Parametric Optimization of Taper Cutting Process using Wire Electrical Discharge Machining (WEDM)

Significant technological advancement of wire electrical discharge machining (WEDM) process has been observed in recent times in order to meet the requirements of various manufacturing fields especially in the production of parts with complex geometry in precision die industry. Taper cutting is an important application of WEDM process aiming at generating complex parts with tapered profiles. Wire deformation and breakage are more pronounced in taper cutting as compared with straight cutting resulting in adverse effect on desired taper angle and surface integrity. The reasons for associated problems may be attributed to certain stiffness of the wire. However, controlling the process parameters can somewhat reduce these problems. Extensive literature review reveals that effect of process parameters on various performance measures in taper cutting using WEDM is also not adequately addressed. Hence, study on effect of process parameters on performance measures using various advanced metals and metal matrix composites (MMC) has become the predominant research area in this field. In this context, the present work attempts to experimentally investigate the machining performance of various alloys, super alloys and metal matrix composite during taper cutting using WEDM process. The effect of process parameters such as part thickness, taper angle, pulse duration, discharge current, wire speed and wire tension on various performance measures such as angular error, surface roughness, cutting rate and white layer thickness are studied using Taguchi’s analysis. The functional relationship between the input parameters and performance measures has been developed by using non-linear regression analysis. Simultaneous optimization of the performance measures has been carried out using latest nature inspired algorithms such as multi-objective particle swarm optimization (MOPSO) and bat algorithm. Although MOPSO develops a set of non-dominated solutions, the best ranked solution is identified from a large number of solutions through application of maximum deviation method rather than resorting to human judgement. Deep cryogenic treatment of both wire and work material has been carried out to enhance the machining efficiency of the low conductive work material like Inconel 718. Finally, artificial intelligent models are proposed to predict the various performance measures prior to machining. The study offers useful insight into controlling the parameters to improve the machining efficiency

Parametric Optimization of Taper Cutting Process using Wire Electrical Discharge Machining (WEDM)

Significant technological advancement of wire electrical discharge machining (WEDM) process has been observed in recent times in order to meet the requirements of various manufacturing fields especially in the production of parts with complex geometry in precision die industry. Taper cutting is an important application of WEDM process aiming at generating complex parts with tapered profiles. Wire deformation and breakage are more pronounced in taper cutting as compared with straight cutting resulting in adverse effect on desired taper angle and surface integrity. The reasons for associated problems may be attributed to certain stiffness of the wire. However, controlling the process parameters can somewhat reduce these problems. Extensive literature review reveals that effect of process parameters on various performance measures in taper cutting using WEDM is also not adequately addressed. Hence, study on effect of process parameters on performance measures using various advanced metals and metal matrix composites (MMC) has become the predominant research area in this field. In this context, the present work attempts to experimentally investigate the machining performance of various alloys, super alloys and metal matrix composite during taper cutting using WEDM process. The effect of process parameters such as part thickness, taper angle, pulse duration, discharge current, wire speed and wire tension on various performance measures such as angular error, surface roughness, cutting rate and white layer thickness are studied using Taguchi’s analysis. The functional relationship between the input parameters and performance measures has been developed by using non-linear regression analysis. Simultaneous optimization of the performance measures has been carried out using latest nature inspired algorithms such as multi-objective particle swarm optimization (MOPSO) and bat algorithm. Although MOPSO develops a set of non-dominated solutions, the best ranked solution is identified from a large number of solutions through application of maximum deviation method rather than resorting to human judgement. Deep cryogenic treatment of both wire and work material has been carried out to enhance the machining efficiency of the low conductive work material like Inconel 718. Finally, artificial intelligent models are proposed to predict the various performance measures prior to machining. The study offers useful insight into controlling the parameters to improve the machining efficiency

Optimization of the geometric parameters of cutting inserts for turning operations

