The purpose of this thesis is to improve the 'art' of early capital cost estimation
of chemical process plants.
Capital cost estimates are required in the early business planning and feasibility
assessment stages of a project, in order to evaluate viability and to compare the
economics of the alternative processes and operating conditions that are under
consideration for the plant. There is limited knowledge about a new plant in the
early stages of process development. Nevertheless, accurate cost estimates are
needed to prevent incorrect decisions being made, such as terminating the
development of a would-be profitable plant.
The published early capital cost estimation methods are described. The methods
are grouped into three types of estimate: exponent, factorial and functional unit.
The performance of these methods when used to estimate the capital costs of
chemical plants is assessed. A new estimating method is presented. This method
was developed using the same standard regression techniques as used in the
published methods, but derived from a new set of chemical plant data.
The effect that computers have had on capital cost estimating and the future
possibilities for the use of the latest computer techniques are assessed. This leads
to the fuzzy matching technique being chosen to develop a new method for
capital cost estimation. The results achieved when using fuzzy matching to
estimate the capital cost of chemical plants are presented. These results show
that the new method is better than those that already exist. Finally, there is a
brief discussion of how fuzzy matching could be applied in the future to other
fields of chemical engineering.
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.