Experimental investigation on Linz‐Donawitz slag filled polypropylene composites using teaching‐learning based optimization approach

Linz‐Donawitz (LD) slag is a major solid waste generated in huge quantities during steel making. It comes from slag formers such as burned lime/dolomite and from oxidizing of silica, iron etc. while refining the iron into steel in the LD furnace. This article reports on the erosion wear performance of a new class of hybrid composites prepared by reinforcement of short glass fibers (SGF) in LD slag filled polypropylene (PP) matrix. In this investigation, composites with different LD slag content (0, 7.5, 15, and 22.5 wt%) in a polypropylene matrix base with 20 wt% SGF reinforcement are prepared by injection molding technique. The composites are characterized in regard to their density, porosity, micro‐hardness, and strength properties. Erosion trials (ASTM G 76) are conducted on the composite samples following a well‐planned experimental schedule based on Taguchi design‐of‐experiments. Significant process parameters predominantly influencing the rate of erosion are identified and the LD slag content in the composites is found as most significant among various factors that influence the wear rate. The metaheuristic approach like Teaching‐learning based optimization (TLBO) reveals the minimum erosion wear rate as 11.94 mg/kg at the optimal parametric combination. POLYM. COMPOS., 39:3944–3951, 2018.