Fuzzy Logic-Based Expert System for Prediction of Wear Rate in Selective Inhibition Sintered HDPE Parts

Abstract

Selective inhibition sintering (SIS) is a novel additive manufacturing process to build parts with least human effort and cost. The SIS made high density polyethylene (HDPE) parts undergo wear, which is robustly influenced by the SIS process parameters like layer thickness, heat energy, heater feed rate and printer feed rate. Predicting the wear rate being a complex phenomenon, a fuzzy logic based expert system is proposed to evaluate the wear characteristics of SIS made HDPE specimens. Experiments are conducted using pin-on-disc wear testing apparatus to examine the wear rate. Comparative evaluation of experiments and fuzzy approach suggested that the obtained average error of wear rate using fuzzy system is concord with experimental results. Hence, the developed fuzzy rules can be effectively utilized to predict the wear rate of SIS polymer parts in automated manufacturing environments.