Abstract:SS304 is a commercial grade stainless steel which is used for various engineering applications like shafts, guides, jigs, fixtures, etc. Ceramic coating of the wear areas of such parts is a regular practice which significantly enhances the Mean Time Between Failure (MTBF). The final coating quality depends mainly on the coating thickness, surface roughness and hardness which ultimately decides the life. This paper presents an experimental study to effectively optimize the Atmospheric Plasma Spray (APS) process… Show more
“…Nalbalt et al [18] utilize L9 orthogonal array together with 9 total experiments, to study the overall performance characteristics among turning operations concerning AISI 1030 steel bars using TiN covered tools. Some researchers adopted L-18 and L-16 orthogonal array to analyze experimental data [22,23].…”
AISI 1060 carbon steel for turning process is used to find out best cutting parameters using Analysis of Variance (ANOVA) and Regression Concept. Optimization of cutting parameters in turning operation is analyzed in this study. Cutting speed and force affects remarkably on the roughness on the surfaces of the test sample at all cutting operations. The reasonable surface roughness was obtained at a low feed rate in the combination of high cutting speed. Tool vibration was increased with the depth of cut and feed rate. In this study surface roughness was obtained which mostly dependent on the cutting speed, that contribution was 59.74 % and feed rate contribution was found as 13.75 %. The A multilinear regression model was developed to correlate the different cutting parameters.
“…Nalbalt et al [18] utilize L9 orthogonal array together with 9 total experiments, to study the overall performance characteristics among turning operations concerning AISI 1030 steel bars using TiN covered tools. Some researchers adopted L-18 and L-16 orthogonal array to analyze experimental data [22,23].…”
AISI 1060 carbon steel for turning process is used to find out best cutting parameters using Analysis of Variance (ANOVA) and Regression Concept. Optimization of cutting parameters in turning operation is analyzed in this study. Cutting speed and force affects remarkably on the roughness on the surfaces of the test sample at all cutting operations. The reasonable surface roughness was obtained at a low feed rate in the combination of high cutting speed. Tool vibration was increased with the depth of cut and feed rate. In this study surface roughness was obtained which mostly dependent on the cutting speed, that contribution was 59.74 % and feed rate contribution was found as 13.75 %. The A multilinear regression model was developed to correlate the different cutting parameters.
The optimization in manufacturing processes refers to the investigation of multiple responses simultaneously. Therefore, it becomes very necessary to introduce a technique that can solve the multiple response optimization problem efficiently. In this study, an attempt has been taken to find the application of three newly introduced multi-objective evolutionary algorithms, namely multi-objective dragonfly algorithm (MODA), multi-objective particle swarm optimization algorithm (MOPSO), and multi-objective teaching-learning-based optimization (MOTLBO), in the modern manufacturing processes. For this purpose, these algorithms are used to solve five instances of modern manufacturing process—CNC process, continuous drive friction welding process, EDM process, injection molding process, and friction stir welding process—during this study. The performance of these algorithms is measured using three parameters, namely coverage to two sets, spacing, and CPU time. The obtained experimental results initially reveal that MODA, MOPSO, and MOTLBO provide better solutions as compared to widely used nondominated sorting genetic algorithm II (NSGA-II). Moreover, this study also shows the superiority of MODA over MOPSO and MOTLBO while considering coverage to two sets and CPU time. Further, in terms of spacing a marginally inferior performance is observed in MODA as compared to MOPSO and MOTLBO.
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