Grinding process parameter optimization to enhance surface finish using NSGA-II algorithm: an integrated experimental and evolutionary approach

The present investigation was dedicated to elucidate grinding characteristics during surface grinding of titanium alloy(TC6) and high temperature alloy (GH2132) by using silicon carbide(SiC) and sol-gel (SG) wheel respectively. The grinding characteristic of SG wheel on aeronautical alloys was studied on the base of systematical measurement of the grinding force, grinding temperature, surface roughness and grinding ratio. The results indicated that the SG grinding wheel possesses excellent grinding properties and is more suitable for grinding these aeronautical alloys compared with conventional abrasive tools. Finally, the grinding mechanism of new-typed SG wheel was unveiled on the base of the microcrystalline structure analysis of SG grains.

Heat flux transients were estimated during unidirectional downward solidification of Al–22% Si alloy against copper, die steel and stainless steel chills. The chill instrumented with thermocouples was brought into contact with the liquid metal so as to avoid the effect of convection associated with the pouring of liquid metal. Heat flux transients were estimated by solving the inverse heat conduction problem. Higher thermal conductivity of chill material resulted in increased peak heat flux at the metal/chill interface. Peak heat flux decreased when 100 μm thick alumina coating was applied on the chill surface. The lower thermal conductivity of alumina based coating and the presence of additional thermal resistance decreases the interfacial heat transfer. For uncoated chills, the ratio of the surface roughness (Ra) of the casting to chill decreased from 6.5 to 0.5 with decrease in the thermal conductivity of the chill material. However when coating was applied on the chill, the surface roughness ratio was nearly constant at about 0.2 for all chill materials. The measured roughness data was used in a sum surface roughness model to estimate the heat transfer coefficient. The results of the model are in reasonable agreement with experimentally determined heat-transfer coefficients for coated chills.

Orthogonal turning of AISI 310S austenitic stainless steel under hybrid nanofluid-assisted MQL and a sustainability optimization using NSGA-II and TOPSIS

The studies described in this paper focus on the wear behavior of duplex grade abrasive segments grinding AISI 1020 and A36 steels on a vertical spindle surface grinding machine (VSSG). The study focuses on the behavior of the abrasive segment and how it contributes to significant changes in the grinding ratio and the type of wear that is occurring under grinding conditions where short chips are generated (roughness ratio, λ > 1) and accumulate in the graded structure of the abrasive segment. The paper discusses the kinematics of the VSSG process, the mechanisms of wear in abrasive and bonded grains, the VSSG experiments performed, and the results generated in terms of segment wear and the resulting roughness of the ground surfaces. The analysis of the results concludes by stating that duplex graded segments are useful in controlling the phenomena of “chip crowding,” although this may lead to “parasitic wear” to take place that may negatively affect segment performance in VSSG operations. In this respect, the paper addresses the type of abrasive grain to be used during VSSG operations. The studies described in this paper may be useful to manufacturing engineers who use VSSG operations and are responsible for their development.

This research examined at the optimum cutting parameters for producing minimum surface roughness and maximum Material Removal Rate (MRR) when turning magnesium alloy AZ91D. Cutting speed (m/min), feed (mm/rev), and cut depth (mm) have all been considered in the experimental study. To find the best cutting parameters, Taguchi's technique and Response Surface Methodology (RSM), an evolutionary optimization techniques Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were employed. GA gives better results of 34.04% lesser surface roughness and 15.2% higher MRR values when compared with Taguchi method. The most optimal values of surface roughness and MRR is received in multi objective optimization NSGA-II were 0.7341 µm and 9460 mm3 /min for the cutting parameters cutting speed at 140.73m/min, feed rate at 0.06mm/min and 0.99mm depth of cut. Multi objective NSGA-II optimization provides several non-dominated points on Pareto Front model that can be utilized as decision making for choice among objectives

Multiobjective optimization approaches have allowed the improvement of technical features in industrial processes, focusing on more accurate approaches for solving complex engineering problems and support decision-making. This paper proposes a hybrid approach to optimize the 3D printing technology parameters, integrating the design of experiments and multiobjective optimization methods, as an alternative to classical parametrization design used in machining processes. Alongside the approach, a multiobjective differential evolution with uniform spherical pruning (usp-MODE) algorithm is proposed to serve as an optimization tool. The parametrization design problem considered in this research has the following three objectives: to minimize both surface roughness and dimensional accuracy while maximizing the mechanical resistance of the prototype. A benchmark with non-dominated sorting genetic algorithm II (NSGA-II) and with the classical sp-MODE is used to evaluate the performance of the proposed algorithm. With the increasing complexity of engineering problems and advances in 3D printing technology, this study demonstrates the applicability of the proposed hybrid approach, finding optimal combinations for the machining process among conflicting objectives regardless of the number of decision variables and goals involved. To measure the performance and to compare the results of metaheuristics used in this study, three Pareto comparison metrics have been utilized to evaluate both the convergence and diversity of the obtained Pareto approximations for each algorithm: hyper-volume (H), g-Indicator (G), and inverted generational distance. To all of them, ups-MODE outperformed, with significant figures, the results reached by NSGA-II and sp-MODE algorithms.

