Prediction and wear performance of red brick dust filled glass–epoxy composites using neural networks

Abstract

Red brick dust (RBD) is the waste or leftover powder, or the powder formed from deformed bricks in the process of their manufacturing. Bricks can be deformed while handling and the deformed bricks cannot be used for construction purposes; hence, they are dumped as waste. This article describes on erosion wear response of a new class of hybrid composites consisting of epoxy reinforced with glass fiber and filled with RBD particulates. Different compositions of composites are prepared by simple hand lay-up technique. Erosion characteristics are studied with the help of an air jet type erosion test rig employing the design-of-experiments approach based on Taguchi’s orthogonal arrays. An artificial neural network approach is also applied to predict the wear rate of the composites. The morphology of worn surfaces is then examined by scanning electron microscopy, and possible wear mechanisms are discussed. This study reveals that addition of red brick dust improves the erosion resistance of glass–epoxy composites significantly and thus, makes them suitable for tribological applications.