Balla Prasad | Gitam University,Visakhapatnam,India (original) (raw)

Papers by Balla Prasad

Journal for Manufacturing Science and Production, Jun 1, 2016

In the present work investigation primarily focuses on identifying the presence of cutting tool v... more In the present work investigation primarily focuses on identifying the presence of cutting tool vibrations during face turning process. For this purpose an online non-contact vibration transducer i. e. laser Doppler Vibrometer is used as part of a novel approach. The revisions in the values of cutting forces, vibrations and acoustic optic emission signals with cutting tool wear are recorded and analyzed. This paper presents a mathematical model in an attempt to understand tool lifeunder vibratory cutting conditions. Tool wear and cutting force data are collected in the dry machiningof AISI 1040 steel at different vibrationinduced test conditions. Identifying the correlation among tool wear, cutting forces and displacement due to vibration is a critical task in the present study. These results are used to predict the evolution of displacement and tool wear in the experiment. Specifically, the research tasks include: to provide an appropriate experimental data to prove the mathematical model of tool wear based on the influence of cutting tool vibrations in turning.The modeling is focused on demonstrating the scientific relationship between the process variables such as vibration displacement, vibration amplitude, feedrate, depth of cut and spindle speed while getting into account machine dynamics effect and the effects such as surface roughness and tool wear generated in the operation. Present work also concentrates on the improvement in machinability during vibration assisted turning with different cutting tools. The effect of work piece displacement due to vibration on the tool wear is critically analyzed. Finally, tool wear is established on the basis of the maximum displacement that can be tolerated in a process for an effective tool condition monitoring system.

International Journal of Machining and Machinability of Materials, 2008

... Department of Mechanical Engineering, GITAM Institute of Technology, GITAM University, Visakh... more ... Department of Mechanical Engineering, GITAM Institute of Technology, GITAM University, Visakhapatnam 530 045, India E-mail: bsp.prasad@gmail.com *Corresponding author ... At present working as an Assistant Professor in GIT, GITAM University, Visakhapatnam, India. ...

The International Journal of Advanced Manufacturing Technology, Jan 13, 2011

In metal cutting as a result of the cutting motion, the surface of workpiece will be influenced b... more In metal cutting as a result of the cutting motion, the surface of workpiece will be influenced by cutting parameters, cutting force, and vibrations, etc. Thus, by monitoring the machined surface topography of the workpiece and extracting the relevant information the cutting process and tool wear state should be able to be monitored and quantified. But the effects of vibrations have been paid less attention. The work in the present paper is divided into two parts. First part consists of a data acquisition and signal processing using acousto optic emission sensor (i.e., laser Doppler vibrometer) for online tool condition monitoring and the second part of the work presents the surface topography analysis of machined surfaces during the progression of the tool wear. Most of the work presented is also a study where surface metrology is being used to measure all aspects of the machining in combination with an online metrology tool. The encouraging results of the work pave the way for the development of a real-time, low cost, and reliable tool-condition-monitoring system. A high degree of correlation is established between the results of the acousto optic emission signal-and vision-based surface textural analysis in identification of tool wear state.

The International Journal of Advanced Manufacturing Technology, Apr 1, 2010

In automated manufacturing systems, one of the most important issues is accurate detection of the... more In automated manufacturing systems, one of the most important issues is accurate detection of the tool conditions under given cutting conditions so that worn tools can be identified and replaced in time. In metal cutting as a result of the cutting motion, the surface of workpiece will be influenced by cutting parameters, cutting force, and vibrations, etc. But the effects of vibrations have been paid less attention. In the present paper, an investigation is presented of a tool condition monitoring system, which consists of a fast Fourier transform preprocessor for generating features from an online acousto-optic emission (AOE) signals to develop a database for appropriate decisions. A fast Fourier transform (FFT) can decompose AOE signals into different frequency bands in the time domain. Present work uses a laser Doppler vibrometer for online data acquisition and a high-speed FFT analyser used to process the AOE signals. The generation of the AOE signals directly in the cutting zone makes them very sensitive to changes in the cutting process due to vibrations. AOE techniques is a relatively recent entry into the field of tool condition monitoring. This method has also been widely used in the field of metal cutting to detect process changes like displacement due to vibration and tool wear, etc. In this research work the results obtained from the analysis of acousto-optic emission sensor employs to predict flank wear in turning of AISI 1040 steel of 150 BHN hardness using Carbide insert and HSS tools. The correlation between the tool wear and AOE parameters is analyzed using the experimental study conducted in 16 H.P. all geared lathe. The encouraging results of the work pave the way for the development of a real-time, low-cost, and reliable tool condition monitoring system. A high degree of correlation is established between the results of the AOE signal and experimental results in identification of tool wear state.

