An experimental investigation of process parameters on material removal and surface roughness improvement in abrasive flow machining

Abstract

Today, there is huge demand for mechanical components with long life cycles, and superior surface finishes as a result of the industrial revolution. New methods for nano-finishing complex structures, including abrasive flow machining (AFM), have been developed in response to the need for superior surface finish. This is a relatively new technique in non-conventional machining techniques. Because abrasion only happens in locations where flow is restricted, this approach is utilized to polish metallic parts as well as interior, inaccessible cavities, and recesses using a semi-liquid paste. It has evolved to flow of abrasives with a viscoelastic polymer (referred to as abrasive media) over complex geometries, and edges to deburr, and radius those surfaces. This paper focuses on investigating the impact of process parameters on material removal, and percentage improvement in surface roughness on cylindrical brass workpieces using Taguchi L9 orthogonal array, the number of cycles, extrusion pressure, and grit size of abrasives have been selected. The abrasive medium employed in this investigation is composed of a blend of polymer, hydrocarbon gel, and aluminium oxide abrasive particles with varying grit sizes. The outcome shows which process parameters to optimize for material removal, and improvement in percentage improvement in surface roughness. The number of cycles that have the largest percentage contribution to material removal was 83.74%. For the response material removal, the percentage contributions of the abrasive particle grit size, and extrusion pressure are 2.03%, and 14.16%, respectively. N2P2G3 has the optimal level used for material removal. The largest percentage contribution to improvement in surface roughness, or 83.48%, was the result of the number of cycles. Extrusion pressure, and abrasive particle grit size account for 7.38%, and 8.88% of the total percentage contribution, respectively. N3P2G3 has the optimal level obtained for percentage improvement in surface roughness improvement.