scholarly journals Effect of Machining Limiting Factors on Drilling Progress during Spark Assisted Chemical Engraving (SACE): General Trends

Ceramics ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 618-627
Author(s):  
Jana D. Abou Ziki ◽  
Rolf Wüthrich
Keyword(s):  
Fast Rate ◽  
Local Heating ◽  
Etching Process ◽  
Machining Process ◽  
Limiting Factors ◽  
Machining Parameters ◽  
Micro Machining ◽  
Machining Performance ◽  
Conductive Materials ◽  
Machining Speed

Spark Assisted Chemical Engraving (SACE) is a micro-machining technology for non-conductive materials, mainly glass, based on thermal assisted etching. Generally, during SACE, drilling proceeds at a fast rate reaching 100 µm/s for the first 100 µm and then it slows down for depths higher than 300 µm. While several techniques have been proposed to establish faster drilling, they mainly rely on tuning the machining parameters to enhance the machining performance. However, with this approach machining parameters need to be constantly tuned to achieve certain machining performance depending on the size of the tool and the features needed. Therefore, this necessitates further work to enhance understanding regarding the SACE machining process fundamentals in order to enhance machining speed and quality. Since SACE is a thermal assisted etching process, both local heating and flushing of electrolyte in the machining zone are required. However, to the authors’ knowledge there is not any study that attempts to analyze the effect of each of these machining limiting factors on the machining performance. This work attempts to clarify the effect of each flushing and heating on the drilling progress for hole depths higher than 100 microns. It therefore provides a deeper understanding of the fundamentals of the SACE machining process.

scholarly journals Effects of the Tribological Behaviour of h-BN MQL Nano Cutting Fluid (NCF-MQL) on Turning Inconel 625

2019 ◽  
Vol 11 (4) ◽  
pp. 107-121 ◽  
Author(s):  
Chinmaya PADHY ◽  
Pariniti SINGH
Keyword(s):  
Optimization Technique ◽  
Minimum Quantity Lubrication ◽  
Chip Morphology ◽  
Machining Process ◽  
Cutting Fluid ◽  
Inconel 625 ◽  
Machining Parameters ◽  
Machining Performance ◽  
Tribological Behaviour ◽  
Machined Surface

Minimum quantity lubrication (MQL) is currently a widely used lubricating technique during machining, in which minimum amount of lubricant in the form of mist is delivered to the machining interface, thus helps to reduce the negative effects caused to the environment and human health. Further, to enhance the productivity of machining process specifically for hard-to-cut materials, nano cutting fluid (suitably mixed nano materials with conventional cutting fluid) is used as an alternative method to conventional lubrication (wet) in MQL. In this study, h-BN nano cutting fluid was formulated with 0.1% vol. concentration of h-BN in conventional cutting fluid (Servo- ‘S’) for NCF-MQL technique and its tribological behaviors on machining(turning) performance of Inconel 625 were studied and compared with other lubricating conditions (dry, wet, MQL conventional). The tribological effects were analyzed in terms of tool wear analysis, chip morphology along with statistical analysis for machined surface and evolved cutting forces during machining. The optimal input machining parameters for experiments were defined by the use of Taguchi and Grey relational based multi response optimization technique. Finally, the tribological study shows that the use of h-BN NCF-MQL is a viable and sustainable option for improving machining performance of hard- to- cut material like Inconel 625.

A Study of Abrasive Jet Micro-Grooving of Quartz Crystals

2010 ◽  
Vol 443 ◽  
pp. 645-651 ◽  
Author(s):  
Alireza Moridi ◽  
Jun Wang ◽  
Yasser M. Ali ◽  
Philip Mathew ◽  
Xiao Ping Li
Keyword(s):  
Predictive Models ◽  
Deep Understanding ◽  
Machining Process ◽  
Micro Machining ◽  
Machining Performance ◽  
Quartz Crystals ◽  
Abrasive Jet Machining ◽  
Model Predictions ◽  
Micro Grooving ◽  
Good Agreement

Owing to its various distinct advantages over the other machining technologies, abrasive jet machining has become a promising machining technology for brittle and hard-to-machine materials. An experimental study is presented on the micro-grooving of quartz crystals using an abrasive airjet. The effect of the various process parameters on the major machining performance measures are analysed to provide a deep understanding of this micro-machining process. Predictive models are then developed for quantitatively estimating the machining performance. The models are finally verified by an experiment. It shows that the model predictions are in good agreement with the experimental results under the corresponding conditions.

The Micro-Milling Machining of Pyrex Glass Using the Electrochemical Discharge Machining Process

2011 ◽  
Vol 403-408 ◽  
pp. 738-742 ◽  
Author(s):  
Chang Jian Lu ◽  
An Gu ◽  
Li Meng ◽  
Sheng Yi Yang
Keyword(s):  
Machining Process ◽  
Micro Milling ◽  
Pyrex Glass ◽  
Good Prospect ◽  
Micro Machining ◽  
Affecting Factors ◽  
Conductive Materials ◽  
Electrochemical Discharge Machining ◽  
Electrochemical Discharge

The principles of ECDM and micro-milling were described in the article. The ECDM technology and micro-milling technology were combined, and a milling platform was designed, through the analysis of the affecting factors in the processing, the Pyrex glass was machined by using the electrochemical discharge micro-milling machining and the experiment results were discussed. The results showed that the electrochemical discharge milling machining had a good prospect for the micro machining of the non-conductive materials.

