scholarly journals Design of Regenerative Flutter Stability Detection System in Machine Tool Cutting

2021 ◽  
Vol 2074 (1) ◽  
pp. 012071
Author(s):  
Liyao Li
Keyword(s):  
Machine Tool ◽  
Manufacturing Industry ◽  
Cutting Tool ◽  
Detection System ◽  
Machining Process ◽  
Advanced Technology ◽  
Practical Significance ◽  
Work Piece ◽  
Excited Vibration ◽  
Cutting Chatter

Abstract Cutting chatter is a strong relative vibration between cutting tool and work piece in machining process, which will reduce cutting quality and cutting efficiency, and shorten the service life of cutting tool and machine tool. As long as cutting is carried out in production, vibration will occur, and chatter is a strong self-excited vibration between machining work piece and cutting tool. Flutter problem will occur in almost all cutting processes, which will cause a series of problems such as the reduction of dimensional accuracy of machined work pieces, tool damage and so on. In the dynamic design and dynamic analysis of machine tool structure, in order to evaluate and improve the ability of machine tool to resist chatter, and to select the cutting conditions without chatter, it is necessary to judge the cutting stability of machine tool. How to improve the advanced technology of manufacturing industry is an important topic for manufacturing researchers, and the research on the detection of cutting chatter stability has important practical significance for promoting the development of cutting manufacturing industry to high-end technology.

Stability and Online Monitoring of Cutting Chatter: A Review

2011 ◽  
Vol 121-126 ◽  
pp. 377-381
Author(s):  
Yong Liang Zhang ◽  
Zhi Yuan Li
Keyword(s):  
Machine Tool ◽  
Manufacturing Industry ◽  
Online Monitoring ◽  
Rapid Development ◽  
Stability Limit ◽  
Cutting Process ◽  
Work Piece ◽  
Cutting Chatter ◽  
The Stability ◽  
Tool Cutting

Cutting chatter is a kind of severe vibration generating from the interaction of machine tool system and cutting process and it will seriously affect the performance of machine tool and the quality of work piece. With the rapid development towards high precision and automation of the modern manufacturing industry, the stability and monitoring of cutting process have become the hot issues in production and engineering field, lots of useful researches and explorations have been done worldwide. The research situations of stability limit prediction of machine tool cutting system and technology of chatter online monitoring are discussed, the problems and the developing trends are summarized.

Performance assessment of energy efficient and eco-friendly turning of Nimonic C-263: A comparative study on MQL and cryogenic machining

2021 ◽  
pp. 095440542110619
Author(s):  
Prashant S Jadhav ◽  
Chinmaya P Mohanty
Keyword(s):  
Work Environment ◽  
Manufacturing Industry ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Work Piece ◽  
Cryogenic Machining ◽  
Machined Surface ◽  
Machining Strategies ◽  
The Impact

Nimonic C-263 is predominantly used in the manufacturing of heat susceptible intricate components in the gas turbine, aircraft, and automotive industries. Owing to its high strength, poor thermal conductivity, the superalloy is difficult to machine and causes rapid tool wear during conventional machining mode. Moreover, the unpleasant machining noise produced during machining severely disrupts the tool engineer’s concentration, thereby denying a precise and environment friendly machining operation. Hence, close dimensional accuracy, superior machined surface quality along with production economy, and pleasant work environment for the tool engineers is the need of an hour of the current manufacturing industry. To counter such issues, the present work attempts to compare and explore the machinability of two of the most popular machining strategies like minimum quantity lubrication (MQL) and cryogenic machining process during turning of Nimonic C-263 work piece in order to achieve an ideal machining environment. The machining characteristics are compared in terms of surface roughness (SR), power consumption (P), machining noise (S), nose wear (NW), and cutting forces (CF) to evaluate the impact of machining variables like cutting speed (Vc), feed (f), and depth of cut (ap) with a detailed parametric study and technical justification. Yet again, an investigation is conducted to compare both the machining strategies in terms of qualitative responses like chip morphology, total machining cost, and carbon emissions. The study revealed that cryogenic machining strategy is adequately proficient over MQL machining to deliver energy proficient and gratifying work environment for the tool engineers by reducing the cost of machining and improving their work efficiency.

