Abstract: In electrical discharge machining (EDM), a complete and clear theory has not yet been established. The developed theory (physical models) yields results far from reality due to the complexity of the physics. It is difficult to select proper parameter settings in order to achieve better EDM performance. However, modelling can solve this critical problem concerning the parameter settings. Therefore, the purpose of the present work is to develop mathematical model to predict performance characteristics of EDM on Ti-5Al-2.5Sn titanium alloy. Response surface method (RSM) and artificial neural network (ANN) are employed to develop the mathematical models. The developed models are verified through analysis of variance (ANOVA). The ANN models are trained, tested, and validated utilizing a set of data. It is found that the developed ANN and mathematical model can predict performance of EDM effectively. Thus, the model has found a precise tool that turns EDM process cost-effective and more efficient.
Abstract: This paper presents an experimental investigation on the optimization and the effect of the cutting parameters on Material Removal Rate (MRR) in Plasma Arc Cutting (PAC) of EN-45A Material using Taguchi L 16 orthogonal array method. Four process variables viz. cutting speed, current, stand-off-distance and plasma gas pressure have been considered for this experimental work. Analysis of variance (ANOVA) has been performed to get the percentage contribution of each process parameter for the response variable i.e. MRR. Based on ANOVA, it has been observed that the cutting speed, current and the plasma gas pressure are the major influencing factors that affect the response variable. Confirmation test based on optimal setting shows the better agreement with the predicted values.
Abstract: In the present work response surface methodology (RSM) based central composite design (CCD) is used for analyzing the electrical discharge machining (EDM) process. For experimentation, mild steel is selected as work piece and copper is used as electrode. Three machining parameters namely current (I), spark on time (Ton) and spark off time (Toff) are selected as the input variables. The output or response chosen is material removal rate (MRR) which is to be maximized. To reduce the number of runs face centered central composite design (FCCCD) was used. ANOVA was used to determine the significance of parameter and interactions. The suitability of model is tested using Anderson darling (AD) plot. The results conclude that different parameters considered i.e. current, pulse on and pulse off time; all have dominant effect on the MRR. At last, the optimized parameter setting for maximizing MRR is found through main effect plot analysis.
Abstract: Productivity and quality are two important aspects that have become great concerns in today’s competitive global market. Every production/manufacturing unit mainly focuses on these areas in relation to the process, as well as the product developed. The electrical discharge machining (EDM) process, even now it is an experience process, wherein the selected parameters are still often far from the maximum, and at the same time selecting optimization parameters is costly and time consuming. Material Removal Rate (MRR) during the process has been considered as a productivity estimate with the aim to maximize it, with an intention of minimizing surface roughness taken as most important output parameter. These two opposites in nature requirements have been simultaneously satisfied by selecting an optimal process environment (optimal parameter setting). Objective function is obtained by Regression Analysis and Analysis of Variance. Then objective function is optimized using Genetic Algorithm technique. The model is shown to be effective; MRR and Surface Roughness improved using optimized machining parameters.
Abstract: Manufacturing technologies are becoming continuously
more diversified over the years. The increasing use of robots for
various applications such as assembling, painting, welding has also
affected the field of machining. Machining robots can deal with
larger workspaces than conventional machine-tools at a lower cost
and thus represent a very promising alternative for machining
applications. Furthermore, their inherent structure ensures them a
great flexibility of motion to reach any location on the workpiece with
the desired orientation. Nevertheless, machining robots suffer from
a lack of stiffness at their joints restricting their use to applications
involving low cutting forces especially finishing operations. Vibratory
instabilities may also happen while machining and deteriorate the
precision leading to scrap parts. Some researchers are therefore
concerned with the identification of optimal parameters in robotic
machining. This paper continues the development of a virtual robotic
machining simulator in order to find optimized cutting parameters in
terms of depth of cut or feed per tooth for example. The simulation
environment combines an in-house milling routine (DyStaMill)
achieving the computation of cutting forces and material removal
with an in-house multibody library (EasyDyn) which is used to
build a dynamic model of a 3-DOF planar robot with flexible links.