The Effect of Machining Toolpath on Surface Roughness and Dimensional Accuracy for High-Speed Micro Milling

2017 ◽  
Vol 261 ◽  
pp. 69-76
Author(s):  
Amin Dadgari ◽  
De Hong Huo ◽  
David Swailes
Keyword(s):  
Surface Roughness ◽  
Process Planning ◽  
Tool Path ◽  
Dimensional Accuracy ◽  
Machining Process ◽  
Micro Milling ◽  
Geometric Features ◽  
Machining Parameters ◽  
Machining Performance ◽  
Planning Stage

This paper investigates different machining toolpath strategies on machining efficiency and accuracy in the micro milling of linear and circular micro geometric features. Although micro milling includes many characteristics of the conventional machining process, detrimental size effect in downscaling of the process can lead to excessive tool wear and machining instability, which would, in turn, affects the geometrical accuracy and surface roughness. Most of the research in micro milling reported in literature focused on optimising specific machining parameters, such as feed rate and depth of cut, to achieve lower cutting force, better surface roughness, and higher material removal rate. However, there was little attention given to the suitability and effect of machining tool path strategies. In this research, a tool path optimisation method with respect to surface roughness and dimensional accuracy is proposed and tested experimentally. Various toolpath strategies, including lace(0°), lace(45°), lace(90°), concentric and waveform in producing linear and circular micro geometric features were compared and analysed. Experimental results show that the most common used strategies lace(0°) and concentric reported in the literature have provided the least satisfactory machining performance, while waveform toolpath provides the best balance of machining performance for both linear and circular geometries. Hence, at process planning stage it is critical to assign a suitable machining toolpath strategy to geometries accordingly. The paper concludes that an optimal choice of machining strategies in process planning is as important as balancing machining parameters to achieve desired machining performance.

Evaluation of Electrical Discharge Machining Performance on Al (6351)–SiC–B4C Composite

2019 ◽  
pp. 109-124
Author(s):  
Uthayakumar M. ◽  
Suresh Kumar S. ◽  
Thirumalai Kumaran S. ◽  
Parameswaran P.
Keyword(s):  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Research Work ◽  
Machining Process ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Machining Performance ◽  
Machined Surface ◽  
Output Performance ◽  
B4c Particles

Electrical discharge machining (EDM) process is a non-conventional machining process used for the material which are difficult to machine. In this research work, an attempt has been made to determine the influence of Boron Carbide (B4C) particles on the machinablity of the Al (6351) alloy reinforced with 5 wt. % Silicon Carbide (SiC) Metal Matrix Composite (MMC) through EDM. Influence of machining parameters such as pulse current (I), pulse on time (Ton), duty factor (τ), and gap voltage (V) on affecting the output performance characteristics namely Electrode Wear Ratio (EWR), Surface Roughness (SR) and Power Consumption (PC) which are studied. The result shows that the addition of B4C particles significantly affects the machinablity of the composite, with a contribution of 1.6% on EWR, 3.5% on SR and 19.8% on PC. The crater, recast layer formation, and Heat Affected Zone (HAZ) in the machined surface of the composite are also reported in detail.

scholarly journals A study on Electrical Discharge Machining of Titanium Grade2 with experimental and theoretical analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emmanouil L. Papazoglou ◽  
Panagiotis Karmiris-Obratański ◽  
Beata Leszczyńska-Madej ◽  
Angelos P. Markopoulos
Keyword(s):  
Power Distribution ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
White Layer ◽  
Machining Process ◽  
Heat Transfer Analysis ◽  
Machining Parameters ◽  
Machining Performance ◽  
Plasma Flushing Efficiency

AbstractTitanium alloys, due to their unique properties, are utilized in numerous modern high-end applications. Electrical Discharge Machining (EDM) is a non-conventional machining process, commonly used in machining of hard-to-cut materials. The current paper, presents an experimental study regarding the machining of Titanium Grade2 with EDM, coupled with the development of a simulation model. The machining performance indexes of Material Removal Rate, Tool Wear Ratio, and Average White Layer Thickness were measured and calculated for different pulse-on currents and pulse-on times. Moreover, the developed model that integrates a heat transfer analysis with deformed geometry, allows to estimate the power distribution between the electrode and the workpiece, as well as the Plasma Flushing Efficiency, giving an insight view of the process. Finally, by employing the Response Surface Methodology, educed regression models that correlate the machining parameters with the corresponding results, while for all the aforementioned indexes, ANOVA was performed.

