Abolfazl Golshan

The application of surface response methodology to the pretreatment of WC substrates prior to diamond coating

High cobalt (Co) content greater than 10% in tungsten carbide is desirable because Co improves the toughness of the cutting tool. However, the additional Co poses a huge challenge in surface preparation given that the Co content must be reduced to less than 1% on the substrate surface prior to applying a diamond coating. The excessive presence of Co on the substrate surface during coating suppresses diamond nucleation and causes the deterioration of diamond film adhesion. Many attempts have been made to overcome this issue, including the use of chemical etching, mechanical blasting, and heat treatment, but the successful pretreatment of WC-12%Co is still very limited. In this paper, a single-step chemical pretreatment using a mixture of sulfuric acid and hydrogen peroxide solutions was carried out on WC-12%Co. Two independent variables, i.e., etching time and acid temperature, were varied in the experiments to reduce Co contents as well as to roughen the substrate surface. The experimental plan was based on a central composite design. Variance analysis was employed to verify the precision of the mathematical models and their relative parameters. The predicted models generated by the response surface methodology (RSM) were compared with the experimental results, and close agreement was observed. The models demonstrated the significance of both factors, namely, acid temperature and etching time, in reducing Co contents to less than 1% as well as a roughening of the substrate surface within the desirable range.

Multi-objective optimisation of electrical discharge machining of metal matrix composite Al/SiC using non-dominated sorting genetic algorithm

In this research, the influence of electrical discharge machining (EDM) on surface roughness and material removal rate (MRR) in metal matrix composite Al/SiC composite was investigated. With use of experimental result analysis and mathematical modelling, the correlation between four EDM conditions and process outputs were studied. Four investigated EDM conditions included pulse on-time, pulse peak current, average gap voltage and percent volume fraction of SiC. For finding optimal conditions, outputs extracted from non-dominated sorting genetic algorithm (NSGA-II) led in achieving appropriate models. The optimisation results showed suggested method has a high performance in problem solving.

Multi-objective optimization of wire electrical discharge machining process using evolutionary computation method: Effect of cutting variation

This article focuses on comparing the performance of brass wire and zinc-coated brass wire that are widely used as the wire electrode in wire electrical discharge machining. To this end, an evolutionary computation method is presented based on non-dominated sorting genetic algorithm in order to find an optimization of rough cutting of the Ti-6Al-4V titanium alloy with the aid of response surface methodology modeling. This research examines the effects of three process parameters, namely, pulse on-time, pulse off-time, and peak current on the process outputs, that is, material removal rate, sparking gap, and white layer thickness. The obtained results indicated that zinc-coated wire was more predictable and it showed more reliable response in the experimental and modeling results. Additionally, the optimization results for both wires demonstrated the high performance of non-dominated sorting genetic algorithm approach to obtain the Pareto optimal set of solutions.

First-Ply Strength of Thick Circular Cylindrical GRP Composite Shell Subjected to Static External Pressure via Finite Element Simulation and Analytical Approaches

One-ply thick externally pressurized GFRP cylinders were analyzed using computational numerical simulation and analytical method. The main part of the work was to study the critical external pressure to avoid failure in the laminated shells by employing various phenomenological failure criteria. Comparison between ABAQUS FEM simulation results and analytical solutions using MATLAB programming codes proved high accuracy of the analytical approach. Various fiber angles stacking sequences were chosen for optimization analysis. The results did not show any increase in stability as the layer number increased. The results also showed high correlation with corresponding failure criteria. The analytical solutions gave higher accuracy as the number of plies and the total laminate thicknesses were reduced.

Prediction of Failure in Thin-Walled Hemispherical GRP Dome Subjected to Static Internal Pressure Based on a Failure Factor

Failure analysis of one-ply thin-walled hemispherical GRP dome internally pressurized was checked via analytical approach and finite element simulations using ABAQUS and MATLAB software. Tsai-Wu failure criterion was employed during analysis. The failure factor against changes of dome’s geometrical parameters was investigated. Subsequently, laminated hemispherical GRP dome failure behavior was theoretically analyzed using MATLAB software. During the analysis some geometrical parameters were assumed to be constant. Moreover, symmetrical laminations were taken into account. The Tsai-Wu failure factor was checked based on changes of applied internal pressure, ply thickness, dome’s internal radius and ratio of dome’s internal radius over ply thickness. The behavior was determined to be linear and quadratic both.

Effect of Volumetric Fiber Fraction on Failure Strength of Thin-Walled GFRP Composite Cylindrical Shell Externally Pressurized

Externally pressurized thin-walled GFRP composite cylindrical shell strength was studied against failure. Fiber breakage, matrix breakage, interlaminate shear deformation, delamination shear deformation and micro buckling failure were investigated employing maximum failure criteria as volumetric fiber fraction factor varied. One-ply cylindrical shell with fiber angle orientation of 0 degree was modeled in ABAQUS finite element simulation and the result was varied using analytical approaches. Moreover, the pressure fluctuations for various volumetric fiber fraction factors were quadratic according to plotted graphs obtained. Meanwhile, MATLAB software was used for theoretical analysis. The comparison of two approaches was proved to be accurate. Subsequently, failure strength of various laminated GFRP cylindrical shell with different fiber angle orientations at each ply was studied for diverse volumetric fiber fraction factors. Stacking sequence, fiber angle orientations were mainly effective on failure strength.

Optimization Of Machining Parameters During Drilling Of 7075 Aluminium Alloy

Proper selection of drilling parameters is one of the significant challenges in drilling process. In this study, a new method for selection of optimal machining parameters during drilling operation is investigated. The present study deals with multiple-performance optimization of machining characteristics during drilling of 7075 aluminum alloy. The most commonly-used material in aerospace industry is aluminum alloy with zinc as the primary alloying element. The drilling parameters used for this experiment include cutting speed, feed rate and drill diameter while the two output parameters are surface roughness and dimension error. These outputs are specified to be optimized as a measure of process performance. The statistical model is generated from linear polynomial equations which are developed from different output responses when the machining parameters are changed. The Non-dominated Sorting Genetic Algorithm optimization results show high performance in solving the present problem.

Computational Inteligence in Optimization of Machining Operation Parameters of ST-37 Steel

Optimal selection of cutting parameters is one of the significant issues in achieving high quality machining. In this study, a method for the selection of optimal cutting parameters during lathe operation is presented. The present study focuses on multiple-performance optimization on machining characteristics of St-37 steel. The cutting parameters used in this experimental study include cutting speed, feed rate, depth of cut and rake angle. Two output parameters, namely, surface roughness and tool life are considered as process performance. A statistical model based on linear polynomial equations is developed to describe different responses. For optimal conditions, the Non-dominated Sorting Genetic Algorithm (NSGA) is employed in achieving appropriate models. The optimization procedure shows that the proposed method has a high performance in problem-solving.

Optimization of Pre-Treatment Parameters before Diamond Coating Using Non-Dominated Sorting Genetic Algorithm (NSGA-II)

In this study a single step of the chemical pre-treatment is implemented to tungsten carbide (WC 6 [%]) at the surface of the substrate in order to solve poor adhesion problem. During the pre-treatment process, numerous parameters such as etching time, acid temperature and concentration affect on the surface roughness and Cobalt content of WC-Co substrate are investigated. Optimal selection of these parameters is one of the significant issues to achieve high-quality work-piece in etching process. Thus, the statistical model based on nonlinear polynomial equations is developed for the different responses. Non-dominated Sorting Genetic Algorithm (NSGA-II) with the use of MATLAB Software codes is used to solve multi-objective optimization problem in order to provide a preferred solution for a process engineer in a short period of time.