The position of the robot end-effector submitted to milling forces is
controlled through an inverse kinematics scheme while controlling
the position of its joints separately. Each joint is actuated through
a servomotor for which the transfer function has been computed
in order to tune the corresponding controller. The output results
feature the evolution of the cutting forces when the robot structure
is deformable or not and the tracking errors of the end-effector.
Illustrations of the resulting machined surfaces are also presented.
The consideration of the links flexibility has highlighted an increase
of the cutting forces magnitude. This proof of concept will aim
to enrich the database of results in robotic machining for potential
improvements in production.
Abstract: Electric discharge machining (EDM) is one of the most widely used non-conventional manufacturing process to shape difficult-to-cut materials. The process yield, in terms of material removal rate, surface roughness and tool wear rate, of EDM may considerably be improved by selecting the optimal combination(s) of process parameters. This paper employs Multi-response signal-to-noise (MRSN) ratio technique to find the optimal combination(s) of the process parameters during EDM of Inconel 718. Three cases v.i.z. high cutting efficiency, high surface finish, and normal machining have been taken and the optimal combinations of input parameters have been obtained for each case. Analysis of variance (ANOVA) has been employed to find the dominant parameter(s) in all three cases. The experimental verification of the obtained results has also been made. MRSN ratio technique found to be a simple and effective multi-objective optimization technique.
Abstract: Chatter vibrations and process instabilities are the
most important factors limiting the productivity of the milling
process. Chatter can leads to damage of the tool, the part or the
machine tool. Therefore, the estimation and prediction of the process
stability is very important. The process stability depends on the
spindle speed, the depth of cut and the width of cut. In milling, the
process conditions are defined in the NC-program. While the spindle
speed is directly coded in the NC-program, the depth and width of cut
are unknown. This paper presents a new simulation based approach
for the prediction of the depth and width of cut of a milling process.
The prediction is based on a material removal simulation with an
analytically represented tool shape and a multi-dexel approach for the
workpiece. The new calculation method allows the direct estimation
of the depth and width of cut, which are the influencing parameters of
the process stability, instead of the removed volume as existing
approaches do. The knowledge can be used to predict the stability of
new, unknown parts. Moreover with an additional vibration sensor,
the stability lobe diagram of a milling process can be estimated and
improved based on the estimated depth and width of cut.
Abstract: Wire Electric Discharge Machining (WEDM) is
thermal machining process capable of machining very hard
electrically conductive material irrespective of their hardness.
WEDM is being widely used to machine micro scale parts with the
high dimensional accuracy and surface finish. The objective of this
paper is to optimize the process parameters of wire EDM to fabricate
the micro channels and to calculate the surface finish and material
removal rate of micro channels fabricated using wire EDM. The
material used is aluminum 6061 alloy. The experiments were
performed using CNC wire cut electric discharge machine. The effect
of various parameters of WEDM like pulse on time (TON) with the
levels (100, 150, 200), pulse off time (TOFF) with the levels (25, 35,
45) and current (IP) with the levels (105, 110, 115) were investigated
to study the effect on output parameter i.e. Surface Roughness and
Material Removal Rate (MRR). Each experiment was conducted
under different conditions of pulse on time, pulse off time and peak
current. For material removal rate, TON and Ip
were the most significant process parameter. MRR increases with the increase in
TON and Ip and decreases with the increase in TOFF. For surface
roughness, TON and Ip have the maximum effect and TOFF was found
out to be less effective.
Abstract: In this study, a multi objective optimization for end
milling of Al 6061 alloy has been presented to provide better
surface quality and higher Material Removal Rate (MRR). The input
parameters considered for the analysis are spindle speed, depth of cut
and feed. The experiments were planned as per Taguchis design of
experiment, with L27 orthogonal array. The Grey Relational Analysis
(GRA) has been used for transforming multiple quality responses
into a single response and the weights of the each performance
characteristics are determined by employing the Principal Component
Analysis (PCA), so that their relative importance can be properly and
objectively described. The results reveal that Taguchi based G-PCA
can effectively acquire the optimal combination of cutting parameters.