У докторској дисертацији проучавано је стругање легуре инконел 601, без примене средства за хлађење и подмазивање, са ПВД обложеним резним плочицама. Стругање је извршено са различитим брзинама резања, помацима, облицима резних плочица, радијусима врха, грудним угловима и нападним угловима. Након обраде мерена је средња аритметичка храпавост обрађене површине и леђно хабање резне плочице, а рачуната је стопа уклањања материјала. Ефекти улазних на излазне параметара процењени су уз помоћ анализа варијансе. За измерене вредности, процес је моделиран употребом вештачких неуронских мрежа. На основу добијеног модела, оптимизовани су параметри процеса стругања применом генетског алгоритма. Функција циља је била истовремена минимизација средње аритметичке храпавости обрађене површине и леђног хабања резне плочице, као и максимизација стопе уклањања материјала. Тачност модела и оптималне вредности додатно су валидиране кроз конфирмационе експерименте. Добијене процентуалне и апсолутне грешке указују на могућност практичне примене хибридног приступа за моделовање и оптимизацију процеса стругања легуре инконел 601.U doktorskoj disertaciji proučavano je struganje legure inkonel 601, bez primene sredstva za hlađenje i podmazivanje, sa PVD obloženim reznim pločicama. Struganje je izvršeno sa različitim brzinama rezanja, pomacima, oblicima reznih pločica, radijusima vrha, grudnim uglovima i napadnim uglovima. Nakon obrade merena je srednja aritmetička hrapavost obrađene površine i leđno habanje rezne pločice, a računata je stopa uklanjanja materijala. Efekti ulaznih na izlazne parametara procenjeni su uz pomoć analiza varijanse. Za izmerene vrednosti, proces je modeliran upotrebom veštačkih neuronskih mreža. Na osnovu dobijenog modela, optimizovani su parametri procesa struganja primenom genetskog algoritma. Funkcija cilja je bila istovremena minimizacija srednje aritmetičke hrapavosti obrađene površine i leđnog habanja rezne pločice, kao i maksimizacija stope uklanjanja materijala. Tačnost modela i optimalne vrednosti dodatno su validirane kroz konfirmacione eksperimente. Dobijene procentualne i apsolutne greške ukazuju na mogućnost praktične primene hibridnog pristupa za modelovanje i optimizaciju procesa struganja legure inkonel 601.The doctoral dissertation investigated the dry turning of Inconel 601 in a dry environment with PVD-coated inserts. Turning was performed at different cutting speeds, feeds, insert shapes, corner radii, rake and approach angles. After machining, the arithmetic mean surface roughness and flank wear were measured and the material removal rate was calculated. An analysis of variance was performed to determine the effects of the turning input parameters. For the measured values, the turning process was modelled using an artificial neural networks. Based on the model obtained, the process parameters were optimized using a genetic algorithm. The objective function was to simultaneously minimize the arithmetic mean surface roughness and flank wear and maximize the material removal rate. The accuracy of the model and the optimal values were further validated by confirmation experiments. The percentage and absolute errors show the possibility of practical implementation of the hybrid approach for modelling and optimization of dry turning of Inconel 601 alloy

Estudo do micro-corte no acabamento de um biomaterial de difícil usinabilidade

Doutoramento em Engenharia MecânicaA microusinagem está se tornando um processo de usinagem amplamente usado em indústrias ou pesquisas acadêmicas, pois este processo é uma opção para a miniaturização que apresenta bons resultados. Embora o processo de microusinagem apresente grandes vantagens, existem ainda lacunas há serem preenchidas ou o desenvolvimento de novas aplicações, principalmente para área médica. Este estudo investigou o uso do micro-corte com altas velocidades de corte no acabamento da liga de titânio Ti-6Al-7Nb, para fins de aplicações dentárias. A eficiência desse processo foi analisada através da análise da corrosão dos componentes em in vitro testes. Os resultados indicaram que essa técnica pode beneficiar a eficiência dos componentes dentários.The micromachining is becoming a machining process widely used in the industries or academic researchers, because this process is an option to miniaturization that presents good results. In spite of micromachining process presents great advantages, there are still gaps to be filled or discovery of new applications, mainly for the medical applications. This study investigated the use of the micro-cutting with high speed machining in the finishing of the Ti-6Al-7Nb titanium alloy, for purposes of dental applications. The efficiency of this process was analyses through the corrosion analysis of the components in in vitro test. The results of experiments indicated that this technique can benefit for the dental components

Optimization of anodizing parameters for the morphological properties of TiO2 nanotubes based on response surface methodology

TiO2 nanotube (TNT) morphology is crucial for applications in a variety of fields. In this paper, response surface methodology (RSM) has been utilized to optimize the anodizing parameters i.e., electrolyte concentration (C), anodization voltage (V), and time (t) for morphology (e.g., nanotube diameter and length) of TNTs. Ethylene glycol (EG) based electrolyte has been used for anodization employing ammonium fluoride (NH4F) as a source of fluoride ion (F–) with 2.5 vol% H2O. Reliable regression models have been developed between the input variables and the corresponding responses, namely tube diameter and length with multiple regression coefficients of 0.9649 and 0.9253, respectively, revealing a trustworthy association between the actual and those predicted values using the quadratic model. The predicted values of C (0.31 wt%), V (38.44 V), and t (69.37 min) were found to be the optimum anodization condition preceding a TiO2 nanotubes diameter of 99.31 nm and length of 4572.64 nm. It was observed that the nanotubes diameter and length are more affected by anodizing voltage and time, and less sensitive to NH4F concentration. Therefore, RMS could be an appropriate technique to optimize anodizing parameters for producing TiO2 nanotubes with good morphology