Investigation of Chatter Vibration in End-Milling Process by Considering Coupled System Model

2014 ◽  
Vol 939 ◽  
pp. 201-208
Author(s):  
Kosuke Hattori ◽  
Hiroyuki Kodama ◽  
Toshiki Hirogaki ◽  
Eiichi Aoyama
Keyword(s):  
Cutting Tool ◽  
End Milling ◽  
Milling Process ◽  
Work Piece ◽  
Vibration Modes ◽  
Test Results ◽  
Chatter Vibration ◽  
Simple Method ◽  
Excited Vibration ◽  
End Milling Process

Chatter vibration in cutting processes usually leads to surface finish degradation, tool damage, cutting noise, energy loss, etc. Self-excited vibration particularly seems to be a problem that is easily increased to large vibration. The regenerative effect is considered as one of the causes of chatter vibration. Although the chatter vibration occurs in various types of processing, the end-milling is a typical process that seems to cause the chatter vibration due to a lack of rigidity of one or more parts of the machine tools, cutting tool, and work-piece. The aim of our research is to propose a simple method to control chatter vibration of the end-milling process on the basis of a coupling model integrating the related various elements. In this study, hammering tests were carried out to measure the transfer function of a machine tool and cutting tool system, which seems to cause vibration. By comparing these results, finite elemental method (FEM) analysis models were constructed. Additionally, cutting experiments were carried out to confirm the chatter vibration frequencies in end-milling with a machining center. In the hammering tests, impulse hammer and multiple acceleration pick-ups are connected to a multi-channel FFT analyzer and estimate the natural frequencies and natural vibration modes. A simplified FEM model is proposed by circular section stepped beam elements on the basis of the hammering test results, considering a coupling effect. In comparisons of the calculated results and hammering test results, the vibration modes are in good agreement. As a result, the proposed model accurately predicts the chatter vibration considering several effects among the relating elements in end-milling. Moreover, it can be seen that the chatter vibration is investigated from a viewpoint of the integrating model of the end-milling process.

Researched on the Technology of Machining Simulation

2014 ◽  
Vol 1039 ◽  
pp. 390-396
Author(s):  
Bao Rui Li ◽  
Wen Hua Zhu ◽  
Benoit Eynard ◽  
Matthieu Bricogne
Keyword(s):  
Machine Tool ◽  
Manufacturing Industry ◽  
Production Costs ◽  
Machining Process ◽  
Simulation Test ◽  
Processing Efficiency ◽  
Simulation Engine ◽  
Blade Machining ◽  
Modern Manufacturing ◽  
Simulation Systems

The machine tool machining is a major processing method in manufacturing industry. Achieved the simulation for the machining process will greatly improved the processing efficiency, perfected the processing quality and reduced the production costs. It has important significance for the development of modern manufacturing industry. This paper studied the constitute of the processing verification and simulation systems. And focuses on the principle of the machine tool system driven by the common simulation engine and driven by the virtual NC controller. Finally, the simulation system was built and use the blade machining as an example to the simulation test and verify.

Vibration Control in Turning Machining

2013 ◽  
Vol 706-708 ◽  
pp. 1672-1675 ◽  
Author(s):  
Long Bo Chen ◽  
Ji Lin Guo ◽  
Tian Rui Zhou ◽  
Tao Jiang
Keyword(s):  
Free Vibration ◽  
Machine Tool ◽  
Vibration Control ◽  
Detailed Analysis ◽  
Forced Vibration ◽  
Cutting Tool ◽  
System Dynamic ◽  
Cutting Process ◽  
Excited Vibration ◽  
Process System

Vibration in turning processing is associated with free vibration, forced vibration and self-excited vibration, the composition and machine tool, tool and workpiece process system dynamic characteristic.A detailed analysis of the main types of vibration in turning and the causes, and put forward from the aspects of cutting tool, fixture, cutting process, reduce or eliminate vibration measures.