Abstract: Non-water based fixed abrasive polishing was adopted
to manufacture LBO crystal for nano precision surface quality because
of its deliquescent. Ethyl alcohol was selected as the non-water based
slurry solvent and ethanediamine, lactic acid, hydrogen peroxide was
added in the slurry as a chemical additive, respectively. Effect of
different additives with non-water based slurry on material removal
rate, surface topography, microscopic appearances, and surface
roughness were investigated in fixed abrasive polishing of LBO
crystal. The results show the best surface quality of LBO crystal with
surface roughness Sa 8.2 nm and small damages was obtained by
non-water based slurry with lactic acid. Non-water based fixed
abrasive polishing can achieve nano precision surface quality of LBO
crystal with high material removal.
Abstract: Machining of hard materials is a recent technology for
direct production of work-pieces. The primary challenge in
machining these materials is selection of cutting tool inserts which
facilitates an extended tool life and high-precision machining of the
component. These materials are widely for making precision parts for
the aerospace industry. Nickel-based alloys are typically used in
extreme environment applications where a combination of strength,
corrosion resistance and oxidation resistance material characteristics
are required. The present paper reports the theoretical and
experimental investigations carried out to understand the influence of
machining parameters on the response parameters. Considering the
basic machining parameters (speed, feed and depth of cut) a study has
been conducted to observe their influence on material removal rate,
surface roughness, cutting forces and corresponding tool wear.
Experiments are designed and conducted with the help of Central
Composite Rotatable Design technique. The results reveals that for a
given range of process parameters, material removal rate is favorable
for higher depths of cut and low feed rate for cutting forces. Low feed
rates and high values of rotational speeds are suitable for better finish
and higher tool life.
Abstract: Several researches have been conducted to study
consumption of energy in cutting process. Most of these researches
are focusing to measure the consumption and propose consumption
reduction methods. In this work, the relation between the cutting
parameters and the consumption is investigated in order to establish a
generalized energy consumption model that can be used for process
and production planning in real production lines. Using the
generalized model, the process planning will be carried out by taking
into account the energy as a function of the selected process
parameters. Similarly, the generalized model can be used in
production planning to select the right operational parameters like
batch sizes, routing, buffer size, etc. in a production line. The
description and derivation of the model as well as a case study are
given in this paper to illustrate the applicability and validity of the
model.
Abstract: In addition to the increase of the material removal rate or surface rate, or the improvement of the surface quality, which are the main aims of the development of manufacturing technology, a growing number of other manufacturing requirements have appeared in the machining of workpiece surfaces. Among these it is becoming increasingly dominant to generate a surface topography in finishing operations which meets more closely the needs of operational requirements.
These include the examination of the surface periodicity and/or ensuring that the twist-structure values are within the limits (or even preventing its occurrence) in specified cases such as on the sealing surfaces of rotating shafts or on the inside working surfaces of needle roller bearings. In the view of the measurement the twist has different parameters from surface roughness, which must be determined for the machining procedures. Therefore in this paper the alteration of the theoretical values of the parameters determining twist structure are studied as a function of the kinematic properties.
Abstract: This paper is intended to develop an artificial neural network (ANN) based model of material removal rate (MRR) in the turning of ferrous and nonferrous material in a Indian small-scale industry. MRR of the formulated model was proved with the testing data and artificial neural network (ANN) model was developed for the analysis and prediction of the relationship between inputs and output parameters during the turning of ferrous and nonferrous materials. The input parameters of this model are operator, work-piece, cutting process, cutting tool, machine and the environment.
The ANN model consists of a three layered feedforward back propagation neural network. The network is trained with pairs of independent/dependent datasets generated when machining ferrous and nonferrous material. A very good performance of the neural network, in terms of contract with experimental data, was achieved. The model may be used for the testing and forecast of the complex relationship between dependent and the independent parameters in turning operations.