Experimental Investigations on Machining of CFRP Composites: Study of Parametric Influence and Machining Performance Optimization

Carbon Fiber Reinforced Polymer (CFRP) composites are characterized by their excellent mechanical properties (high specific strength and stiffness, light weight, high damping capacity etc.) as compared to conventional metals, which results in their increased utilization especially for aircraft and aerospace applications, automotive, defense as well as sporting industries. With increasing applications of CFRP composites, determining economical techniques of production is very important. However, as compared to conventional metals, machining behavior of composites is somewhat different. This is mainly because these materials behave extremely abrasive during machining operations. Machining of CFRP appears difficult due to their material discontinuity, inhomogeneity and anisotropic nature. Moreover, the machining behavior of composites largely depends on the fiber form, the fiber content, fiber orientations of composites and the variability of matrix material. Difficulties are faced during machining of composites due to occurrence of various modes of damages like fiber breakage, matrix cracking, fiber–matrix debonding and delamination. Hence, adequate knowledge and in-depth understanding of the process behavior is indeed necessary to identify the most favorable machining environment in view of various requirements of process performance yields. In this context, present work attempts to investigate aspects of machining performance optimization during machining (turning and drilling) of CFRP composites. In case of turning experiments, the following parameters viz. cutting force, Material Removal Rate (MRR), roughness average (Ra) and maximum tool-tip temperature generated during machining have been considered as process output responses. In case of drilling, the following process performance features viz. load (thrust), torque, roughness average (of the drilled hole) and delamination factor (entry and exit both) have been considered. Attempt has been made to determine the optimal machining parameters setting that can simultaneously satisfy aforesaid response features up to the desired extent. Using Fuzzy Inference System (FIS), multiple response features have been aggregated to obtain an equivalent single performance index called Multi-Performance Characteristic Index (MPCI). A nonlinear regression model has been established in which MPCI has been represented as a function of the machining parameters under consideration. The aforesaid regression model has been considered as the fitness function, and finally optimized by evolutionary algorithms like Harmony Search (HS), Teaching-Learning Based Optimization (TLBO), and Imperialist Competitive Algorithm (ICA) etc. However, the limitation of these algorithms is that they assume a continuous search within parametric domain. These algorithms can give global optima; but the predicted optimal setting may not be possible to adjust in the machine/setup. Since, in most of the machines/setups, provision is given only to adjust factors (process input parameters) at some discrete levels. On the contrary, Taguchi method is based on discrete search philosophy in which predicted optimal setting can easily be achieved in reality.However, Taguchi method fails to solve multi-response optimization problems. Another important aspect that comes into picture while dealing with multi-response optimization problems is the existence of response correlation. Existing Taguchi based integrated optimization approaches (grey-Taguchi, utility-Taguchi, desirability function based Taguchi, TOPSIS, MOORA etc.) may provide erroneous outcome unless response correlation is eliminated. To get rid of that, the present work proposes a PCA-FuzzyTaguchi integrated optimization approach for correlated multi-response optimization in the context of machining CFRP composites. Application potential of aforementioned approach has been compared over various evolutionary algorithms

Investigation of productivity, energy efficiency, quality and cost for laser drilling

Laser drilling is a high speed, non-contact advanced machining process and has proven to be an important industrial process for producing cooling holes in various aeroengine components; in particular high-pressure turbine blades, combustor liners and nozzle guide vanes. However, an increase in the number of cooling holes demands the need for effective utilisation of laser drilling process capability. Material removal rate (MRR), specific energy consumption (SEC), hole taper and the drilling cost are the basic performance indicators to meet this goal. Hence, this research aims to examine the laser drilling process in terms of the mentioned performance measures. Taking into account the significance of material removal quantity, energy efficiency, product quality and manufacturing cost, this study is performed in the form of an experimental investigation for three laser drilling processes, namely, single-pulse drilling, percussion and trepanning. Two different laser drilling setups were prepared to produce holes in Inconel 718 superalloy sheets using flashlamp-pumped Nd:YAG laser and Quasi-CW fibre laser. This research contributes to an evaluation of the influence of laser drilling process parameters on the MRR, SEC, hole quality and drilling cost. Moreover, the performance of laser drilling methods has been compared in relation to the selected performance measures. To further understand the significance of laser sources, the performance of laser drilling was compared for the mentioned drilling setups. This research also introduced a detailed cost analysis to explore the economic implications of the laser drilling process. In addition, optimal drilling conditions were determined aiming to maximise the MRR and minimise hole taper and drilling cost.Manufacturin

