Predictive Model for Cement Clinker Quality ParametersReport as inadecuate




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Managers of cement plants are gradually becoming aware of the need for soft sensors in product quality assessment. Cement clinker quality parameters are mostly measured by offline laboratory analysis or by the use of online analyzers. The measurement delay and cost, associated with these methods, are a concern in the cement industry. In this study, a regression-based model was developed to predict the clinker quality parameters as a function of the raw meal quality and the kiln operating variables. This model has mean squared error, coefficient of determination, worst case relative error and variance account for in external data given as 8.96 × 10



Author: Nsidibe-Obong Ekpe Moses1, Sunday Boladale Alabi2*

Source: http://www.scirp.org/



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