Mrr

An experiment was carried out to assess the economic feasibility of maize-wheat cropping system for five different fertility treatments (T1,control; T2, PGPR + PK (80-60 kg ha-1), T3, (120-80-60 NPK kg ha-1); T4, poultry manure at the rate of 15 t ha-1 , and T5, half poultry manure (7.5 t ha-1) + half PK (40-30 kg ha-1) + PGPR. According to statistical and economic analysis of the data revealed that maize plots treated with half poultry manure + half PK + PGPR gave 43% maize grain yield higher over control. Maximum wheat yield was recorded in plots previously treated poultry manure. Maize wheat cropping sequence accrued the highest net benefit of Rupees 78419.66 ha-1 than rest of the treatments. Likewise, considerable higher marginal rate of return 441.03 % was observed for maize wheat system with half poultry manure + half PK + PGPR and resulted in utmost residual value as verified through residual analysis in similar treatment. On the basis of agronomic as well as economic performance of maize it was well evident that combined use of organic, biofertilizers and chemical fertilizers proved to be more productive, sustainable and remunerative and can be recommended for maize growers to improve maize productivity and elevate their income.

The objective of this paper is to study the effect of different process parameter of wire electrical discharge machine (WEDM) process on the performance measures such as material removal rate (MRR), surface roughness, dimensional accuracy and kerf width. It is necessary to evaluate the factors that affect the productivity and efficiency of WEDM process. It will directly contribute to increase cutting speed and dimensional accuracy.

Abrasive water jet machining, one of the non-traditional processes for machining and cutting uses the abrasive particles mixed with the water jet and is impinged onto the workpiece for manufacturing processes. In this study focus is on the investigation of experimental work based on Taguchi method for machining of granite material with abrasive water jet machine. Three control factors were selected-Traverse speed (mm/min), Water pressure (MPa) and Stand-off distance (mm) with two response parameters – Material removal rate (gm/min) and Surface roughness (í µí»m). With the help of ANOVA (Analysis of variance), it was observed that traverse speed was the most significant parameter affecting Material removal rate (MRR), while Stand-off distance (SOD) was found to be the most significantly affecting factor for the surface roughness parameter. It was also observed that with increase in traverse speed, MRR and surface increases. A multiple linear regression model was also developed for prediction of results.

In the last few years the development of new materials show deep growth but the major problem is it’s machining. So it is necessary adopt new machining methods. CNC (Computer Numerical Control) milling machine is one of the common machine tools in machine industry. Face milling is very common method for finishing of new materials and machined materials. The determination of optimal process parameters such as spindle speed, tool feed and depth of cut are one of the vital parameters. All experiment conduct on CNC face milling machine on SS202 material. During the face milling process, the material is removed by the face mill cutter. The effects of various parameters of face milling process like spindle speed, depth of cut, feed rate have been investigated to reveal their Impact on Material Removal Rate and surface roughness using Taguchi Methodology. The experiments are conducted by using Taguchi L9 orthogonal array as suggested by Taguchi. Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA) is employed to analyses the effect of milling parameters on material removal rate and surface roughness. Experimental plan is performed by a Standard Orthogonal Array. The results of analysis of variance (ANOVA) indicate that the proposed mathematical model can be adequately describing the performance within the limit of factors being studied and various plots were generated by using MINITAB software.

Drilling is one of the most common and fundamental machining processes. In machining, twist drills with diameters of 1–20 mm are used. Most of automotive components are manufactured using a conventional machining process, such as turning, drilling, milling, shaping and planning, etc.. These focus on producing high quality products in time at minimum cost. The surface roughness and MRR are considered to be a measure of the technological quality of a product. The aim of the present work is to optimize cutting conditions (Cutting speed, feed, wet and dry cutting, depth of hole) parameters for minimum MRR in drilling of AISI H11 using Face Centered Design . Experiments were conducted based on the design of experiments (DOE) and followed by optimization of the results using Analysis of Variance (ANOVA) to find the maximum material removal rate (MRR).

The hard-turning process is steadily finding its place in modern manufacturing technology and with advance cutting tool materials it can be applied as alternative machining process to grinding providing a more economical way to finish hard surfaces. The main concerns of hard turning are tooling cost and the effect of process on machinability characteristics. The poor selection of process parameters may cause excessive tool wear and increased surface roughness. Hence there is a need to find the right parameters to achieve the right dimensional accuracy, good surface and maximum material removal rate. This paper reviews the effects of various process parameters such as cutting speed, depth of cut and feed rate on the response parameters such as surface roughness, material removal rate and chip reduction coefficient. Through this study main cutting parameters which affect the turning operation are discussed.

Electro Discharge Machining Processes are used only when no other traditional machining process, like drilling, milling, grinding and other traditional machining operation can meet the necessary requirements efficiently and economically. Electro discharge machining is a non-traditional

Wire-cut Electric Discharge Machine (WEDM) process is one of the most widely used non-traditional machining processes in current manufacturing. This work presents the effect using different combinations of input parameters like pulse on time, pulse off time, output responses like kerf width, MRR, surface roughness (Ra) and the surface topography on different types of materials using design of experiments. A standard orthogonal array in Taguchi is used as a technique in design of experiments. The selection of the parameters depends on the requirements based on a better surface roughness or a maximum material removal rate. Hence an appropriate combination of the variables can be selected accordingly.