Heterogeneous catalytic conversion of carbon dioxide to chloromethyl ethylene carbonate and styrene carbonate using a novel Zr/ZIF-8 catalyst

In the last two decades, several attempts have been made to develop new catalytic systems for the chemical fixation of CO2, both homogeneous and heterogeneous catalysis. However, these attempts have failed to yield satisfactory results as most of these catalysts requires high temperature and/or pressure (usually around 453 K and pressure higher than 8 atm), further separation and purification steps, many of these catalysts deactivate after few recycle experiments and worse of all, low product yield. Hence, this research is focused on the use of metal-organic frameworks (MOFs) catalysts as a relatively new and promising candidate that addresses these aforementioned shortfalls. The development of a novel Zr/ZIF-8 catalyst via a simple low-cost solvothermal method, easy separation by centrifugation, and its excellent recyclability properties have demonstrated that the catalyst could be viable for large-scale industrial applications. The heterogeneity of the catalyst has been proven by recovering and reusing the catalyst for up seven times without any significant loss in catalytic activity. The powder x-ray diffraction (XRD), fourier transform infrared (FTIR) spectroscopy and thermogravimetric analysis (TGA) of the recycled catalyst shows that its framework is quite stable after reusability performance. Furthermore, the catalyst shows high substrates tolerance towards different epoxides including epichlorohydrin (ECH), styrene oxide (SO) and butylene oxide (BO). The reaction has been carried out under solvent-free and cocatalyst conditions. The catalytic properties of the novel catalyst have been satisfactorily consistent with pristine ZIF-8 catalyst using multiple physicochemical characterisation techniques. We believe that this work could provide a new direction for designing more sustainable, non-toxic catalysts for the transformation of CO2 and other substrates. The comparison of catalytic activity of both the pristine ZIF-8 and the novel Zr/ZIF-8 catalysts have been drawn based on the effect of various reaction conditions such as reaction temperature, CO2 pressure, catalyst loading, reaction time, stirring speed and reusability studies. Zr/ZIF-8 catalyst has been assessed as a suitable heterogeneous catalyst outperforming the catalytic activity of pristine ZIF-8 catalyst with respect to the conversion of epoxide, selectivity and yield of the desired carbonates. In addition, experimental design, modelling and optimisation techniques via response surface methodology (RSM) have also been implemented for different process responses. The experimental results have been employed to design and simulate chloromethyl ethylene carbonate (CMEC) and styrene carbonate (SC) using batch experimental studies. The adequacy of the models has been validated by the correlation between the experimental and predicted values of the responses using an Analysis of Variance (ANOVA) method. Therefore, statistical modelling using RSM can be used as a reliable prediction tool for system optimisation for greener synthesis of both chloromethyl ethylene carbonate and styrene carbonate. In conclusions, the catalyst has displayed high epoxide conversion and high carbonate selectivity. The optimum experimental conditions and results for the synthesis of chloromethyl ethylene carbonate were found to be 353 K, 8 bar of CO2 pressure and 8 h using fresh 10% (w/w) Zr/ZIF-8 catalyst loading for a 93% ECH conversion, 86% and 76% of CMEC selectivity and yield, respectively. While the optimum experimental conditions and results for the synthesis of styrene carbonate were found to be 353 K, 6 bar of CO2 pressure and 8 h using fresh 6% (w/w) Zr/ZIF-8 catalyst loading for a 98% SO conversion, 72% and 68% of SC selectivity and yield, respectively. Similarly, the optimised reaction conditions and results using RSM techniques for the synthesis of chloromethyl ethylene carbonate were found at 353 K, 11 Bar of CO2 pressure 12 h using 12% (w/w) fresh catalyst loading for a 96% ECH conversion and 68% CMEC yield while 353 K, 6.1 Bar of CO2 pressure and 8.2 h using fresh 6% (w/w) Zr/ZIF-8 catalyst loading for 98% SO conversion and 68% SC yield for the synthesis of styrene carbonate