Development of an Intelligent Stage with Sensor-Less Cutting Force and Torque Monitoring Function

2012 ◽  
Vol 6 (6) ◽  
pp. 736-741 ◽  
Author(s):  
Takafumi Kamigochi ◽  
◽  
Yasuhiro Kakinuma ◽  
Keyword(s):  
Tool Wear ◽  
Machine Tool ◽  
Cutting Force ◽  
Process Monitoring ◽  
Good Condition ◽  
Basic Information ◽  
Monitoring Method ◽  
Intelligent Machine

Intelligent machine tool is required to implement highprecision process monitoring for judging the abnormal tool conditions. Various techniques have been widely researched and studied to maintain machine tool in good condition and to detect tool wear. The occurrence of tool wear can be detected by monitoring the cutting torque, which is basic information for machining. The purpose of this study was to propose a sensor-less cutting force and torque monitoring method and to develop an intelligent stage using this method.

Simulation Technologies for the Development of an Autonomous and Intelligent Machine Tool

2013 ◽  
Vol 7 (1) ◽  
pp. 6-15 ◽  
Author(s):  
Keiichi Shirase ◽  
◽  
Keiichi Nakamoto ◽  
Keyword(s):  
Fault Detection ◽  
Machine Tool ◽  
Cutting Force ◽  
Milling Process ◽  
Planning System ◽  
Cutting Force Prediction ◽  
Intelligent Machine ◽  
Milling Operation ◽  
Digital Copy ◽  
Copy Milling

An autonomous and intelligent machine tool have been developed to solve fundamental issues with the current command method using NC programs, and simulation technologies for its realization have been introduced. The process planning system introduced here, various process plans can be created, and the best process plan can be selected to achieve flexible machining operations in accordance with changes in production planning. Digital Copy Milling, digitizing the principle of copy milling, has opened up new possibilities for machine tool control. The NC machine tool can be directly controlled with the 3D CAD data of the product shape in Digital CopyMilling. Direct machining without the need to create an NC program before milling operation, adaptive control which changes the cutting conditions in accordance with the cutting load during milling operation, and fault detection in the cutting load and avoiding tool breakages can be performed through Digital Copy Milling. Themilling process simulator with integrated milling shape simulator and cutting force simulator provides new functions. Simultaneous cutting force prediction with milling operation provides the possibility of milling process control and fault detection by comparing the measured cutting force with the predicted one.

Development of Innovative Intelligent Machine Tool Based on CAM-CNC Integration Concept – Adaptive Control Based on Predicted Cutting Force –

2019 ◽  
Vol 13 (3) ◽  
pp. 373-381
Author(s):  
Isamu Nishida ◽  
Ryo Tsuyama ◽  
Keiichi Shirase ◽  
Masahiro Onishi ◽  
Katsuyuki Koarashi ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Machine Tool ◽  
Cutting Force ◽  
Real Time ◽  
Machining Efficiency ◽  
Intelligent Machine ◽  
Computer Aided ◽  
Machine Control ◽  
Digital Copy ◽  
Copy Milling

A new methodology to generate instruction commands for prompt machine control as a replacement for the previously prepared numerical control (NC) programs is developed to realize an innovative intelligent machine tool. This machine tool can eliminate NC program preparation, achieve cutting process control, reduce the production lead time, and realize an autonomous distributed factory. In this study, the innovative intelligent machine tool based on the computer-aided manufacturing-computer NC integrated concept is developed. The special feature of this system is to generate instruction commands in real time for prompt machine control instead of using NC programs. Digital Copy Milling, which is a digitized version of traditional copy milling, is realized by using only the computer-aided design model of the product. In this system, the cutting-force simulation is performed simultaneously with the real-time tool path generation. Then, the tool feed rate can be controlled according to the predicted cutting force. Therefore, both the improvement of the machining efficiency and the avoidance of machining problems can be achieved. The instantaneous cutting force model predicts the cutting force. In this system, the work material is represented by the voxel model, and the uncut chip thickness is calculated discretely from the number of voxels removed. Thus, it is possible to predict the cutting force in the case of non-uniform contact between the tool and the work material. In this study, a machining simulation is conducted to validate the proposed method. The results of the simulation show successful tool feed speed adaptation based on the predicted cutting force. The results also show the effective reduction of the machining time. A case study of a custom-made product for dental prosthetics is examined as a good application of both the proposed adaptive control and the Digital Copy Milling system. Through this method, it is possible to improve the machining efficiency and prevent tool breakage.

scholarly journals Indirect Monitoring Method of Tool Wear using the Analysis of Cutting Force during Dry Machining of Ti Alloys

