Smart Machining Process Monitoring Enabled by Contextualized Process Profiles for Synchronization

2020 ◽  
Vol 4 (2) ◽  
pp. 20190040
Author(s):  
Zhigang Wang ◽  
Timothy C. Wagner ◽  
Changsheng Guo
Keyword(s):  
Process Monitoring ◽  
Machining Process ◽  
Smart Machining

Method for Evaluating Machining Toolholder-Spindle Unbalance Due to Chips at the Toolholder Interface

2010 ◽  
Author(s):  
John Agapiou
Keyword(s):  
Real Time ◽  
Process Monitoring ◽  
Diagnostic System ◽  
Machining Process ◽  
Monitoring Method ◽  
Spindle System ◽  
On Line

Machining process monitoring method is developed for detecting and diagnosis of the presence of chips at the toolholder-spindle interface. Although toolholders can be simply balanced before they are placed in the spindle, there can be some balancing problems remaining when one or more loose machining chips are attached at the toolholder-spindle interface(s) during a tool change. A method is developed by considering the natural and geometric unbalances of the toolholder-spindle system combined with an analysis of the toolholder tilt due to the presence of loose machining chips around the spindle. The method can be integrated on-line as a real-time expert diagnostic system for toolholder tilt due to the presence of loose machining chips at the spindle nose. The expert diagnostic system makes intelligent decisions on toolholder unbalance and concerns with chips at the interface that result in unwanted tilting and vibrations. The tool unbalance algorithm was able to monitor the toolholder tilting according to the results of this study.

Machining process monitoring with vibration signal based manifold learning

2020 ◽  
Vol 148 (4) ◽  
pp. 2766-2766
Author(s):  
Jing Wang ◽  
Mingxin Hui ◽  
Bin Liu ◽  
Xun Wang ◽  
Xiaobin Cheng ◽  
...  
Keyword(s):  
Process Monitoring ◽  
Manifold Learning ◽  
Vibration Signal ◽  
Machining Process

scholarly journals Development of smart machining system for optimizing feedrates to minimize machining time

2017 ◽  
Vol 5 (3) ◽  
pp. 299-304 ◽  
Author(s):  
Hong-seok Park ◽  
Bowen Qi ◽  
Duck-Viet Dang ◽  
Dae Yu Park
Keyword(s):  
Cutting Force ◽  
Machining Process ◽  
Cnc Machine ◽  
Machining Time ◽  
Virtual Machining ◽  
Milling Operations ◽  
Nc Program ◽  
Machining System ◽  
Optimal Feed ◽  
Smart Machining

Abstract Feedrate optimization is an important aspect of getting shorter machining time and increase the potential of efficient machining. This paper presents an autonomous machining system and optimization strategies to predict and improve the performance of milling operations. The machining process was simulated and analyzed in virtual machining framework to extract cutter-workpiece engagement conditions. Cutting force along the cutting segmentation is evaluated based on the laws of mechanics of milling. In simulation, constraint-based optimization scheme was used to maximize the cutting force by calculating acceptable feedrate levels as the optimizing strategy. The intelligent algorithm was integrated into autonomous machining system to modify NC program to accommodate these new feedrates values. The experiment using optimized NC file which generates by our smart machining system were conducted. The result showed autonomous machining system, was effectively reduced 26%. Highlights The smart machining system was implemented in the CNC machine. Optimal feed rates enhance machine tool efficiency. The smart machining system is reliable to reduce machine time.

Milling Process Monitoring Based on Vibration Analysis Using Hilbert-Huang Transform

2018 ◽  
Vol 12 (5) ◽  
pp. 688-698 ◽  
Author(s):  
Agus Susanto ◽  
Chia-Hung Liu ◽  
Keiji Yamada ◽  
Yean-Ren Hwang ◽  
Ryutaro Tanaka ◽  
...  
Keyword(s):  
Signal Processing ◽  
Feature Extraction ◽  
Process Monitoring ◽  
Signal Analysis ◽  
Vibration Analysis ◽  
Milling Process ◽  
Machining Process ◽  
Hilbert Huang Transform ◽  
Thin Walled ◽  
Tool Damage

Vibration analysis is one method of machining process monitoring. The vibration obtained in machining is often nonlinear and of a nonstationary nature. Therefore, an appropriate signal analysis is needed for signal processing and feature extraction. In this research, vibrations obtained in the milling of thin-walled workpieces were analyzed using the Hilbert-Huang transform (HHT). The features obtained by the HHT served as machining-state indicators for machining process monitoring. Experimental results showed the effectiveness of the HHT method for detecting chatter and tool damage.

In-Process Monitoring of the Machining State in Superfinishing by Measuring the Dynamic Machining Forces

2016 ◽  
Vol 1136 ◽  
pp. 592-596
Author(s):  
Takashi Onishi ◽  
Kazuhito Ohashi ◽  
Kohei Higashi ◽  
Yohei Morinaka ◽  
Shinichi Banno ◽  
...  
Keyword(s):  
Process Monitoring ◽  
Machining Process ◽  
Dynamic Component ◽  
Machining Forces ◽  
Sliding Surfaces ◽  
Machining Conditions ◽  
Machining Force ◽  
Finished Surface ◽  
The Relationship

Superfinishing is widely used as a final finishing method for sliding surfaces of bearings. In superfinishing, a fine finished surface can be obtained by transiting the machining states from the cutting action to the finishing one as the tool loading is encouraged. To obtain good machining conditions, it is necessary to judge the transition of the machining state reliably. However, it is difficult to judge the transition of the machining states. In this study, we focused on the change of the dynamic component of the machining force, which was applied to the oscillation direction of the superfinishing stone, during machining process. With machining experiments, the relationship between the declination of the dynamic machining force and the transition of the machining state was confirmed.

scholarly journals Machining process monitoring and application: a review

2021 ◽  
Vol 1 (1) ◽  
pp. 1-10
Author(s):  
Wuyang SUN ◽  
Dinghua ZHANG ◽  
Ming LUO
Keyword(s):  
Process Monitoring ◽  
Machining Process

Mini Special Issue on Machining Control and Process Monitoring

2014 ◽  
Vol 8 (6) ◽  
pp. 791-791
Author(s):  
Tojiro Aoyama
Keyword(s):  
Machine Tool ◽  
Process Monitoring ◽  
Machine Tools ◽  
Cutting Tools ◽  
Machining Process ◽  
Machining Accuracy ◽  
Special Issue ◽  
Practical Proposal ◽  
Machining Control ◽  
Novel Approaches

Control and process monitoring are key technologies supporting high machining accuracy and efficiency. This special issue features six papers taking novel approaches to controlling machine and cutting tools and monitoring the machining process. The motion control of machine tools and cutting tools are introduced. A new challenge for monitoring the machining process by referring to NC control servo signals implements a practical proposal. The precise identification of friction at driving elements of machine tool components is an important factor in improving machine tool control motion accuracy. I would like to express my sincere appreciation to the authors and reviewers whose invaluable efforts have helped make the publication of this manuscript possible.

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