• Title/Summary/Keyword: tool breakage

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Development of Coil Breakage Prediction Model In Cold Rolling Mill

  • Park, Yeong-Bok;Hwang, Hwa-Won
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1343-1346
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    • 2005
  • In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).

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A Study on the System Identification of Tool Breakage Detection in Turning (선삭가공에서 공구파손 검출 시스템 인식에 관한 연구)

  • 사승윤
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1999.10a
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    • pp.40-45
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    • 1999
  • The demands for robotic and automatic system are continually increasing in manufacturing fields. There have been many studies to monitor and predict the system, but they have mainly focused upon measuring cutting force, and current of motor spindle, and upon using acoustic sensor, etc.In this study, time series sequence of cutting force was acquired by taking advantage of piezoelectric type tool dynamometer. Radial cutting force was obtained from it and was available for useful observation data. The parameter was estimated using PAA (parameter adaptation algorithm) from observation data. ARMA(auto regressive moving average) model was selected for system model and second order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter.

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A Study of Tool Breakage Dection Using AE Sensor (AE(acoustic emission)센서를 이용한 공구파손검출에 관한 연구)

  • Lee, Jae-Jong;Song, Jun-Yeop;Park, Hwa-Yeong
    • 한국기계연구소 소보
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    • s.19
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    • pp.61-68
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    • 1989
  • As the system monitoring technology become required in order to improve the system performance and the productivity, we’ve studied to the detection for the tool wear and the tool breakage using AE sensors that is able to detection of generated high frequency stress pulse at cutting. The detection system is consist of a sensing part, a amplifier part, a signal processing part, and a analysis & output part. The moment (a rms and a kurtosis) of statistical method is used for analysis of AE singnal. The experiment are carried out in a CNC lathe. In this study, we achieved that the amplitude level of the AE signal and statistical moments was largely changed as the tool failure. The change rate of Kurtosis was especially large, but the change rate of the rms was small.

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Breakage Detection of Small-Diameter Tap Using Vision System in High-Speed Tapping Machine with Open Architecture Controller

  • Lee, Don-Jin;Kim, Sun-Ho;Ahn, Jung-Hwan
    • Journal of Mechanical Science and Technology
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    • v.18 no.7
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    • pp.1055-1061
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    • 2004
  • In this research, a vision system for detecting breakages of small-diameter taps, which are rarely detected by the indirect in-process monitoring methods such as acoustic emission, cutting torque and motor current, was developed. Two HMI (Human Machine Interface) programs to embed the developed vision system into a Siemens open architecture controller, 840D, were developed. They are placed in sub-windows of the main window of the 840D and can be activated or deactivated either by a softkey on the operating panel or the M code in the NC part program. In the event that any type of tool breakage is detected, the HMI program issues a command for an automatic tool change or sends an alarm signal to the NC kernel. An evaluation test in a high-speed tapping machine showed that the developed vision system was successful in detecting breakages of small-diameter taps up to M1.

The Mechanism and Detection of Tool Fracture using Sensor Fusion in Cutting Force and AE Signals for Small Diameter Ball-end Milling (미세 볼엔드밀가공시 절삭력과 음향방출신호에 의한 공구 파손 검출 및 메커니즘)

  • Wang, Duck-Hyun;Kim, Won-Il;Lim, Jeong-Suk
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.3 no.3
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    • pp.24-31
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    • 2004
  • A successful on-line monitoring system for conventional machining operations has the potential to reduce cost, guarantee consistency of product quality, improve productivity and provide a safer environment for the operator. In fine-shape machining, typical signs of tool problems such as vibration, noise, chip flow characteristics and visual signs are almost unnoticeable without the use of special equipment. These characteristics increase the importance of automatic monitoring in fine-shape machining, however, sensing and interpretation of signals ar more complex. In addition, the shafts of the mini-tools break before the typical extensive cutting edge of the tool gets damaged. In this study, the existence of a relationship between the characteristics of the cutting force and tool usage was investigated, and tool breakage detection algorithm by LabVIEW was developed and the following results are obtained. It was possible to use a relative error compare which mainly used in established experiment and investigated tool breakage detection algorithm in time domain which can detect AE and cutting force signals more effective and accurate.