In micro injection molding, the cavity thickness and surface roughness are the main effects factors of polymer flow in the die designing and affect the quality of molded products significantly. In this study, the effects of cavity thickness and roughness of cavity surface were investigated mainly on polymer flow during molding and on the roughness of molded products. The parts were molded in the cavities with the thickness from 0.05 mm to 0.25 mm and surface roughness from Ra = 46.55 nm to Ra = 462.57 nm, respectively. The filling integrities and roughness replication ratio of molded parts were used to evaluate the statements of polymer flow and microstructure replication during micro injection molding, respectively. The results showed that the filling integrity changing trends in the thinner cavities were obviously different or even opposite to those in the thicker cavities with the changing of cavity surface roughness instead of single trend in the conventional studies. For each cavity surface roughness, the filling integrity showed an upward trend with the increasing cavity thickness. In different cavity thickness, the maximum gap of filling integrity was 23.76 mm, reaching 544.94% from 0.05 mm to 0.25 mm. Additionally, the surface roughness ratio was slightly smaller than one before, reaching the polymer surface roughness limit around Ra = 71.27 nm, which was decided by the nature of the polymer itself. This study proposed the references for the design and fabrication of mold cavities and parts, and saved time and cost in the actual product manufacturing.

Subsurface damage of Nd-doped phosphate glasses in optical fabrication

An experimental–computational fracture-mechanics approach for the analysis and design of structural adhesive joints under static loading is demonstrated by predicting the ultimate fracture load of cracked lap shear and single lap shear aluminum and steel joints bonded using a highly toughened epoxy adhesive. The predictions are then compared with measured values. The effects of spew fillet, adhesive thickness, and surface roughness on the quasi-static strength of the joints are also discussed. This fracture-mechanics approach is extended to characterize the fatigue threshold and crack growth behavior of a toughened epoxy adhesive system for design purposes. The effects of the mode ratio of loading, adhesive thickness, substrate modulus, spew fillet, and surface roughness on the fatigue threshold and crack growth rates are considered. A finite element model is developed to both explain the experimental results and to predict how a change in an adhesive system affects the fatigue performance of the bonded joint.

It will be effective to combine electrochemical and electrodischarge removal actions with mechanical grinding in order to increase the productivity of materials which are difficult to machine. This method was tested on the groove grinding of cemented carbide. The influences of applied electric voltage on grinding force, wheel wear and grinding ratio were tested experimentally. As a result, it is known that the grinding ratio increases and reaches a maximum when a charge of 20 volts was applied. At that voltage both electrochemical and electrodischarge actions are recognized. At voltages lower than this, wheel wear increases and grinding ratio decreases due to the increase of mechanical action. At voltages higher than 20, wheel were also increases. This is caused by wheel damage due to severe electrodischarge. In order to get high grinding ratio and better surface roughness, it is effective to add reverse voltage. The frequent application of voltage makes electro-chemical and electrodischarge actions more significant.

Surface roughness of polyamide 12 parts manufactured using selective laser sintering

The present article is the first study on and identifies the different process parameters that affect the cutting speed and surface roughness in wire electric discharge machining of titanium 6-2-4-2. Box–Behnken designs are used to plan and analyse the experiments. Mathematical models are developed for cutting speed and surface roughness using regression technique and are utilized for simultaneous optimization of cutting speed and surface roughness. As the influence of process parameters on cutting speed and surface roughness is opposite, the problem is formulated as a multi-objective optimization problem. Non-dominated sorting genetic algorithm-II is then applied to obtain Pareto optimal set of solutions. Confirmatory experiments indicate that the model is suitable for predicting the response parameters. These Pareto optimal sets of solutions can be used as guidelines by manufacturing engineers to select optimal combination of parameters depending upon the job requirements.

Cutting fluid designed for all modern machine tools: Rocol Ltd, Rocol House, Swillington, Leeds LS26 8BS, UK

Influence of the cutting edge radius on surface integrity in hard turning of roller bearing inner rings

Experimental analysis and low-damage machining strategy for composite ultrasonic vibration-assisted grinding of silicon carbide based on DA-MLP-NSGA-II algorithm