2026· International journal of research and innovation in social science· Vol 10, pp. 361-370· 0 citations
Abstract
Cooling-slope (CS) process is a process in preparing the feedstock for the semi-solid process with minimal equipment required. In CS process, optimal selection of CS parameters is important in producing high-quality feedstock. A comprehensive investigation concerning the influence of CS parameters on feedstock quality specifically Tensile strength (TS) and Impact Strength (IS) through an experimental design is conducted. The experiment employs three full factorial designs with added center points for CS parameters, including Pouring temperature (Pt), Pouring distance (Pd), and Slanting angle (Sa). Data from the CS experiment are utilized to develop the mathematical model using regression analysis approach. The models were validated using analysis of variance (ANOVA) and the coefficient of determination (R2). The confirmatory test result shows 3.47% of difference between simulation and experimental. The optimal solution will provide flexibility to the process planner to choose the best parameter settings depending on the application.
In modern manufacturing, optimizing machining parameters is crucial for enhancing productivity, reducing costs, and improving surface quality. Turning, a widely used metal cutting process, often suffers from inefficiencies due to poor parameter selection, leading to increased tool wear and energy use. This study invest...
S. Omotehinse, Esiri Amagre Monday, Precious Osayomwanbor et al.· FUDMA Journal of Sciences· 0 citations
EN24 alloy steel is widely used in high-strength engineering components such as shafts, gears and spindles, where machining performance and surface integrity are critical for reliable service. The present work investigates the influence of spindle speed, feed rate and depth of cut on material removal rate (MRR) and sur...
Y. R. Vadaje, H. A. Chavan· International Journal of App...· 0 citations
There is a set of process variables that defines the quality of a gas metal arc weld (GMAW) joint. The iteration of these process variables to find the optimum setting is time-consuming and does not have a statistical basis. The Taguchi method of robust parameter design is used to determine the optimum combination of w...
Innocent Mapindu, Destine Mashava, Vongai Shangwa et al.· World Journal of Advanced En...· 0 citations
Optimization of the material removal rate (MRR) in wet lathe drilling can improve machining efficiency, while keeping the process parameters under controlled conditions for structural steel applications. Previous studies have explored machinability of ASTM A36 using Taguchi analysis, ANOVA analysis, process-capability...
Gregory Onwuzurike Amanze, John Alabo Michael· Journal of Science Innovatio...· 0 citations
In this study, the effects of ten input factors (wheel speed, workpiece speed, feed, depth of cut, wheel diameter, wheel width, wheel abrasive material, wheel grain size, wheel hardness and wheel structure) on three response variables (dimensional deviation, surface roughness, and material removal rate) were investigat...
A. Milošević, G. Simunovic, Ž. Kanović et al.· Facta Universitatis. Series:...· 1 citation
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