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A Study on the System Identification for Detection of Tool Breakage (공구파손검출을 위한 시스템인식에 관한 연구)

  • 사승윤
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.9 no.5
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    • pp.144-149
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    • 2000
  • The demands for robotic and automatic system are continually increasing in manufacturing fields. There have been many studies to monitor and predict the system, but they have mainly focused upon measuring cutting force, and current of motor spindle, and upon using acoustic sensor, etc. In this study, time series sequence of cutting force was acquired by taking advantage of piezoelectric type tool dynamometer. Radial cutting force was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. ARMA(auto regressive moving average) model was selected for system model and second order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter.

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SPC 기법에 의한 밀링공구의 파손분석 및 검색

  • 서석환;전치혁;최용종
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1992.10a
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    • pp.47-51
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    • 1992
  • Automatic detection of tool breakage during NC machining is a key issue not only for improving productivity but to implement the unattended manufacturing system. In this paper, we develop a vibration sensor-based tool breakage detection system for NC milling processes. The system obtains the time-domain vibration signal from the sensor attached on the spindle bracket of our CNC machine and declares tool failures through the on-line monitoring schemes. For on-line detection, our approach is to use the PSC(statistical process control) methods being increasingly used for on-line process control. The main thrust of this paper is to propose and compare the performance of SPC methods including : a) X-bar control scheme, b) S control scheme, c)EWMA (exponentially weighted moving average) scheme, and d) AEWMA (adaptive exponentially weighted moving average) scheme. The performance of the control schemes are compared in terms of the type 1 and 2 error calculated from the experiment data.

A Study on Real Time Monitoring of Tool Breakage in Milling Operation Using a DSP (DSP를 이용한 정면 밀링공구의 실시간 파단 감시방법에 관한 연구)

  • Baek, Dae-Kyun;Ko, Tae-Jo;Kim, Hee-Sool
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.6
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    • pp.168-176
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    • 1996
  • A diagnosis system which can monitor tool breakage and chipping in real time was developed using a DSP(Digital Signal Processor) board in face milling operation. AR modelling and band energy method were used to extract the feature of tool states from cutting force signals. Artificial neural network embedded on DSP board discriminates different patterns from features got after signal processing. The features extracted from AR modelling are more accurate for the malfunction of a process than those from band energy method, even though the computing speed of the former is slow. From the processed features, we can construct the real time diagnosis system which monitors malfunction by using a DSP board having a parallel processing capability.

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Monitoring of Tool Wear Condition by Cutting Resistance and AE Signal in Drilling ADI Material. (ADI재의 드릴가공시 절삭저항 및 AE신호에 의한 공구마멸상해의 검출)

  • 유경곤;전태옥;박홍식
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.11
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    • pp.32-38
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    • 1998
  • For the purpose of monitoring the abnormal state in proportion to cutting in automatic production process, the 3 kinds of specimens different from mechanical properties by austempering through temperature variation were manufactured, and the effects of tool wear on thrust and AE RMS was analyzed with sequential drilling in in-process. When the ADI specimens were drilled, the relationship of thrust and AE RMS with flank wear was studied through experiments, and it is confirmed that the reliable wear state is able to be monitored by using these signals. It was shown that thrust and AE RMS increased slowly till flank wear reached to V$_{B}$ = 0.25mm, and they increased steeply over the value. The effective tool exchange time was able to be pre-estimated by using this fact. It was validated that the tool breakage was able to be detected on the real time by monitoring in in-process.s.

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Development of API module program for automatic tool compensation on machining center (머시닝센터의 자동공구보정을 위한 API모듈용 프로그램개발)

  • 정상화;신현성;김현욱
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.04a
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    • pp.100-105
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    • 2002
  • In general, manufacturing error originated in bad material, machine tool defection, tool defection, and tool breakage. When the manufacturing process is stable, the error is come from the tool wear. In common on-machine measurement, teaching probe and touch sensor are widely used, however in this thesis the automatic tool compensation system using electric touch point measuring system is developed and evaluated, and effective operating is proposed.

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