• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.95-100
• /
• 1995

Automatic monitoring of cutting process is one of the most important technology for increasing the stability and the reliability of unmanned manufacturing system. In this study, basic methods which use the acoustic emission (AE) signals and sutting forces proposed to monitor tool wear (flank wear) quantitatively. Fist, in order to detect flank wear, it was investigated influence of cutting conditions, that is, cutting velocity, feed and depth of cut, on AE signals (AErems) and cutting forces. Furthermore,the relationship flank wear between AErems and cutting forces were discussed.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.7 no.3
• /
• pp.14-21
• /
• 1998

The in-process detection of the state of cutting tool is one of the most important technical problem in Intelligent Machining System. This paper presents a method of detecting the state of cutting tool in turning process, by using Artificial Neural Network. In order to sense the state of cutting tool. the sensor fusion of an acoustic emission sensor and a force sensor is applied in this paper. It is shown that AErms and three directional dynamic mean cutting forces are sensitive to the tool wear. Therefore the six pattern features that is, the four sensory signal features and two cutting conditions are selected for the monitoring system with Artificial Neural Network. The proposed monitoring system shows a good recogniton rate for the different cutting conditions.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2009.06a
• /
• pp.1059-1060
• /
• 2009

• Journal of the Korean Society for Precision Engineering
• /
• v.4 no.3
• /
• pp.60-68
• /
• 1987

An optoelectronical method for in process monitoring of flank wear of cutting tools is presented. The method is based upon real-time vision technology in which the tool is illuminated by a beam of laser and then the image of wear zone is taken by a vidicon camera. The image is converted to a series of digital pixel data and processed through an algorithm specially developed for measurement of the wear land width. Detailed aspects of the prototype measurement system byilt for experiment are described, and test results are discussed. As conclusions, it is proved that the methods are effec- tive especially for-in situ application with a measuring accuracy of 0.01mm.

• Transactions of Materials Processing
• /
• v.31 no.2
• /
• pp.103-108
• /
• 2022

Systematic quality control based on real time data is required for modern factories. This study introduced a method of predicting punch wear in the trimming process of automobile parts. Based on monitoring data of the mass production process using a bolt-type piezo sensor, it was shown that precursor symptoms of die wear could be predicted from the change in load pattern with respect to production volume. The load pattern that changed according to the wear of the die was verified by numerical analysis.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.12 no.3
• /
• pp.8-16
• /
• 2003

Monitoring of the drill wear :md hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work-piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process and provide a relatively easy way to monitor a machining process for industrial application. for this advantage, AE signal is used to estimate the abnormal fate. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so of but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality. As the results of this experiment AE RMS signal and measurements by vision system are shorn the similar tendency as abnormal state of drilling.

• IE interfaces
• /
• v.7 no.3
• /
• pp.155-168
• /
• 1994

In computer integrated manufacturing environment, tool management plays an important role in controlling tool performance for machining operations. Knowledge of tool behavior during the cutting process and effective tool-behavior prediction contribute to controlling machine costs by avioding production delays and off-target parts due to tool failure. The purpose of this paper is to review and develop the tool condition monitoring scheme for drilling operation to assure a fast corrective response to minimize the damage if tool failures occur. If one desires to maximize system through-put and product quality as well as tooling resources, within an economic environment, real-time tool sensing system and information processing system can be coupled to provide the necessary information for the effective tool management. The example is demonstrated as to drilling operation when the aluminum composites are drilled with carbide-tipped HSS drill bits. The example above is limited to the situation that the tool failure mode of drill bits is wear.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.84-87
• /
• 2001

The high speed machining which cam improve the production and quality has been remarkable in die/mold industry with the growth of parts and materials industries. The speed of machine tool increases, but on the other hand, the response of sensors I not being improved. Therefore, the condition monitoring techniques for the machine too, tool and workpiece in high speed machining are incomplete. In this study, characteristics of the tool edge roughness were verified from the high frequency components of cutting force signals acquired by the high speed dynamometer. Also, the experimental evaluation technique for the machinability and condition monitoring in high speed machining was established by analyzing the cutting force, acceleration and surface roughness.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.2 no.3
• /
• pp.13-19
• /
• 2003

The high speed machining technology has been improved remarkably in die/mold industry with the growth of parts and materials industries. Though the spindle speed of machine tool increases, the condition monitoring techniques of the machine tool, tool and workpiece in high speed machining ate incomplete. In tins study, efficient sensing technology in high speed machining is suggested by observing the characteristics of cutting force, gap sensor and accelerometer signal also, machinability of high-speed machining is experimentally evaluated sensing technique to monitor the machine tool and machining conditions was performed.

• Journal of the Korean Society for Precision Engineering
• /
• v.10 no.2
• /
• pp.95-103
• /
• 1993

In the manufacturing field, some traditional manufacturing and machining methods become weakened the productivity, the external competitive power, and accuracies of the products. In these point of view, the unmanned and intelligent manufacturing systems are proposed by some manufacturing companies. The real-time monitoring technology of the cutting tool conditions i.e. tool wear, tool breakage, crack, and chipping anre necessarily reauired to realize those system, especially. In this study, we constructed the multi- sensing system using the acceleration sensor, the current sensor, and the loadmeter of a machine tool. Also, we analyzed the nose breakage, the massive signal, and some monitoring features by means of the developed system.