Van Uu Nguyen, M. ” Tender evaluation by fuzzy sets”, J. Construction engineering and management, ASCE, Vol. 111, No. 3, 1985, PP. 231-243.
 Karia Knight, Amina R. F.,” Use of fuzzy logic for predicting design cost overruns on building projects”, J. Construction engineering and management, ASCE, Vol. 128, No. 6, 2001, PP. 503-512.
 Ganoud A., Ali H. A., & Ibrahem S., ” Studying the influence of Random Factors on the planning of Building Works”, Tishreen U. J. Eng. Science Series Vol. 27, No. 3, 2005.
 Saaty T. L.,” The Analytic Hierarchy Process”, McGraw-Hill, Inc., 1980, Reprinted by RWS Publications,1996, Pittsburgh.
 Saaty T.L., 1986. Axiomatic foundation of the Analytic Hierarchy Process, Management Science, 32(7), .841-855
 Saaty T.L., 1992. Decision making for leaders, RWS Publications, Pittsburgh, USA.
 Marsh et. Al. DRAFT,” Hierarchical Decision Making in Machine Design”, July, 1993.
Tikrit Journal of Engineering Sciences (2013) 20(1) 1-14
Using the Techniques of Decision-Making and Statistical Experiments Design in Prediction of the Random Factors Impacts on Implementation of Construction Project Plan
|Salim Abdulla Salih||Nizar Numan Ismail|
|Mechanical Eng. Dept., Tikrit University, Iraq||Environmental Eng. Dept., Tikrit University, Iraq|
Accelerated development and use of decision-making technology, including the analytical hierarchy process (AHP) which has a high reliability to solve most of the uncertainty problems and meet their practical requirements, which enabled it to be used in a number of engineering and administrative applications. Statistical design of experiments technology is considered essential keys to deal with random data. Their important features enables us to combine them in a appropriate scenario to predict the prospects and rates of random factors and determine the extent of their impact on the delay for the implementation of a project. This research verified and reach the possibility of using these two techniques in the development of mutual influence between each of random factors, a very high correlation has been proved among such factors, where the correlation coefficient between them is equal to the value (1), a mathematical models that govern random factors effects was built by using of Statistical analysis of variance (Anova) and multiple linear regression to find mathematical models that found to be had a high resolution through R2 and F tests which gave (R2 = 1, F > = 1.18E +32) results. These models are used to build a scenario to predict the expectations of potential for the disposal of these factors during the annual monthly plan, and treatment to avoid random effects on the implementation of the project and the planned completion time.
Keywords: Analytical Hierarchy Process AHP, Statistical Design of Experiments DOE, Random Factors, Construction Project Plan.