Abstract: Artificial neural networks (ANN) are used in distinct researching fields and professions, and are prepared by cooperation of scientists in different fields such as computer engineering, electronic, structure, biology and so many different branches of science. Many models are built correlating the parameters and the outputs in electrical discharge machining (EDM) concern for different types of materials. Up till now model for Ti-5Al-2.5Sn alloy in the case of electrical discharge machining performance characteristics has not been developed. Therefore, in the present work, it is attempted to generate a model of material removal rate (MRR) for Ti-5Al-2.5Sn material by means of Artificial Neural Network. The experimentation is performed according to the design of experiment (DOE) of response surface methodology (RSM). To generate the DOE four parameters such as peak current, pulse on time, pulse off time and servo voltage and one output as MRR are considered. Ti-5Al-2.5Sn alloy is machined with positive polarity of copper electrode. Finally the developed model is tested with confirmation test. The confirmation test yields an error as within the agreeable limit. To investigate the effect of the parameters on performance sensitivity analysis is also carried out which reveals that the peak current having more effect on EDM performance.
Abstract: Abrasive Water Jet Machining is an unconventional machining process well known for machining hard to cut materials. The primary research focus on the process was for through cutting and a very limited literature is available on pocket milling using AWJM. The present work is an attempt to use this process for milling applications considering a set of various process parameters. Four different input parameters, which were considered by researchers for part separation, are selected for the above application, i.e., abrasive size, flow rate, standoff distance and traverse speed. Pockets of definite size are machined to investigate surface roughness, material removal rate and pocket depth. Based on the data available through experiments on SS304 material, it is observed that higher traverse speeds gives a better finish because of reduction in the particle energy density and lower depth is also observed. Increase in the standoff distance and abrasive flow rate reduces the rate of material removal as the jet loses its focus and occurrence of collisions within the particles. ANOVA for individual output parameter has been studied to know the significant process parameters.
Abstract: Metal matrix composites (MMC) are generating
extensive interest in diverse fields like defense, aerospace, electronics
and automotive industries. In this present investigation, material
removal rate (MRR) modeling has been carried out using an
axisymmetric model of Al-SiC composite during electrical discharge
machining (EDM). A FEA model of single spark EDM was
developed to calculate the temperature distribution.Further, single
spark model was extended to simulate the second discharge. For
multi-discharge machining material removal was calculated by
calculating the number of pulses. Validation of model has been done
by comparing the experimental results obtained under the same
process parameters with the analytical results. A good agreement was
found between the experimental results and the theoretical value.
Abstract: This paper describes a combined mathematicalgraphical
approach for optimum tool path planning in order to
improve machining efficiency. A methodology has been used that
stabilizes machining operations by adjusting material removal rate in
pocket milling operations while keeping cutting forces within limits.
This increases the life of cutting tool and reduces the risk of tool
breakage, machining vibration, and chatter. Case studies reveal the
fact that application of this approach could result in a slight increase
of machining time, however, a considerable reduction of tooling cost,
machining vibration, noise and chatter can be achieved in addition to
producing a better surface finish.
Abstract: Greenhouse gases (GHG) emissions impose major
threat to global warming potential (GWP). Unfortunately
manufacturing sector is one of the major sources that contribute
towards the rapid increase in greenhouse gases (GHG) emissions. In
manufacturing sector electric power consumption is the major driver
that influences CO2 emission. Titanium alloys are widely utilized in
aerospace, automotive and petrochemical sectors because of their
high strength to weight ratio and corrosion resistance. Titanium
alloys are termed as difficult to cut materials because of their poor
machinability rating. The present study analyzes energy consumption
during cutting with reference to material removal rate (MRR).
Surface roughness was also measured in order to optimize energy
consumption.
Abstract: FW4 is a newly developed hot die material widely
used in Forging Dies manufacturing. The right selection of the
machining conditions is one of the most important aspects to take
into consideration in the Electrical Discharge Machining (EDM) of
FW4. In this paper an attempt has been made to develop
mathematical models for relating the Material Removal Rate (MRR),
Tool Wear Ratio (TWR) and surface roughness (Ra) to machining
parameters (current, pulse-on time and voltage). Furthermore, a study
was carried out to analyze the effects of machining parameters in
respect of listed technological characteristics. The results of analysis
of variance (ANOVA) indicate that the proposed mathematical
models, can adequately describe the performance within the limits of
the factors being studied.