Hussain, M A D (2001) Value engineering expert system in suburban highway design (VEESSHD). 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 |
| Index terms: | creativity, customer satisfaction, artificial neural network, neural network, value engineering, expert system, programming, methodology, program |
| Subjects: | value management, programming, artificial intelligence, modelling and simulation, service delivery, research methods, software systems, innovation and creative processes, data management |
| Topics: | Design Practice, Digital Applications, Stakeholder Management, Cost Management, Research Practice |
| Descriptive scope: | 3 PCT |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here