Application of Statistical Approaches for the Development of Cost Estimation Models for Jaw Crushers

摘要

Adequate estimation of equipment costs is a key factor in a feasibility study and in evaluation ofrndesign alternatives for mining and mineral processing projects. Inaccurate early cost estimationrncould lead to the elimination of investment benefi ts. However, this estimation is complex and timernconsuming because of data accessibility problems and consequently access to a rapid, up-to-date andrnaccurate tool is desirable for carrying out cost estimations.rnThis paper describes the development of models for estimating capital and operating costs forrna jaw crusher, which is used as the primary crusher for a wide variety of mineral benefi ciationrnplants, applying single and multivariate regression analyses, together with the design of experimentrnapproach, based on principal component analysis. Explanatory variables include gape size, length ofrnfeed opening and power as numeric (quantitative) variables and toggle type (single or double) andrnthe existence of extra heavy duty construction as categorical (qualitative) variables. The performancernof each model has been investigated and comparing the estimated R-squared (R2) of each model, thernbest was selected and its validity examined. The cost models include the capital and operating costsrnalong with the operating cost components. The results indicate that the suggested best cost model isrnsuffi ciently accurate for use in feasibility studies.