Simulation modelling of a lumber manufacturing process for automation of the quality control function

Lumber size control for improvement of lumber recovery factor has been a major topic for research. However, no precise mathematical formulations have been developed so far for statistical process control in sawing. In this thesis, a mathematical model is developed using the Taguchi quadratic function for the optimization of a sawing process for determination of reliable sample sizes required for statistical process control in lumber manufacturing. The latter process has also been modelled by computer simulation using time series analysis and ordinary stochastic process generation techniques, for development of a knowledge-base to be applied in an expert system for automation of the lumber size quality function. A coherent strategy with well defined man-computer-machine interfaces is provided for automatic data collection using a laser sensor; data analysis using analytical computers and plotters, and correction of assignable causes in sawing using an expert system and an actuations generator.