Dry EDM is an environment-friendly modification of the oil based EDM process. In the current work, a unit has been developed to implement dry EDM process on existing oil based EDM machine. All experiments are performed on bright mild steel with the help of hollow copper electrode. Response variables analyzed are material removal rate, tool wear rate and surface roughness. Design of experiments is done using Taguchi method. All experiments are performed using process parameters such as current, pulse on time and oxygen gas pressure. The statistical analysis of results show that current and POT significantly influence MRR and TWR.

This paper presents complete process of turning operation by using CNC machine tool and the input parameters associated with the process that can be controlled to enhance the output quality parameters like material removal rate and average surface roughness as per the desired requirement. Every detail of turning operation and associated parameters is explained. The optimization techniques like Taguchi, Anova, S/N ratio, grey relational analysis is also described and their importance is also discussed in detail. The study explains step by step procedure involved in optimization of turning process in detail.

The development of new materials shows the immense growth but the major problem, it is very difficult to machine the newly developed materials. So it is necessary to adopt some new machining methods. Electrical Discharge Machining (EDM) is a non-traditional and most popular machining method to manufacture dies, punches and press tools because of its capability to produce complicated, intricate shapes and to machine hard materials. Electrical Discharge Machining performance is generally evaluated on the basis of Overcut (OC), Material Removal Rate (MRR), Tool Wear Rate (TWR) and Surface Roughness (SR). The important EDM machining parameters affecting to the performance measures of the process are discharge current, pulse on time, pulse off time, arc gap, and duty cycle. Several approaches are proposed in the literature to solve the problems related with optimization of these parameters. It is felt that a review of the various approaches developed would help to compare their main features and their relative advantages or limitations to allow choose the most suitable approach for a particular application and also throw light on aspects that needs further attention. In view of above, this paper presents a review of Effect of Electrode Material on Overcut, MRR, TWR of Steel Material in EDM.

Heat Assisted Drilling Machine (HADM) is a new technique to drill hard, brittle and ceramic materials. This system is hybrid of conventional and non-conventional manufacturing processes, In which conventional radial drilling machine were used and non-conventional heating source used. Heat source decreases the hardness and brittleness of material by thermally softening phenomenon. Ti6Al4V has been used as the working material in this research. HSS M42 has been used as the tool material for drilling operation. It has been demonstrated that HADM process can improves the material removal rate and surface finish

The main aim of this Project work is to study experimentally the influence of depth of cut, cutting speed, and feed rate on the tool tip temperature, Material Removal Rate, Surface Roughness during turning process. The experiments will be obtained by varying one parameter while, the remaining two parameter were kept constant. So the influence of tool tip on different machining parameters is done in this research work. To increase the tool life, Taguchi Optimization method is used to optimization of machining parameters. The Taguchi method, a powerful tool of design optimization for quality, is used to find the optimal cutting parameters for turning operations. Through this study, not only the optimal cutting parameters for turning operations are obtained, but also the main cutting parameters that affect the cutting performance in turning operations will be evaluated. Experimental results will be provided to confirm the effectiveness of this approach. It will give the best result for turning operation of EN19 Material.

The objective of the present study is to investigate the optimal process parameters of Electric Discharge Machining (EDM) on Inconel 800 alloy material with molybdenum as a tool electrode. The input parameters considered were voltage, pulse on time, pulse off time, current and bed speed for the experimental work and their effect on Material Removal Rate (MRR) and Surface Roughness (Ra) while machining Inconel 800 in Wire Electric Discharge Machining (WEDM). The effect of various process parameters on machining performance is investigated in this study. Taguchi method is used to formulate the experiment and L18 orthogonal array is selected for the experimentation. ANOVA is used to analyze the effect of input process parameters on the machining characteristics. To predict the machining characteristics using Artificial Neural Network (ANN) is used and were later compared with the experimental results. The results of the present work reveal that proper selection of input parameters play a significant role while machining with EDM.

In this paper the experimental work, where AISI D3 material is machined by using other four edges of CNMG 120408 is
explained. In this work, we also compare the scrap edges of CNMG with SPKN 1203 R, which is commonly used in milling. In
this work we use a special milling cutter having dia 50mm .The cutter has five pockets & we use the scrap edges of CNMG for
milling. We also optimize the influence of the tool on the end results by using Taguchi methodology .The design of experiment used for experiment is L18. In production the tooling cost is very effective due to its high cost. By using scrap inserts & special make tools like milling cutters, boring bars, we are able to reduce the tooling cost. Mostly in industries the welded tool are used for milling & turning or tooling of high cost is used. But by using these scrap inserts we can reduce labor cost as well as tooling cost. Steam jet act as transportation carriers carrying the heat away from the cutting region, and the efficiency of this cooling
method largely depends on jet pressure. The input parameters used in this work is Speed, Feed, Depth of cut, Pressure. Four level of input parameters are used i.e. speed (450 rpm, 900 rpm, 2900 rpm), feed (20mm/min, 35mm/min, 65 mm/min), Depth of cut (0.5 mm, 0.75 mm, 1mm). The material used in this thesis is AISI D3 block (60mmx70mm).In this, we analyses the effect of micro Hardness, Surface Roughness and Material Removal Rate (MRR) due to cutting parameters by using Taguchi method. The
optimization is done using eighteen experimental runs based on L’18 orthogonal array of the Taguchi method, and are performed to derive objective functions to be optimized within the experimental domain.