Modelling and Optimization of Tool Chip Interface Temperature and Surface Roughness in CNC Dry Turning of EN 24 Steel

2016 ◽  
Vol 16 ◽  
pp. 7-15 ◽  
Author(s):  
Nirmal Kumar Mandal ◽  
Tanmoy Roy
Keyword(s):  
Surface Roughness ◽  
Cutting Tool ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Minimum Quantity Lubrication ◽  
Machining Process ◽  
Interface Temperature ◽  
Depth Of Cut ◽  
Work Piece ◽  
Substantial Impact

Abstract. Kinetic energy of a machining process is converted into heat energy. The generated heat at cutting tool and work piece interface has substantial impact on cutting tool life and quality of the work piece. On the other hand, development of advanced cutting tool materials, coatings and designs, along with a variety of strategies for lubrication, cooling and chip removal, make it possible to achieve the same or better surface quality with dry or Minimum Quantity Lubrication (MQL) machining than traditional wet machining. In addition, dry and MQL machining is more economical and environment friendly. In this work, 20 no. of experiments were carried out under dry machining conditions with different combinations of cutting speed, feed rate and depth of cut and corresponding cutting temperature and surface roughness are measured. The no. of experiments is determined through Design of Experiments (DOE). Nonlinear regression methodology is used to model the process using Response Surface Methodology (RSM). Multi-objective optimization is carried using Genetic Algorithm which ensures high productivity with good product quality.

scholarly journals The application of machine learning to sensor signals for machine tool and process health assessment

2020 ◽  
pp. 095440542096089
Author(s):  
James Moore ◽  
Jon Stammers ◽  
Javier Dominguez-Caballero
Keyword(s):  
Machine Learning ◽  
Machine Tool ◽  
Manufacturing Industry ◽  
Failure Modes ◽  
Test Procedure ◽  
Machining Process ◽  
Sensor Data ◽  
Custom Made ◽  
Production Environments ◽  
Sensor Signals

Due to the latest advancements in monitoring technologies, interest in the possibility of early-detection of quality issues in components has grown considerably in the manufacturing industry. However, implementation of such techniques has been limited outside of the research environment due to the more demanding scenarios posed by production environments. This paper proposes a method of assessing the health of a machining process and the machine tool itself by applying a range of machine learning (ML) techniques to sensor data. The aim of this work is not to provide complete diagnosis of a condition, but to provide a rapid indication that the machine tool or process has changed beyond acceptable limits; making for a more realistic solution for production environments. Prior research by the authors found good visibility of simulated failure modes in a number of machining operations and machine tool fingerprint routines, through the defined sensor suite. The current research set out to utilise this system, and streamline the test procedure to obtain a large dataset to test ML techniques upon. Various supervised and unsupervised ML techniques were implemented using a range of features extracted from the raw sensor signals, principal component analysis and continuous wavelet transform. The latter were classified using convolutional neural networks (CNN); both custom-made networks, and pre-trained networks through transfer learning. The detection and classification accuracies of the simulated failure modes across all classical ML and CNN techniques tested were promising, with all approaching 100% under certain conditions.

An Analysis and Modeling of the Dynamic Stability of the Cutting Process Against Self-Excited Vibration

2020 ◽  
Vol 22 (4) ◽  
pp. 1287-1300
Author(s):  
A. Motallebia ◽  
A. Doniavi ◽  
Y. Sahebi
Keyword(s):  
Machine Tool ◽  
Removal Rate ◽  
Dimensional Accuracy ◽  
Modal Testing ◽  
Cutting Process ◽  
Work Piece ◽  
Stability Diagrams ◽  
Machine Tool Structure ◽  
Excited Vibration ◽  
The Stability

AbstractChatter is a self-excited vibration which depends on several parameters such as the dynamic characteristics of the machine tool structure, the material of the work piece, the material removal rate, and the geometry of tools. Chatter has an undesirable effect on dimensional accuracy, smoothness of the work piece surface, and the lifetime of tools and the machine tool. Thus, it is useful to understand this phenomenon in order to improve the economic aspect of machining. In the present article, first the theoretical study and mathematical modeling of chatter in the cutting process were carried out, and then by performing modal testing on a milling machine and drawing chatter stability diagrams, we determined the stability regions of the machine tool operation and recognized that witch parameter has a most important effect on chatter.

