New Development in High Efficiency Deep Grinding

2012 ◽  
Author(s):  
Andre D. L. Batako ◽  
Valery V. Kuzin ◽  
Brian Rowe
Keyword(s):  
Machine Tool ◽  
High Efficiency ◽  
Machining Process ◽  
Depth Of Cut ◽  
Removal Rates ◽  
Workpiece Surface ◽  
New Development ◽  
Cutting Processes ◽  
Selection Of ◽  
Made In

High Efficiency Deep Grinding (HEDG) has been known to secure high removal rates in grinding processes at high wheel speed, relatively large depth of cut and moderately high work speed. High removal rates in HEDG are associated with very efficient grinding and secure very low specific energy comparable to conventional cutting processes. Though there exist HEDG-enabled machine tools, the wide spread of HEDG has been very limited due to the requirement for the machine tool and process design to ensure workpiece surface integrity. HEDG is an aggressive machining process that requires an adequate selection of grinding parameters in order to be successful within a given machine tool and workpiece configuration. This paper presents progress made in the development of a specialised HEDG machine. Results of HEDG processes obtained from the designed machine tool are presented to illustrate achievable high specific removal rates. Specific grinding energies are shown alongside with measured contact arc temperatures. An enhanced single-pole thermocouple technique was used to measure the actual contact temperatures in deep cutting. The performance of conventional wheels is depicted together with the performance of a CBN wheel obtained from actual industrial tests.

A Method of Using Neural Networks and Inverse Kinematics for Machine Tools Error Estimation and Correction

1997 ◽  
Vol 119 (2) ◽  
pp. 247-254 ◽  
Author(s):  
J. Mou
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Machine Tool ◽  
Inverse Kinematics ◽  
Network Models ◽  
Thermal Conditions ◽  
Depth Of Cut ◽  
Time Varying ◽  
Neural Network Models ◽  
Cutting Processes

A method using artificial neural networks and inverse kinematics for machine tool error correction is presented. A generalized error model is derived, by using rigid body kinematics, to describe the error motion between the cutting tool and workpiece at discrete temperature conditions. Neural network models are then built to track the time-varying machine tool errors at various thermal conditions. The output of the neural network models can be used to periodically modify, using inverse kinematics technique, the error model’s coefficients as the cutting processes proceeded. Thus, the time-varying positioning errors at other points within the designated workspace can be estimated. Experimental results show that the time-varying machine tool errors can be estimated and corrected with desired accuracy. The estimated errors resulted from the proposed methodology could be used to adjust the depth of cut on the finish pass, or correct the probing data for process-intermittent inspection to improve the accuracy of workpieces.

Standardization and System Implementation of Cutting Parameter Selection Process

2012 ◽  
Vol 505 ◽  
pp. 11-14 ◽  
Author(s):  
Yu Bai ◽  
Yan Cao ◽  
Xiao Fen Zhang
Keyword(s):  
Selection Process ◽  
Cutting Parameters ◽  
Scientific Basis ◽  
Parameter Selection ◽  
Flow Management ◽  
Management Framework ◽  
Cutting Parameter ◽  
Cutting Processes ◽  
Selection Of ◽  
Made In

The goal of the paper is to design a system that helps to select cutting parameters in cutting processes. The approach is based on industrial engineering methods. The result is the parameters that take into account all the existing restrictive factors. First, a reasonable process to select cutting parameters is proposed. And then, the corresponding tools are designed. To achieve the standardization of the resources and process of cutting parameter selection, the resource contents and query actions are made in a uniform form. Finally, the selection of cutting parameters is realized within a flow management framework. It provides a scientific basis for selecting cutting parameters in actual production

scholarly journals Using tool wear to increase process stability when milling Al7075 and AISI 4140+QT

2021 ◽  
Author(s):  
Berend Denkena ◽  
Alexander Krödel ◽  
Andreas Relard
Keyword(s):  
Tool Wear ◽  
Flank Wear ◽  
Load Capacity ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Process Stability ◽  
Side Milling ◽  
Machine Performance ◽  
Cutting Processes

AbstractOne of the main limits of productivity during cutting processes is the occurrence of regenerative chatter. Due to these self-excited vibrations, the load capacity of the machine components, the tool as well as the machine performance cannot be fully utilized. There are several methods to stabilize the milling process. One is the use of increased process damping, which results from the contact of the tool’s flank face and the workpiece. The flank wear land naturally increases the contact between tool and workpiece. However, this effect has not been used to increase productivity in milling processes. This paper investigates with experiments and numerical simulations how tool wear affects process stability in milling of aluminum and steel. Therefore slot milling and side milling tests were carried out with tools of various states of flank wear. It could be shown that increasing flank wear allows to raise the depth of cut ap up to 300% in machining aluminum and perform the machining process with a higher productivity.

