• 한국정밀공학회지
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• 제17권12호
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• pp.54-60
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• 2000

Research about tool condition monitoring has been done until now for product automation and unmaned system. But it is hard to apply it to the industrial field due to its cost and reliability. This paper presents the new method of tool wear measurement using Marpos gauge. This is a kind of touch sensor, so its cost is lower than vision system. And it is not affected by dust and illumination, which are important in vision system. This proposed method use tool clearance angle to measure flank wear. Experimental results compared with vision system shows that this method is available for tool condition monitoring system.

• 한국기계가공학회지
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• 제2권3호
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• pp.34-40
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• 2003

This paper describes evaluation and monitoring methods of machining characteristics for developed micro grooving machine. Experiments were conducted under various process conditions such as spindle revolution speed, feed rates and depth of groove V and U shape of blade and STD11 were used in this experiment. The status of grooving was evaluated through analysis of the Acoustic emission (AE) signal resulted in each process condition. Based on the analysis, this paper examined the possibility of monitoring adapting fuzzy logic. In conclusion, this paper presented the possibility of monitoring in process adapting AE technology and appropriate micro grooving condition.

• 한국생산제조학회지
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• 제25권6호
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• pp.445-451
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• 2016

The Inconel 718 alloy is a well-known super-heat-resistant alloy and a difficult-to-cut material. Inconel 718 with excellent corrosion and heat resistance is used in harsh environments. However, the heat generated is not released owing to excellent physical properties, making processes (e.g., adhesion and thermal fatigue) difficult. Tool condition monitoring in machining is significant in reducing manufacturing costs. The cutting tool is easily broken and worn because of the material properties of Inconel 718. Therefore, tool management is required to improve tool life and machinability. This study proposes a method of predicting the tool wear with non-contacting sensors (e.g., IR thermometer for measuring the cutting temperature and a microphone for measuring the sound pressure level in machining). The cutting temperature and sound pressure fluctuation according to the tool condition and cutting force are analyzed using experimental data. This experiment verifies the effectiveness of the non-contact measurement signals in tool condition monitoring.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 추계학술대회 논문집
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• pp.411-416
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• 1993

In order to achieve computer-oriented control and automation of manufacturing processec, a distributed NC (DNC_) system was developed for FMS under the Windows environment. The DNC system consists of conventional DNC, PMC interface and tool management modules. Real-time system conditon monitoring and control fuctions required for machine tools and machining processes were accomplished by developing a PMC interface module called MMC board. Tool condition monitoring and management was performed by the developed tool management module composed of a tool setting probe and softwares. Performance of the DNC system was confirmed on the horizontal and the vertical type machining center equipped with FANUC OMC for the large amount of experiments.

• 한국기계가공학회지
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• 제15권4호
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• pp.134-140
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• 2016

Main Spindle System has effect on performance of machine tools and working quality as well as is required of high reliability. Especially, it takes great importance in producing automobiles which includes a large number of working processes. However, main spindle unit in Machine tools are often cases where damage occurs do not meet the design life due to driving in harsh environments. This is when excessive maintenance and repair of machine tools or for damage stability has resulted in huge economic losses. Therefore, this studying propose a method of accelerated life test for diagnosing and prognosis the state of life assessment main spindle system. Time status monitoring of diagnostic data - through the analysis of the frequency band signals were carried out inside the main spindle bearing condition monitoring and fault diagnosis.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.161-164
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• 1995

Nonlinear analysis of various phenomena has been developed with improvement of computer. The characteristics form nonlinear analysis are available in monitoring and diagnosis state of system. There are many nonlinear property in cutting process, but nonlinear signals have been considered as noise. In this study, nonlinear analysis technique is applied and it will be verified that cutting force is chaos by calculating Lyapunov exponents,fractal dimension and embedding dimension. The relation between characteristic parameter calculated form sensor signal and various cutting condition is investigated.

• 한국정밀공학회지
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• 제13권10호
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• pp.112-122
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• 1996

In order to monitior machine tool condition and diagnose alarm states due to electrical and mechanical faults, and expert system using diagnostic parameters of NC machine tools was developed. A model-based knowledge base was constructed via searching and comparing procedures of diagnostic parameters and state parameters of the machine tool. Diagnostic monitoring results generate through a successive type inference engine were graphically displayed on the screen of the console. The validity and reliability of the expert system was rcrified on a vertical machining center equipped with FANUC OMC through a series of experiments.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.61-66
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• 1994

Tool condition monitoring is one of the most important aspects to improve productivity and quality and to achieve intelligent machining system. The tool state is classified into three groups as chipping, wear and fracture. In this study, wear of a ceramic cutting tool for hardened die material (SKD11) was investigated. Flank wear was occured more dominant than crarer wear. Therefore, to predict flank wear, the modeling of cutting force has been performed. The modeling of cutting force by an assumption that act the stress distribution on the tool face obtained through a numerical analysis. The relationships between the cutting force and the tool wear can be constructed by machining paraneters with cutting conditions. Experiments were performed under the various cutting conditions to ensure the validity of force models. The theoretical predictions of the flank wear is approximately in good agreement with experimental result.

• 한국생산제조학회지
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• 제7권3호
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• pp.14-21
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• 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.

• 한국정밀공학회지
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• 제33권6호
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• pp.453-458
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• 2016

CFRP (Carbon Fiber Reinforced Plastic) and CFRP-metal stacks have recently been widely used in the aerospace and automobile industries. When CFRP is machined by a brittle fracture mechanism, defect generation behaviors are different from those associated with metal cutting. The machining quality is strongly dependent on the properties of CFRP materials. Therefore, process control for CFRP machining is necessary to minimize the defects of differently manufactured CFRPs. In this study, defects in drilling of CFRP substrates with a variety of fiber directions and resin types are compared with respect to thrust force. An experimental study on material interface detection is carried out to investigate its benefits in process control.