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Civil-Comp Proceedings
ISSN 1759-3433
CCP: 61
NOVEL DESIGN AND INFORMATION TECHNOLOGY APPLICATIONS FOR CIVIL AND STRUCTURAL ENGINEERING
Edited by: B. Kumar and B.H.V. Topping
Paper VI.3

Development of an Intelligent Decision Support System for Cost Escalation in the Heavy Engineering Industry

N. Dawood and W. Bates

School of Science and Technology, University of Teesside, Middlesbrough, England

Full Bibliographic Reference for this paper
N. Dawood, W. Bates, "Development of an Intelligent Decision Support System for Cost Escalation in the Heavy Engineering Industry", in B. Kumar, B.H.V. Topping, (Editors), "Novel Design and Information Technology Applications for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 113-126, 1999. doi:10.4203/ccp.61.6.3
Abstract
The heavy civil engineering industry (railways, sewage treatment, chemical and pharmaceutical facilities, oil and gas facilities, etc.) is one of the major contributors to the British economy and generally involves a high level of investment. Clients in this industry are demanding accurate cost estimate, proper analysis of out-turn cost and cost escalation and a high quality risk analysis throughout the construction processes. Current practices in the industry has suggested that there is a lack of, structured methodologies and systematic cost escalation approach to achieve an appropriate cost analysis at the outset of projects and throughout the construction processes. In this context the prime objective of this research work is to develop a structured cost escalation methodology for improving estimating management and control in the heavy engineering industry construction processes. The methodology is composed of a forecasting model to predict cost indices of major items in industry and a risk knowledge base model for identifying and quantifying causes of cost escalations.

This paper, as part of the research, reviews and discusses a knowledge based model for applying a cost escalation factor. The cost escalation factor is made up of market variation, a risk element and a component for bias. A knowledge elicitation strategy was employed to obtain the required knowledge for the model. The strategy included questionnaires, interviews and workshops and deliverables came in the form of influences and their effect on project cost escalation. From these deliverables the concept of a decision support model and system specification for applying cost escalation to base estimates is proposed.

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