Machinability Investigation of Reaction-Bonded Silicon Carbide by Single-Point Diamond Turning

2008 ◽  
Vol 389-390 ◽  
pp. 151-156 ◽  
Author(s):  
Zhi Yu Zhang ◽  
Ji Wang Yan ◽  
Tsunemoto Kuriyagawa
Keyword(s):  
Surface Roughness ◽  
Silicon Carbide ◽  
Large Scale ◽  
High Efficiency ◽  
Low Cost ◽  
Single Point ◽  
Diamond Turning ◽  
Machining Process ◽  
Depth Of Cut ◽  
Material Microstructure

Reaction-bonded silicon carbide (RB-SiC) is a recently developed ceramic material with many merits such as low manufacturing temperature, dense structure, high purity and low cost. In the present paper, the precision machinability of RB-SiC was studied by microindentation and single-point diamond turning (SPDT) tests. The influence of depth of cut and tool feed rate on surface roughness and cutting force was investigated. Results showed that there was no clear ductile-brittle transition in machining behavior. The material removal mechanism involves falling of the SiC grains and intergranular microfractures of the bonding silicon, which prevents from large-scale cleavage fractures. The minimum surface roughness depends on the initial material microstructure in terms of sizes of the SiC grains and micro pores. This work preliminarily indicates that SPDT can be used as a high-efficiency machining process for RB-SiC.

Influence of Solid Contaminants in Metal Working Fluids on the Grinding Process

2013 ◽  
Vol 769 ◽  
pp. 61-68 ◽  
Author(s):  
Björn Beekhuis
Keyword(s):  
Machine Tool ◽  
Surface Quality ◽  
Solid Particles ◽  
Machining Process ◽  
Depth Of Cut ◽  
Grinding Wheel ◽  
Metal Working ◽  
Machined Surface ◽  
Working Fluids ◽  
Abrasive Particles

Metal working fluids (MWF) are widely used in grinding processes to lubricate and to remove the heat and chips from the contact zone. Apart from the chips, abrasive particles from the worn grinding wheel contaminate the metalworking fluid. The solid contaminants, in particular the abrasive particles crumbled from the grinding wheel, are believed to cause several negative effects like for example damaging the guideways of the machine tool. Furthermore, it is assumed that a pronounced interaction of the solid particles and the machined surface will decrease the achievable surface quality of the ground surfaces. Cleaning units are employed within the fluid circuit to prevent failure of the machine tool and to ensure the desired surface quality. The economic efficiency of such cleaning plants cleaning plants depends strongly on the choice of the grade of filtration (the particle size which has to be retained). A grade of filtration which exceeds the actual needs of the machining process adds unnecessary costs for operating the cleaning unit. To enable cost efficient design of filtration units the interaction between solid contaminants and the machining process has to be understood. The results of grinding experiments (face grinding of workpieces made of AISI 52100) confirm a significant increase of the surface waviness when corundum particles are added to the MWF. The underlying effect is an extraordinary tool wear combined with a locally varying effective depth of cut. The excess particles block the pores of the grinding wheel and are transported into the grinding gap. An increasing ratio of the size of solid contaminants and the size of the bonded grains on the wheel accelerates the wear of the tool.

scholarly journals An Efficient Ultraprecision Machining System Automating Setting Operations of Roughly Machined Workpiece

2021 ◽  
Vol 5 (1) ◽  
pp. 11
Author(s):  
Meng Xu ◽  
Keiichi Nakamoto ◽  
Yoshimi Takeuchi
Keyword(s):  
Machine Tool ◽  
Machine Tools ◽  
High Efficiency ◽  
Industrial Robot ◽  
Numerical Control ◽  
Machining Process ◽  
Machining Accuracy ◽  
Ultraprecision Machining ◽  
Target Shape ◽  
Machining System

Ultraprecision machining is required in many advanced fields. To create precise parts for realizing their high performance, the whole machining process is usually conducted on the same ultraprecision machine tool to avoid setting errors by reducing setting operations. However, feed rate is relatively slow and machining efficiency is not so high compared to ordinary machine tools. Thus, the study aims to develop an efficient ultraprecision machining system including an industrial robot to avoid manual setting and to automate the setting operations. In this system, ultraprecision machining is conducted for the workpiece having a shape near the target shape, which is beforehand prepared by ordinary machine tools and is located on the machine table by means of an industrial robot. Since the setting errors of the roughly machined workpiece deteriorate machining accuracy, the differences from the ideal position and attitude are detected with a contact type of on-machine measurement device. Numerical control (NC) data is finally modified to compensate the identified workpiece setting errors to machine the target shape on an ultraprecision machine tool. From the experimental results, it is confirmed that the proposed system has the possibility to reduce time required in ultraprecision machining to create precise parts with high efficiency.