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Nov 6, 2014

This article presents the correlation of vibration signal feature, that is, displacement due to v... more This article presents the correlation of vibration signal feature, that is, displacement due to vibration (microns) during the machining and three-dimensional finite element simulations in tool wear monitoring of a metal turning operation. Machining of AISI 1040 has been carried on using an uncoated inserts and online vibration signals acquired using a laser Doppler vibrometer. The measured tool wear forms correlate to features in the vibration signals in frequency domains. Analyses of the results suggested that the vibration signals’ features are effective for use in cutting tool wear monitoring and wear qualification. Present work demonstrates the three-dimensional finite element analysis to predict the workpiece displacements in feed direction and corresponding tool wear with the help of induced vibrations in face turning under dry machining conditions. Vibration-assisted turning model is developed and validated by comparing the simulation results with experimental results. In this research, three-dimensional finite element modelling and simulation issues for vibration-assisted turning are explored in detail. Machine dynamic effects are taken into account to predict the outcomes such as tool wear displacements and chip formation. The model can be implemented in an online tool wear monitoring system which predicts the actual state of tool wear in real time by correlating displacement variations during the machining. The correlation between the displacement due to vibration and flank wear has been evaluated through three-dimensional finite element modelling and simulation. Comparisons of simulations with experimental results demonstrate their predictive capability. From the results, useful conclusions may be drawn, and it can be stated that the proposed models can be used for industrial application.

Engineering Science and Technology, an International Journal, Feb 1, 2017

In this paper, a correlation between vibration amplitude and tool wear when in dry turning of AIS... more In this paper, a correlation between vibration amplitude and tool wear when in dry turning of AISI 4140 steel using uncoated carbide insert DNMA 432 is analyzed via experiments and finite element simulations. 3D Finite element simulations results are utilized to predict the evolution of cutting forces, vibration displacement amplitudes and tool wear in vibration induced turning. In the present paper, the primary concern is to find the relative vibration and tool wear with the variation of process parameters. These changes lead to accelerated tool wear and even breakage. The cutting forces in the feed direction are also predicted and compared with the experimental trends. A laser Doppler vibrometer is used to detect vibration amplitudes and the usage of Kistler 9272 dynamometer for recording the cutting forces during the cutting process is well demonstrated. A sincere effort is put to investigate the influence of spindle speed, feed rate, depth of cut on vibration amplitude and tool flank wear at different levels of workpiece hardness. Empirical models have been developed using second order polynomial equations for correlating the interaction and higher order influences of various process parameters. Analysis of variance (ANOVA) is carried out to identify the significant factors that are affecting the vibration amplitude and tool flank wear. Response surface methodology (RSM) is implemented to investigate the progression of flank wear and displacement amplitude based on experimental data. While measuring the displacement amplitude, R-square values for experimental and numerical methods are 98.6 and 97.8. Based on the R-square values of ANOVA it is found that the numerical values show good agreement with the experimental values and are helpful in estimating displacement amplitude. In the case of predicting the tool wear, R-square values were found to be 97.69 and 96.08, respectively for numerical and experimental measures while determining the tool wear. By taking R-square values into account, ANOVA confirms the close relation between experimental values and numerical values in evaluating the tool wear.

