Value engineering expert system in suburban highway design (VEESSHD)

Hussain, M A D (2001) Value engineering expert system in suburban highway design (VEESSHD). Unpublished PhD thesis, University of Pittsburgh, USA.

Abstract

Value Engineering (VE) is a professionally applied, function-oriented, systematic team approach used to analyze and improve value in a product, facility design, system or service. VE is a powerful methodology for solving problems and/or reducing costs while improving performance/quality requirements. By enhancing value characteristics, VE increases customer satisfaction and adds value to an investment. Several studies have been developed to computerize this process. Most of them concentrate on the quantitative part of the process. The VE process consists of several phases, including the creativity phase and evaluation phase. Creativity depends on the human brain and cannot be computerized easily by conventional programming techniques. For this reason, the present research attempts to design an ES called Value Engineering Expert System in Suburban Highway Design (VEESSHD). VEESSHD employs the power and abilities of Expert Systems (ES) in solving complex problems to assist VE team in suburban highway design. The required knowledge and data for VEESSHD was extracted from the National Cooperative Highway Research Program (NCHRP) Report 282. Artificial Neural Networks (ANN) were employed as a complementary technique to treat the missing data. VEESSHD is intended to save experts' time and to encourage the exchange experience amongst team members. VEESSHD has been validated and found to be efficient based on the goal of this research and compared to the examples in NCHRP Report 282. Some future improvements are recommended to make the system more useful and to cover more areas in highway design.

Item Type: Thesis (Doctoral)
Thesis advisor: Bullen, A G R
Uncontrolled Keywords: highway; artificial neural network; creativity; expert system; investment; programming; value engineering; neural network
Date Deposited: 16 Apr 2025 19:24
Last Modified: 16 Apr 2025 19:24