The manufacturing sectors are consistently striving to figure out ways to minimize the consumption of natural resources through rational utilization. This is achieved by a proper understanding of every minute influence of parameters on the entire process. Understanding the influencing parameters in determining the machining process efficacy is inevitable. Technological advancement has drastically improved the machining process through various means by providing better quality products with minimum machining cost and energy consumption. Specifically, the machining factors such as cutting speed, spindle speed, depth of cut, rate of feed, and coolant flow rate are found to be the governing factors in determining the economy of the machining process. This study is focused on improving the machining economy by enhancing the surface integrity and tool life with minimum resources. The study is carried out on low-carbon mold steel (UNS T51620) using Box–Behnken design and grey regression analysis. The optimized multiobjective solution for surface roughness (Ra), material removal rate (MRR), and power consumed (Pc) and tool life is determined and validated through the confirmatory run. The optimized set of parameters in Box–Behnken design and grey regression analysis with that of confirmatory runs shows a 10% deviation that proves the reliability of the optimization techniques employed.
The diffusion bonding (DB) method is used in this investigation to connect high-temperature dissimilar materials. The existence of difficult-to-remove oxide coatings on the titanium surfaces, as well as the arrangement of breakable metallic interlayers and oxide enclosures inside the bond region, provides the most significant challenges during the transition from AISI304 to Ti-6Al-4V alloying. In addition, an effort was made to advance DB processing maps for the operational connection of Ti-6Al-4V to AISI304 alloys to improve their performance. Joints had been created by combining several process factors, such as bonding temperature (T), bonding pressure (P), and holding time (t), to create diverse designs. Based on the findings, database processing maps were created. This set of processing maps may be used as a rough guideline for selecting appropriate DB process parameters for generating virtuous excellent bonds between Ti-6Al-4V and AISI304 alloys. The maximum lap shear strength (LSS) was achieved at 800°C, 15 MPa, and 45 min.
The aim of this research work was to develop the optimal mechanical properties, namely, tensile strength, flexural strength, and impact strength of sisal and glass fiber-reinforced polymer hybrid composites. The sisal, in the form of short fiber, is randomly used as reinforcements for composite materials, which is rich in cellulose, economical, and easily available as well as glass fibers have low cost and have good mechanical properties. In addition, epoxy resin and hardener were for the fabrication of composites by compression molding. The selected materials are fabricated by compression molding in various concentrations on volume basics. The combination of material compositions is obtained from the design of experiments and optimum parameters determined by the Response Surface Methodology (RSM). From the investigation of mechanical properties, the sisal is the most significant factor and verified by ANOVA techniques. The multiobjective optimal levels of factors are obtained by LINGO analysis.
Al2O3 with 10 wt.% of SiC ceramic composite is synthesized at 1500°C by electrical resistance heating sintering with a holding time of 5 hours and microwave sintering methods with a holding time of 15 minutes. The samples generated by the two methods are characterized using powder X-ray diffraction and field emission scanning electron microscopy (FESEM). Experiments with both samples showed that the existence of the α-Al2O3 and β-SiC phases in both samples was verified by the findings of XRD pattern on both samples. Microstructure study illustrates that the Al2O3 matrix particles have spherical-like shape and their average matrix particle size is 67 ± 5 nm for electrical resistance heating sintered sample and 38 ± 5 nm for microwave sintered sample. The lattice strain and crystallite size of Al2O3 matrix were measured using Williamson–Hall (W-H) methods, which were achieved via the use of XRD peak broadening, based on a diffraction pattern. Three modified W-H models were used to compute other parameters, including strain (ε) and stress (σ), as well as energy density (u). These models were the uniform deformation model (UDM), the uniform deformation energy density model (UDEDM), and the uniform deformation stress model (UDSM). The average crystallite sizes of α-Al2O3 attained from these three models of Williamson–Hall (W–H) methods and FESEM analysis are correlated and found very close to each other. In all three models of the W-H technique, X-ray diffraction peak profile examination of electrical resistance heating-sintered and microwave-sintered Al2O3/10 wt. % SiC ceramic composite reveals that the microwave-sintered sample has finer crystallite size with less strain.
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