Higher material removal rate with better surface finish is one of the prime
requirements of today’s industry. The present paper investigate the effects of cutting parameters like spindle speed, feed and depth of cut on surface finish and material removal rate of Aluminium 7075-T6. Taguchi methodology has been applied to optimize cutting parameters. Feed rate is the most significant factor influencing surface finish whereas material removal rate is significantly affected by cutting speed. For highest MRR with better surface finish. Cutting speed (15.102 m/min) ,feed rate (0.3207 mm/rev.) and depth of cut (0.5 mm) are cutting parameters for higher MRR and optimum surface roughness

EDM is a well-established hole machining option with various advantages due to non-contact characteristics of the process. However, knowledge about the process is not enough for its more improvements. Exprimenal studies are costly  and  time  consuming  because  of  the  complex  nature  of  process. Therefore, process modeling is a good alternative to reduce the experimental expense related to the technology. This paper studys EDM process through mathematical model, which includes the precise insight into the interactive behavior of EDM system. The ignition, discharge and recovery phases of the model  have  been  developed  through  MATLABs  time  domain  analysis.Simulation  result  shows  good  agreement  with  expected  profile  of EDM spark. To verify the model, simulated material removal rates (MRRs) from series of simulation are compared with the experimental ones reported by previous researcher. Ability of the model to predict the dynamic behavior profile  of  the  EDM  system  is  successfully  confirmed  by  low  average percentage error in predicting MRR.

Electrical discharge machining (EDM) is non-traditional machining processes. EDM process is based on thermoelectric energy between the work piece and a tool electrode. A pulse discharge occurs in a small gap between the work piece and the tool electrode and removes the unwanted material from the material through melting and vaporizing. The present study discusses about having an overview of the Electrical discharge machining process, and influence of process parameters like input current, pulse on time and pulse off time on performance parameter such as MRR, EWR and over cut. This study discusses about controlling the process parameters and optimization of process parameters in EDM process. From the review, it has been observed that the machining process can be improved by process parameters like current, pulse on time and pulse off time and also observed that electrodes material also effect on the material removal rate, electrode wear rate and over cut.

The degraded quality on the machined parts due to shorter tool life, and unpleasant noise, hence is to be necessarily damped out. For efficient use of machine tools, selection of machining process and design of optimal cutting parameters (speed, feed and depth of cut) are required. In this work milling machine is used to design the forecast value of output responses. The aim of this work is to discover the role of these parameters is to prediction in milling operations by using artificial neural networks.

Design of experiments is performed to analyse the effect of air pressure, nozzle diameter and Stand off distance on the Material Removal Rate (MRR) and Kerf width of hard and brittle materials like Ceramics. The results of the machining experiments were used to characterise the main factors affecting MRR and Kerf width by the Analysis of Variance
(ANOVA) method. The maximum MRR obtained during experimentation is 0.09476 gm/sec & minimum Kerf width is 5.7325 mm. The nozzle diameter was found to be the most significant parameter influencing the MRR in cutting process.

Machine learning projects were conceived in March 2009 as part of the International Scientific Studies Project initiative at the Provisional Technical Secretariat of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) and initiated a few months later. Some of the projects are intended to aim at short to medium term operational applications. These include the identification of seismic and hydroacoustic phase names using a large number of features extracted from the waveforms, and the labeling of automatic events as real or false depending again on a large number of features from the automatic events. Concrete research results using International Data Centre (IDC) data are available for these two sets of projects. Seismic phase identification is shown to have the potential to improve its accuracy by 23 %, and the software developed for the project on false events identification has been tested at the IDC and shown to correctly label 80% of the false alarms. Some projects ar...

Cutting brittle surfaces using an abrasive jet machine (AJM). The current research focuses on testing performance parameters such as Material Removal Rate (MRR) and Surface Roughness (SR) with different controlling parameters. Controlling parameters for measuring their effects on AJM performance parameters include air pressure, abrasive particle, temperature, and mixing chamber speed. In comparison to traditional AJM methods, the newly designed AJM has a special heating jacket and rotary mechanism for experimental purposes. The MRR and SR increase as the pressure, temperature, and speed of the mixing chamber increase, according to the results of the experiments

Heat Assisted Drilling Machine (HADM) is a new technique to drill hard, brittle and ceramic materials. This system is hybrid of conventional and non-conventional manufacturing processes, In which conventional radial drilling machine were used and non-conventional heating source used. Heat source decreases the hardness and brittleness of material by thermally softening phenomenon. Ti6Al4V has been used as the working material in this research. HSS M42 has been used as the tool material for drilling operation. It has been demonstrated that HADM process can improves the material removal rate and surface finish.