Comparison of Optimum Cutting Parameters for AISI1042 in Turning Operation by Genetic Algorithm and Particle Swarm Optimization

2015 ◽  
Vol 813-814 ◽  
pp. 285-292 ◽  
Author(s):  
A. Hemantha Kumar ◽  
G. Subba Rao ◽  
T. Rajmohan
Keyword(s):  
Surface Finish ◽  
Metal Cutting ◽  
Cutting Parameters ◽  
Output Parameter ◽  
Machining Process ◽  
Depth Of Cut ◽  
Optimum Level ◽  
Skilled Operator ◽  
Optimal Cutting Parameters ◽  
Selection Of

In metal cutting surface finish is a crucial output parameter in determining the quality of the product. Good surface finish not only assures quality, but also reduces manufacturing cost. Surface finish is an important parameter in terms of tolerances, it reduces assembly time and avoids the need for secondary operation, thus reduces operation time and leads to overall cost reduction. It is very important to select optimum parameters in metal operations. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The main aim of the present work is to build a model to solve real world optimization problems in manufacturing processes.The selection of optimal cutting parameters are speed, feed and depth of cut. are important for all machining process. Experiments have been designed using Taguchi technique, dry and single pass turning of AISI No. 1042 (EN-41B) steel with cermet insert tool performed on PSG A141 lathe. By using signal to noise (S/N) ratio and Analysis of variance (ANOVA) are performed to find the optimum level and percentage of contribution of each parameter. A mathematical model is developed using regression analysis for surface roughness and the model is validated.Moreover, the proposed algorithm, namely GA and PSO were utilized to optimize the output parameter Rain terms of cutting speed, feed and depth of cut by using MATLAB.

Optimization of Cutting Parameters and Burrs Control with PMMA Coating in Micro-Milling Titanium Alloys

2016 ◽  
Vol 836-837 ◽  
pp. 191-197 ◽  
Author(s):  
Yu Chao Li ◽  
Zhan Qiang Liu ◽  
Yu Kui Cai ◽  
Zhao Jun Kou
Keyword(s):  
Titanium Alloy ◽  
Cutting Parameters ◽  
Optical Microscope ◽  
Machining Process ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Machined Surface ◽  
Workpiece Surface ◽  
Coating Method ◽  
Optimization Of Cutting Parameters

Fabrication of microchannels on titanium alloy with micro-milling is a tough challenge due to the difficultly to remove the burrs formed in machining process. A novel method to gelatinize workpiece surface to control the generation of burr as well as the optimization of cutting parameters are investigated in this paper. Differences existed between the process of micro-milling and that of traditional milling can be accounted for size effect. Influences of feed per tooth, depth of cut and spindle speed on the formation of burr were taken into consideration respectively by single factor method. The topographies of the machined surface with micro-milling were observed and measured by optical microscope. Results showed that the dimensions of burrs increased with the rise of depth of cut. However, it decreased initially, then increased later with the augment of feed per tooth. Sacrifice layer with PMMA was coated and gelatinized on the workpiece surface, which could restrain the plastic deformation of materials during titanium alloy micro-milling. The experimental results presented that the dimensions of burr could reduce greatly by the proposed PMMA coating method compared to materials without coating.

Optimal Selection of Machining Parameters by Genetic Algorithms for Face-Milling Operations Based on Minimum Unit Machining Time

2012 ◽  
Vol 602-604 ◽  
pp. 1989-1992 ◽  
Author(s):  
Pei Qing Yang ◽  
Li Bao An
Keyword(s):  
Face Milling ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Time ◽  
Milling Operations ◽  
Tool Replacement ◽  
Optimal Values ◽  
Cutting Speeds ◽  
Selection Of

In this paper, the parameter optimization problem for face-milling operations is studied. A mathematical model is developed in order to minimize unit machining time. The machining process needs one finishing pass and at least one roughing pass depending on the total depth of cut. Maximum and minimum allowable cutting speeds, feed rates and depths of cut, as well as tool life, surface roughness, cutting force and cutting power consumption are constraints of the model. Optimal values of machining parameters are found by a genetic algorithm (GA). The influence of tool replacement time and GA operators is evaluated.

Measuring Points Selection for Laser Tracker Measurement of Five-Axis Machine Tool

2018 ◽  
Author(s):  
Qingzhao Li ◽  
Wei Wang ◽  
Hai Li ◽  
Jing Zhang ◽  
Zhong Jiang
Keyword(s):  
Machine Tool ◽  
High Efficiency ◽  
Optimization Criterion ◽  
Measurement Scale ◽  
Laser Tracker ◽  
Large Measurement ◽  
Measurement Efficiency ◽  
Five Axis ◽  
Selection Of

Due to the advantages of high efficiency, good flexibility and large measurement scale, the laser tracker measurement method is widely used in the error measurement of the machine tool. For the laser tracker measurement, the selection of the measuring points in the workspace has a significant influence on the identification effect of the errors. In this paper, the method to select the optimal measuring points is proposed. By construction of the suitable error vector and its corresponding error transformation matrix, the optimization criterion in robotic area is adopted to evaluate the identification effect of the measuring points. Based on the optimization criterion, the scheme of the measuring points selection can be established. The method proposed is validated by a case study. The method can help increase both the measurement efficiency and the error identification effect.

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