| The main objective of this research was to develop a disc cutter chip production rate predictor model by using fuzzy logic. The performance of three different disc cutters (wide, narrow, long bladed narrow) was assessed on a linear rock cutting machine used to limit the fundamental relationships governing chip weights for Joachim Limestone and Roubidoux Sandstone. An accurate and reliable prediction of the disc cutter chip production rate was derived using chip weights, cut length, cut speed, cutting forces, spacing and penetration, which are elements critical to successful planning and execution of mechanical tunneling projects.;Mamdani and Sugeno fuzzy logics were adapted to model subjective and quantified data sets. The modeling procedures for both algorithms included identification of input and output variables, fuzzification of input and output variables, multivariable linear regression, fuzzy If-Then rule statements, modeling results, model validation, and a sensitivity analysis of model parameters.;It was concluded that the Mamdani Models were capable of providing more reliable estimates of chip production rate than Sugeno Models, although the Sugeno Method is preferable for non-linear systems such as chip production rate prediction. The Sugeno Model, however, was more sensitive to the sparseness of the experimental test matrix than the Mamdani model was. |