FEM of ECDM Process on Semi Conducting Materials

2018 ◽  
Vol 877 ◽  
pp. 87-91 ◽  
Author(s):  
Lijo Paul ◽  
P.V. Pradeep ◽  
Donald Antony
Keyword(s):  
Finite Element ◽  
Finite Element Modelling ◽  
Machining Process ◽  
Micro Machining ◽  
Semiconducting Materials ◽  
Empirical Estimation ◽  
Element Modelling ◽  
Conductive Materials ◽  
Conducting Materials ◽  
Micro Holes

Electro Chemical Discharge Machining (ECDM) process has been developed as an innovative machining process for machining non-conductive materials. The various application of this hybrid process is used in many industries like nuclear, medical and automobile industries. The scope of ECDM in micro machining of semiconducting materials is still found to be promising challenge for researchers. Due to many advanced properties of silicon, its use in MEMS industries is enormous. Many researchers have carried out lot of empirical estimation for discharges in ECDM. However very less work has been reported in the modelling of the ECDM process. Present work mainly concentrates on Finite Element Modelling (FEM) of micro holes machined on silicon wafers with ECDM process. A thermal FEM of spark discharge in the ECDM is carried out. The results from FEM are compared with experimental results and are found to be satisfactory. The model developed can be used for prediction of MRR for a particular combination of workpiece-tool arrangement.

scholarly journals Tribological Effects of H-Bn Nano Cutting Fluid - Minimum Quantity Lubrication (Nf-Mql) on Machining Inconel 625

2019 ◽  
Vol 9 (1) ◽  
pp. 2306-2315 ◽  
Keyword(s):  
Optimization Technique ◽  
Minimum Quantity Lubrication ◽  
Chip Morphology ◽  
Machining Process ◽  
Cutting Fluid ◽  
Inconel 625 ◽  
Machining Parameters ◽  
Machining Performance ◽  
Negative Effects ◽  
Minimum Quantity

Minimum quantity lubrication (MQL) is currently a widely used lubricating technique during machining, in which minimum amount of lubricant in the form of mist is delivered to the machining interface, thus helps to reduce the negative effects caused to the environment and human health. Further, to enhance the productivity of machining process specifically for hard-to-cut materials, nano cutting fluid (suitably mixed nano materials with conventional cutting fluid) is used as an alternative method to conventional lubrication (wet) in MQL. In the current paper, h-BN nano cutting fluid was formulated with 0.1% vol. concentration of h-BN in conventional cutting fluid for NF-MQL technique and its tribological effects on machining performance of Inconel 625 were compared with other lubricating conditions (dry, wet, MQL conventional). The tribological effects were analyzed in terms of tool wear analysis, chip morphology along with statistical analysis for surface roughness and cutting forces. The optimal input machining parameters for experiments were defined by the use of Taguchi and Grey relational based multi response optimization technique. The tribological effects of h-BN NF-MQL shows that it is a viable and sustainable option for improving the machining performance of hard- to- cut material like Inconel 625

Experimental investigation and optimization of machining performance characteristics during WEDM of inconel 718: On evaluation of wire electrodes and advanced parameter techniques

2021 ◽  
pp. 095440622110231
Author(s):  
Anshuman Kumar ◽  
Chandramani Upadhyay
Keyword(s):  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Performance Characteristics ◽  
Machining Process ◽  
Computational Time ◽  
Machining Parameters ◽  
Optimization Strategy ◽  
Machining Performance ◽  
Teaching Learning ◽  
Machining Parameter

Wire Electrical-Discharge-Machining (WEDM) is a well-known unconventional machining process to produce intricate shapes. However, obtaining a satisfactory WEDM cutting performance is indeed a challenging task during precision cutting. Hence, this investigation aims to attempt a favorable machining parameter setting in order to corner-cutting during WEDM for In-718. Here, machining performance characteristics have been considered based on corner deviation (CD) along with Material Removal Rate (MRR) and surface roughness (SR). Taguchi’s experiment design technique (L16) has been considered to run the experiments. The controllable process parameters are considered as Spark-on-time (Son), flushing-pressure (Fp), wire-tension (Tw), and discharge-current (Id). The aforesaid machining performance characteristics have been achieved through the two most popular wire electrodes, i.e., Zinc-coated brass electrode (Zn-BE) and Brass Wire Electrode (BWE), and compared the results. The comparison of performances by the wire electrodes on CD, MRR, and SR varied from 0.0286 mm to 0.0844 mm, 0.0045 g/min to 0.0214 g/min and 3.12 µm to 4.80 µm for BWE and 0.0218 mm to 0.0783 mm, 0.0090 g/min to 0.0342 g/min and 2.58 µm to 4.40 µm for Zn-BE respectively. However, machining with Zn-WE yields reduced CD, SR, and increased MRR value and shows less defect on the WEDMed surfaces than its counterpart. The present study developed the mathematical model based on non-linear regression for correlating the machining parameters with the machining responses. The next step of this study is that a unique optimization strategy, namely grey relation analysis (GRA) integrated with Teaching Learning-Based Optimization (TLBO), has been implemented for achieving optimal parametric setting. The satisfactory machining setting obtained from GRA-TLBO has been compared with GRA-JAYA and GRA-genetic algorithm (GA). The proposed methodology appears more fruitful in terms of computational time and effort.

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