Cutting Force and Friction Modelling in High Speed End-Milling

2015 ◽  
Author(s):  
Sunday J. Ojolo ◽  
Olumuwiya Agunsoye ◽  
Oluwole Adesina ◽  
Gbeminiyi M. Sobamowo
Keyword(s):  
Temperature Field ◽  
Temperature Distribution ◽  
Cutting Forces ◽  
High Speed ◽  
Metal Cutting ◽  
Cutting Tool ◽  
End Milling ◽  
Cutting Process ◽  
Machining Process ◽  
Work Piece

Temperature field in metal cutting process is one of the most important phenomena in machining process. Temperature rise in machining directly or indirectly determines other cutting parameters such as tool life, tool wear, thermal deformation, surface quality and mechanics of chip formation. The variation in temperature of a cutting tool in end milling is more complicated than any other machining operation especially in high speed machining. It is therefore very important to investigate the temperature distribution on the cutting tool–work piece interface in end milling operation. The determination of the temperature field is carried out by the analysis of heat transfer in metal cutting zone. Most studies previously carried out on the temperature distribution model analysis were based on analytical model and with the used of conventional machining that is continuous cutting in nature. The limitations discovered in the models and validated experiments include the oversimplified assumptions which affect the accuracy of the models. In metal cutting process, thermo-mechanical coupling is required and to carry out any temperature field determination successfully, there is need to address the issue of various forces acting during cutting and the frictional effect on the tool-work piece interface. Most previous studies on the temperature field either neglected the effect of friction or assumed it to be constant. The friction model at the tool-work interface and tool-chip interface in metal cutting play a vital role in influencing the modelling process and the accuracy of predicted cutting forces, stress, and temperature distribution. In this work, mechanistic model was adopted to establish the cutting forces and also a new coefficient of friction was also established. This can be used to simulate the cutting process in order to enhance the machining quality especially surface finish and monitor the wear of tool.

Charged-Particle Emissions During Material Deformation, Failure and Tribological Interactions of Machining

2018 ◽  
Vol 141 (3) ◽  
Author(s):  
Jagadeesh Govindaraj ◽  
Sathyan Subbiah
Keyword(s):  
Plastic Deformation ◽  
Charged Particle ◽  
Emission Intensity ◽  
Cutting Tool ◽  
Charged Particles ◽  
Machining Process ◽  
Work Piece ◽  
Machining Parameters ◽  
Particle Emissions ◽  
Faraday Plate

Charged particles are emitted when materials undergo tribological interactions, plastic deformation, and failure. In machining, plastic deformation and shearing of work piece material takes place continuously along with intense tool-chip rubbing contact interactions; hence, the emission of charged particles can be expected. In this work, an in-situ sensor has been developed to capture the emitted positive (positive ion) and negative (electron and negative ion) charged particles in real-time in an orthogonal machining process at atmospheric conditions without the use of coolant. The sensor consists of a Faraday plate, mounted on the flank face of the cutting tool, to collect the emitted ions and the intensity of emissions is measured with an electrometer. Positively and negatively charged particles are measured separately by providing suitable bias voltage supply to the Faraday plate. Ion emissions are measured during machining of three different work piece materials (mild steel, copper, and stainless steel) using a carbide cutting tool. The experimental results show a strong correlation between the emission intensity and the variation in machining parameters and material properties. Increasing material removal rate increases the intensity of charged particle emissions because of the increase in volume of material undergoing shear, fracture, and deformation. It is found that emission intensity is directly proportional to the resistivity and strength of workpiece material. Charged particles emission intensity is found to be sensitive to the machining conditions which enables the use of this sensor as an alternate method of condition monitoring.

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