.). Modeling geometric uncertainties of continuum structures for reliability assessment purposes. Maryland: Proceedings of ISMU-NAFIPS.

Mullens, M., Gawlik T. & Malek, M. (1995). Benchmarking the constructability of the MIT roof system on IBACOS lab home B. Pittsburgh, PA,Energy Efficient Industrialized Housing (EEIH) Research Program.

Mustafa M., & Al-Bahar, 1. (1991). Project risk assessment using the analytic hierarchy process. IEEE Transactions on Engineering Management, 35.

O'Connor, 1. (1988). Constructability improvement during field operations. Journal of Construction Engineering and Management. 114(4).

O'Conner, 1. & Miller, S. (1994). Constructability programs: Methods for assessment and benchmarking. Journal of Performance of Constructed Facilities. 8.

O'Conner, 1. & Miller, S. (1995). Overcoming barriers to successful constructability implementation. Journal of Performance of Constructed Facilities,2.

Okuma, A. (1985). Software and fuzzy logic let any good programmer design an expert system. Maryland: Proceedings of ISMU-NAFIPS.

Patev, R. (1995). Reliability assessment of pile-founded navigation structures. Maryland: Proceedings of ISMU-NAFIPS.

Pepper, H., III. (1994). The benefits of constructability reviews during the design of environmental projects. Cost Engineering Journal, 36.

Russell, 1. & Gugel, 1. (1993). Comparison of two corporate constructability programs. Journal of Construction Engineering and Management.

Saaty, T. (1994). How to make a decision: The analytic hierarchy process. Interfaces, 24(6): 19-43.

Samuels, A. (1994). Construction facilities audit: Quality system-performance control. Journal of Management in Engineering.

Schmitz, W. & Von Rosenvinge, T., IV. (1994). The key is constructability. Journal of Civil Engineering.

Singh, A& Ebeling, K. (1994). Construction process simulation using a standardized configuration and model. Project Management Journal.

Singh, A& Talavage, 1. (1991). Methodology for design of efficient flexible construction systems. Engineering Management Journal, 1.

Swiatlowski, D. & Isik, C. (1995). Combinability functions in defuzzification. Maryland: Proceedings of ISMU-NAFIPS.

Vachtsevanos, G. et al. (1993). Fuzzy logic control of an automotive engine. IEEE Control Systems.

Wakefield, R. & Carmichael, D. G. (1994). Construction and management: Recent advances. Sydney, Australia: Proceedings of the National Construction And Management Conference. Sydney, Australia.

Warburton, D. (1992). How to design fuzzy logic controller. Machine Design.

Winkler, R. (1990). Decision modeling and rational choice: AHP and the utility theory. Management Science, 36(3).

Yurtser, T. (1992). Fuzzy logic expert system schedule. Austin, Texas: Report for Motorola, Inc.

Zadeh, L. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and System, 1:3-28.

Zadeh, L. (1983). The role of fuzzy logic in the management of uncertainty in expert systems. Fuzzy Sets and Systems. 11(3): 199-227.



  • There are currently no refbacks.

Copyright (c)

Share us to:   


  • How to do online submission to another Journal?
  • If you have already registered in Journal A, then how can you submit another article to Journal B? It takes two steps to make it happen:

1. Register yourself in Journal B as an Author

  • Find the journal you want to submit to in CATEGORIES, click on “VIEW JOURNAL”, “Online Submissions”, “GO TO LOGIN” and “Edit My Profile”. Check “Author” on the “Edit Profile” page, then “Save”.

2. Submission

  • Go to “User Home”, and click on “Author” under the name of Journal B. You may start a New Submission by clicking on “CLICK HERE”.

We only use three mailboxes as follows to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases:;;

 Articles published in Management Science and Engineering are licensed under Creative Commons Attribution 4.0 (CC-BY).


Address:1020 Bouvier Street, Suite 400, Quebec City, Quebec, G2K 0K9, Canada.

Telephone: 1-514-558 6138
Http:// Http://

Copyright © 2010 Canadian Research & Development Centre of Sciences and Cultures