A Study of Influence of Electrolyte Composition on ECH of Bevel Gears using Mixture D-Optimal Design
This paper discusses the experimental investigation to find out the optimal electrolyte composition in improving the surface quality of the gear teeth profile during surfacing finishing of bevel gears by the electrochemical honing process. In this study, AISI 1040 was used as the workpiece material, mixtures of sodium chloride and sodium nitrate in different ratios were used as the input parameter, and the percentage improvement in the surface roughness and material removal rate of the process were used as measures of process performance. The experimental runs were designed according to the Mixture DOptimal design. The analysis of the experimental outcome was carried out and 80% NaCl + 20% NaNO3 was found to be theoptimal electrolyte composition to conduct the confirmation experiments. The finding of the study establishes the process for precision finishing of bevel gears.
Influence of ultrasonic vibrations on process performance of electrochemical honing
Electrochemical honing (ECH) is a novel variant of hybrid machining processes (HMPs). The key feature is that the distinct coupling of electrochemical machining (ECM) and honing provide a controlled functional surface generation and faster material removal rate in a single operation. In the present study, the influence of ultrasonic vibrations on process performance of ECH of bevel gears made of EN8 is investigated. An analysis of the process has been presented with suitable illustrations. Ultrasonic frequency and processing time were considered as the input variables while improvement in surface finish, material removal and geometrical accuracies were considered as the monitored output. The effectiveness of the process was investigated through experimental trials by conducting a comparison study between classical ECH and ultrasonic vibration-assisted ECH (UECH). The results confirm that improvements in surface roughness and martial removal rate are significantly higher than those obtained with classical ECH. The study further reveals that the scrubbing of the oxide layer is easier to be achieved and surface quality is obviously improved due to ultrasonic vibrations. The experimental results demonstrate that UECH gives 18.36 % improvement in average roughness, 9.31 % improvement in maximum roughness and 20 % improvement in material removal rate as compared with ECH.
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.