• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.6
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• pp.1-6
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• 2015

Tool condition monitoring plays one of the most important roles in the improvement of both machining quality and productivity. In this regard, various process signals and monitoring methods have been developed. However, most of the existing studies used cutting force or acoustic emission signals, which posed risks of interference with the machining system in dynamics, fixturing, and machining configuration. In this study, a feed motor current signal is used as a process signal representing process and tool states in tool breakage monitoring based on an adaptive autoregressive model and unsupervised neural network. From the experimental results using various cases of tool breakage, it is shown that the developed system can successfully detect tool breakage before two revolutions of the spindle after tool breakage.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.12
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• pp.94-100
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• 2000

This paper presents a methodology for In-Process monitoring of tool wear by using ultrasonic sensor in turning operation. An integrated single ultrasonic transducer operation at a frequency of 10MHz is placed in contact with the insert tip. The change in amount of the reflected energy from the nose and flank of the tool can be related to the level of tool wear and the mechanical integrity of the tool. As the results, the tool wear monitoring system based on the ultrasonic pulse-echo method was proposed, it is useful to determine a tool life and tool change time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.311-315
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• 2000

In thls paper, a remote machine monitoring system for a vimal machine is proposed. The monltonng system is one of the core functmns of a vimd machne that provides a modeling and simulation environment for machining processes and management of the machine life cycle. The proposed system contains the modules for investigating tool wear using neural network and web-based real time process monitoring. An example implementation for tool wear and machining status monitoring is illustrated

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.3
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• pp.254-262
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• 2008

The objective of the proposed study is to produce a tool-condition monitoring (TCM) strategy that will lead to a more efficient and economical drilling tool usage. Drill-wear monitoring is an important attribute in the automatic cutting processes as it can help preventing damages of the tools and workpieces and optimizing the tool usage. This study presents the architectures of a multi-layer feed-forward neural network with back-propagation training algorithm for the monitoring of drill wear. The input features to the neural networks were extracted from the AE signals using the wavelet transform analysis. Training and testing were performed under a moderate range of cutting conditions in the dry drilling of steel plates. The results indicated that the extracted input features from AE signals to the supervised neural networks were effective for drill wear monitoring and the output of the neural networks could be utilized for the tool life management planning.

• Transactions of Materials Processing
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• v.18 no.2
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• pp.144-149
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• 2009

Recently, the monitoring technology of machining process is very important to improve productivity and quality in manufacturing filed. Such monitoring technology has been performed to measurement using vibration signal, acoustic emission signal and tool dynamometer. However, micro machining is limited small-scale parts machining because micro tool is very small and weakness to generate signal in micro machining process. Therefore, this study has efficient sensing technology for real monitoring system in micro machine that is proposed to supplement a disadvantage of single-sensor by multi sensor. From experimental result, it was evaluated tool wear and cutting situation according to repetitive slot cutting condition and changing cutting condition, and it was performed monitoring spindle rpm and condition according to compare acceleration signal with current signal.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.60-63
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• 1997

Recently, factory automation and shop floor control system need a web based remote monitoring technology to control effectively machine tool. This paper describes a web based remote monitoring system which is concerned with open architecture controller for machine tool. The environment of this system consists of a lot of elements such as web server, database, machine tool, pc based controller, client computers and script programs, also which is interconnected by network including intranet or internet. Designed script programs, also which is interconnected by network including intranet or internet. Designed script program service current status and faults information of machine to remote users who want to monitor machine tool. Additionally those have various functions to service we board for q&a, downloading data and information of after-service managers.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.3
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• pp.36-43
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• 1997

In order to make unmanned machining systems with satisfactory performances, it is necessary to incorporate appropriate condition monitoring systems in the machining workstations to provide the required intelligence of the expert. This paper deals with condition monitoring for tool wear and breakage during turning operation. Developing economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique are proposed. The validity of the proposed system is confirmed through the large number of cutting tests.

• Tribology and Lubricants
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• v.28 no.3
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• pp.130-135
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• 2012

This study presents a new methodology for realtime tool breakage detection by sensor fusion concept of two hall sensor and an acoustic emission (AE) sensor. Spindle induction motor torque of CNC Lathe during machining is estimated by two hall sensor. Estimated motor torque instead of a tool dynamometer was used to measure the cutting torque and tool breakage detection. A burst of AE signal was used as a triggering signal to inspect the cutting torque. A significant drop of cutting torque was utilized to detect tool breakage. The algorithm was implemented on a NI DAQ (Data Acquisition) board for in-process tool breakage detection. The result of experiment showed an excellent monitoring capability of the proposed tool breakage detection system. This system is available tool breakage monitoring through internet also provides this system's user with current cutting torque of induction motor.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.1
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• pp.27-37
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• 1993

In unmanned machining, One of the most essential issue is the tool management system which includes controlling. identification, presetting and monitoring of cutting tools. Especially the monitoring of tool wear and fracture may be the heart of the system. In this study a computer vision based tool monitoring system is developed. Also an algorithm which can determine the tool condition using this system is presented. In order to enhance practical adaptability the vision system through which two modes of images are taken is located over the rake face of a tool insert. And they are analysed quantitatively and qualitatively with image processing technique. In fact the morphologies of tool fracture or wear are occurred so variously that it is difficult to predict them. For the purpose of this problem the pattern recognition is introduced to classify the modes of the tool such as fracture, crater, chipping and flank wear. The experimental results performed in the CNC turning machine have proved the effectiveness of the proposed system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1066-1069
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• 2004

Recently the monitoring system of tool setup in high speed precision machining tool is required for manufacturing products that have highly complex and small shape, high precision and high function. It is very important to reduce time to setup tool in order to improve the machining precision and productivity and to protect the breakage of cutting tool as the shape of product is smaller and more complex. Generally, the combination of errors that geometrical clamping error of fixing tool at the spindle of machining center and the asynchronized error of driving mechanism causes that the run-out of tool reaches to 3∼20 times of the thickness of cutting chip. And also the run-out is occurred by the misalignment between axis of tool shank and axis of spindle and spindle bearing in high speed rotation. Generally, high speed machining is considered when the rotating speed is more than 8,000 rpm. At that time, the life time of tool is reduced to about 50％ and the roughness of machining surface is worse as the run-out is increased to 10 micron. The life time of tool could be increased by making monitoring of tool-setting easy, quick and precise in high speed machining center. This means the consumption of tool is much more reduced. And also it reduces the manufacturing cost and increases the productivity by reducing the tool-setup time of operator. In this study, in order to establish the concept of tool-setting monitoring the measuring method of the geometrical error of tool system is studied when the spindle is stopped. And also the measuring method of run-out, dynamic error of tool system, is studied when the spindle is rotated in 8,000 ∼ 60,000 rpm. The dynamic phenomena of tool-setup is analyzed by implementing the monitoring system of rotating tool system and the noncontact measuring system of micro displacement in high speed.