Grey relational analysis based multiresponse optimization for WEDM of ZE41A magnesium alloy

Abstract

It is considered that corrosion of biodegradable implants causes the release of metal ions from the implant surface, leading to tissue inflammation and subsequent failure of the implant. The alloying composition of the material, as well as the surface features of the material, determines the rate of implant degradation. The present study analyzed the influence of the wire electrical discharge machining (WEDM) process parameters on the rate of material removal, the surface characteristics, and the rate of corrosion of the ZE41A Mg alloy. Weighing samples after one week of immersion in simulated body fluid (SBF) determined the corrosion rate. The experiments were conducted using a Taguchi L16 orthogonal array (OA). WEDM is a method of spark erosion that affects the surface characteristics of magnesium alloy samples by developing overlapping craters and surface oxides that affect the mineralization process. The discharge energy has a significant effect on the response characteristics of the WEDM process, namely rate of material removal (MRR), surface roughness (SR), and corrosion rate (CR), and a trade-off between these response properties is always required to achieve the best performance for biodegradable Mg-alloy implants. As a consequence, grey relational analysis (GRA) was employed to optimize MRR, SR, and CR simultaneously. The study discusses the significance of machining process parameters with the degradation behavior of biomedical implant materials in a simulated body fluid (SBF). According to the current study, the most influential parameters in multi-objective optimization are the Ip and Ton. ZE41A Mg alloy machined samples at optimum WEDM parameters enhanced performance in reduced surface roughness and low in-vitro corrosion rate for ZE41A Mg-alloy. By optimization, the mechanical integrity loss of bone design can be mitigated in relation to bone fracture healing time.