The cement industry provides high wear environment for many casting units which results in high production costs and consumes both the time and efforts of different available skills to investigate and replace the worn parts. Aims to consider a predictive system for the wear of such units that will reduce the related unpredicted incidents.
In this work, cement mill shell liners are non‐repairable castings and subjected to accelerated deterioration process as the operational hours and hence the production increases. Both decision variables and their interaction were used to construct models that best describe the wear process of the shell lines for two compartments' ball mill. Data from past records were used and analyzed using the statistical package SPSS version 10.0.
The best regression model for each compartment was found to be exponential function but with different shape parameters. Some data were used to validate the model using statistical calculations of errors. The proposed models were used to develop the best operational time for liners' replacement strategy.
The findings of the optimal replacement time resulted in higher mill productivity, lower specific power consumption, reduced spare parts cost and reduced production loss for unjustified mill stoppages.
Develops a mathematical model for cement mill shell liners' life to determine the optimal replacement strategy.