International journal of computer applications in technology, 2011

In metal cutting, as a result of the cutting motion, the surface of work piece will be influenced... more In metal cutting, as a result of the cutting motion, the surface of work piece will be influenced by cutting parameters, cutting force, vibrations, etc. The effects of vibrations have been paid little attention. Accurate detection of the tool conditions under given cutting conditions is very important so that worn tools can be identified and replaced in time. Objective of the present work is to predict the effects of displacements due to vibration during face milling and to examine the correlation of surface roughness along with progression of tool wear at different machining combinations so as to develop a base for online tool condition monitoring system. A laser doppler vibrometer and FFT analyser are used for online data acquisition and subsequent processing of signals. The encouraging results of the work pave the way for the development of a real-time and reliable tool-condition-monitoring system.

International Journal of Machining and Machinability of Materials, 2008

International Journal of Computer Applications in Technology, 2011

In this paper an experimental investigation is presented for accomplishing surface texture analys... more In this paper an experimental investigation is presented for accomplishing surface texture analysis using machine vision based system for measuring the condition of the cutting tool. Texture of the machined surface provides reliable information regarding the extent of the tool wear because tool wear affects the surface roughness dramatically. Analysis of the machined surface images of C-SiC material is done by grabbing the image using a scanning electron microscope, amplitude parameters based approach for analysis of machined surface is used. Machined surfaces are investigated using surface metrology software "TRUEMAP". Since the machined surface is a negative replica of the shape of the cutting tool and reflects the volumetric changes in the cutting edge shape, it is more suitable to analyze the machined surface than to look at the cutting tool. However, no work has been performed on the development of surface texture of machined work piece that provide information on the condition of cutting tool employed for machining C-SiC composite material. In this paper, a non-contact method using machine vision with surface metrology software is presented for inspecting surface roughness of machined surfaces. Machined surfaces produced under different cutting conditions are studied to measure the cutting tool condition. A strong correlation is found between tool wear and surface texture of the machined surfaces. Results prove that the approach is effective in measuring the condition of the cutting tool through amplitude parameters.

The International Journal of Advanced Manufacturing Technology, 2022

Journal of Engineering and Applied Science, 2021

In this paper, a connection between vibration amplitude and tool wear when drilling of IS3048 ste... more In this paper, a connection between vibration amplitude and tool wear when drilling of IS3048 steel utilizing different dimensioned tools is dissected through tests. Discriminant features, which are sensitive to drill wear and breakage, were developed. These were discovered to be somewhat impervious toward sensor location and cutting conditions. In the process, the vibration amplitude features a checking highlight dependent on ascertaining both the tools and their performance over vibrations, which was discovered to be somewhat powerful for on-line identification of drill tool breakage in both frequency and time domains. These vibrational amplitude signal features are directly affected, related to the tool geometry, which give higher chances of tool selection criteria during the drilling process. The experiments were carried out using solid carbide tool with change in tool geometry under dry conditions where the vibration amplitude for both is evaluated. The results revealed that cu...

Materials Today: Proceedings

SN Applied Sciences

In this study, a multiple sensor data fusion system is anticipated as essential for monitoring of... more In this study, a multiple sensor data fusion system is anticipated as essential for monitoring of cutting operations, by identifying suitable sensor locations to obtain feedback signals periodically. The sensor signal derives the failure during machining owing to complex cutting tool geometry even in machining of composites. Nano metal matrix composites (NMMC) being extremely upright in mechanical characteristics, consequently machining of these hybrid nano metal matrix composites reinforced with difficult-to-cut nano particles leads to reduced tool life thereby causing rapid flank wear. Therefore, it is a challenge to identify the wear features caused during machining of tailor made NMMC's, reducing wastage and preventing machine malfunction. This paper presents a comprehensive review on the machining strategies in extreme output conditions which rely on input parameters of speed, feed and depth of cut influencing tool life during CNC machining. This can be achieved only with multiple sensor data fusion technique during CNC machining.

Materials Today: Proceedings

Journal of the Brazilian Society of Mechanical Sciences and Engineering