A Grey-Based Taguchi Approach for Characterization of Erosive Wear Phenomenon of Glass–Polyester Fly Ash Filled Composites

Abstract

Fly ash is a solid waste generated in huge quantities from coal fired thermal power stations during the combustion of coal. In India, less than half of this is used as a raw material for concrete manufacturing and construction; the remaining is directly dumped on land side as land fill or simply piled up. Only a small fraction of it is used in development of high valued product. Due to environmental regulations, new ways of utilizing fly ash are being explored in order to safeguard the environment and provide useful ways for its utilization and disposal. With its richness in various metal oxides, it has tremendous potential to be utilized as a filler material in polymer composites. These days glass reinforced polyester composites find widespread application in erosive environment due to several advantages like high wear resistance, strength-to-weight ratio, and low cost. The cost of the composites can be further brought down using cheaper filler materials. To this end, this work uses fly ash in composite making and thereby suggests a new way of better utility of this industrial waste. It includes the processing, characterization and study of the erosion behavior of a class of such fly ash filled polyester-glass fiber composites. The engineering application of composites demands that it should have high wear resistance, low density and high tensile strength. In order to assess the behavior of composites satisfying multiple performance measures, a grey-based Taguchi approach has been adopted. After thorough analysis of factors, optimal factor settings have been suggested to improve multiple responses viz., erosive wear rate, density, flexural strength and tensile strength. This technique eliminates the need for repeated experiments; thus saves time and material. The systematic experimentation leads to determination of significant process parameters and material variables that predominantly influence the multiple responses.