2017 ◽  
Vol 13 ◽  
pp. 623-630 ◽  
Author(s):  
Y. Sanchez ◽  
F.J. Trujillo ◽  
L. Sevilla ◽  
M. Marcos
Keyword(s):  
Tool Wear ◽  
Cutting Force ◽  
Dry Machining ◽  
Monitoring Method ◽  
Ti Alloys

scholarly journals The Use of Machine Tool Internal Encoders as Sensors in a Process Monitoring System

2013 ◽  
Vol 7 (4) ◽  
pp. 410-417 ◽  
Author(s):  
Tomas Beno ◽  
◽  
Jari Repo ◽  
Lars Pejryd ◽  
Keyword(s):  
Tool Wear ◽  
Machine Tool ◽  
Process Monitoring ◽  
Low Frequency ◽  
Machining Process ◽  
Process Conditions ◽  
Monitoring And Control ◽  
Signal Features ◽  
Process Monitoring And Control ◽  
Cutting Force Components

Tool wear in machining changes the geometry of the cutting edges, which affects the direction and amplitudes of the cutting force components and the dynamics in the machining process. These changes in the forces and dynamics are picked up by the internal encoders and thus can be used for monitoring of changes in process conditions. This paper presents an approach for the monitoring of amulti-toothmilling process. The method is based on the direct measurement of the output from the position encoders available in the machine tool and the application of advanced signal analysis methods. The paper investigates repeatability of the developed method and discusses how to implement this in a process monitoring and control system. The results of this work show that various signal features which are correlated with tool wear can be extracted from the first few oscillating components, representing the low-frequency components, of the machine axes velocity signatures. The responses from the position encoders exhibit good repeatability, especially short term repeatability while the long-term repeatability is more unreliable.

scholarly journals Identification of eccentricity for disc milling cutter of indexable two sided inserts

2021 ◽  
Vol 13 (8) ◽  
pp. 168781402110414
Author(s):  
Gensheng Li ◽  
Chao Xian ◽  
Hongmin Xin
Keyword(s):  
Tool Wear ◽  
Machine Tool ◽  
Cutting Force ◽  
Cutting Forces ◽  
Theoretical Method ◽  
Force Model ◽  
Cutting Force Model ◽  
Milling Cutter ◽  
Machining Quality ◽  
Operation Status

Tool eccentricity has a significant impact on machining quality, accuracy, and operation status of machine tool. It is difficult to accurately identify tool eccentricity. In this paper, the mathematical models of instantaneous undeformed cutting thickness and cutting force considering tool eccentricity are determined by theoretical method. Based on the model, the identification method for eccentricity parameters is proposed, and the eccentricity parameters of disc milling cutter is identified. According to the identified parameters, the cutting force is verified. The results show that most of the values of measured cutting forces are greater than the predicted ones considering tool eccentricity. In the future, it is necessary to establish a new cutting force model considering both tool eccentricity and tool wear.

Research on Spindle and Machining Process Monitoring for Intelligent Machine Tools(Advanced machine tool)

2005 ◽  
Vol 2005.2 (0) ◽  
pp. 469-474 ◽  
Author(s):  
Atsushi MATSUBARA ◽  
Motoyuki SUGIHARA ◽  
Ahmed A. D. SARHAN ◽  
Hidenori SARAIE ◽  
Soichi IBARAKI ◽  
...  
Keyword(s):  
Machine Tool ◽  
Process Monitoring ◽  
Machine Tools ◽  
Machining Process ◽  
Intelligent Machine

scholarly journals Feeling Machine for Process Monitoring of Components with Stock Allowance

Machines ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 53
Author(s):  
Berend Denkena ◽  
Benjamin Bergmann ◽  
Matthias Witt
Keyword(s):  
Machine Tool ◽  
Cutting Force ◽  
Process Monitoring ◽  
Process Quality ◽  
Signal Source ◽  
Confidence Limits ◽  
Specific Cutting Force ◽  
First Time ◽  
Critical Process ◽  
Production Conditions

To realize the increasing automation and flexibilization of production, it is necessary to monitor component-specific characteristics under fluctuating production conditions. Signals with a high correlation to the process quality have to be evaluated. In machining, the process force is an important measurand, which is sensitive to changes in the process. Feeling machines with force-sensitive machine tool components are therefore a promising signal source to monitor the machining. However, the force is also sensitive to non-critical process fluctuations such as stock allowance. Consequently, it is necessary to perform signal pre-processing and generate features that increase the robustness of the monitoring. In this paper, the material-specific cutting force was investigated for the first time concerning its suitability for process monitoring of parts with a stock allowance. The sensitivity of confidence limits was evaluated based on the normed bandgap. For the investigation, face turning processes of 20MnCr5 were carried out. The results show that the use of material-specific cutting force improves the sensitivity of the confidence limits to process errors. In this context, the feeling machine can be used to substitute the dynamometer for process monitoring.

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