Development of Rapid Capital Cost Estimation Techniques for the Chemical Processing Industries

Abstract

This thesis describes new developments in the 'step counting' concept of rapid pre-design capital cost estimation of chemical process plants. A series of simple, easy to use, mathematical cost models of varying sophistication and accuracy has been derived for estimating the battery limits investment cost of chemical plants processing gaseous/vapour phase materials. The research was developed from a literature survey of existing methods of capital cost estimation. Particular attention was given to pre-design estimating techniques which are reviewed and their shortcomings identified. From this analysis, new theories for advancing step counting methods are proposed, with careful attention being paid to the definition of the parameters in the cost correlations. These theories were applied to over one hundred sets of published capital cost data for petrochemical and organic chemical processes handling only gas phase materials. After careful standardisation a wide range of cost models of varying complexity were derived using multi-linear regression modelling techniques. The results obtained showed very good agreement with the source data, but when compared with other estimation procedures and tested on recent cost data, gave consistent but unnacceptably low results. This is due to a variety of factors of which unsatisfactory cost indices is believed to be the most significant. The models derived have been accordingly modified to give acceptable results. The range of models form a flexible and practical capital cost estimating package capable of meeting the various estimating situations and needs encountered by both process and cost engineers in the early stages of process design and development.