• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.1005-1010
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• 2000

Internet service has widely used in office automation such as, manufacturing management purchase, and material resource. Nowadays, factory automation and shop floor control system including CAD/CAM department need a web based monitoring and diagnosis to achieve global collaboration and tole-service. This raper deal with design of web based remote monitoring and diagnosis system which concerned with open architecture controller for machine tool.

• Steel and Composite Structures
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• v.21 no.3
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• pp.573-588
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• 2016

Carbon Fiber Reinforced Plastic (CFRP) and Titanium Alloy (Ti6Al4V) stack, extensively used in aerospace structural components are assembled by fasteners and the holes are made using drilling process. Drilling of stack in one shot is a complicated process due to dissimilarity in the material properties. It is vital to have optimal machining condition and tool geometry for better hole quality and tool life. In this study the tool wear and hole quality were analysed by experimental analysis using three modified twist drills and online tool condition monitoring using Acoustics Emission (AE) sensor. Helix angle and point angle influence tool performance and cutting force. It was found that a tool geometry (TG1) with high helix angle of $35^{\circ}$ with low point angle $130^{\circ}$ results in reduction in thrust force of 150-500 N range but the TG2 also perform almost similar to TG1, but when compared with the AErms voltage generated during drilling it was found that progressive rise in voltage in TG1 is less with respect to TG2 which can be attributed to tool life. In process wear monitoring was done using crest factor as monitoring index. AErms voltage were measured and correlated with the performance of the drills.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.26-31
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• 1994

The analysis of acoustic emission signals generated during machining has been proposed as a technique for studying both the fundamentals of the cutting process and process and as a methodology for detecting tool fracture on line. In this study, AE signals detected during End Milling were applied as the experimental test to sensing tool fracture on the CNC vertical milling machine. Because automatic monitoring of the cutting condition is one of the most important technologies in machining, the in-process detection of cutting tool life including fracture has been investigated by performing experimental test.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.42-49
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• 2009

This study proposes a web-based remote monitoring system for evaluating degradation of machine tools using ART2(Adaptive Resonance Theory 2) neural network. A number of studies on the monitoring of machine tools using neural networks have been reported. However, when normal condition is changed due to factors such as maintenance, tool change etc., or a new failure signal is generated, such algorithms need to be entirely retrained in order to accommodate the new signals. To cope with such problems, this study develops a remote monitoring system using ART2 in which new signals when required are simply added to the classes previously trained. This system can monitor degradation as well as failure of machine tools. To show the effectiveness of the proposed approach, the system is experimentally applied to monitoring a simulator similar to the main spindle of a machine tool, and the results show that the proposed system can be extended to monitoring of real industrial machine tools and equipment.

• Health Policy and Management
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• v.13 no.3
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• pp.35-51
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• 2003

This study purports to develop a quality assessment tool for the process of health promotion programs at public health centers(PHC). The draft of the assessment tool developed by the literature was distributed to 242 staffs who were in charge of the health promotion programs at PHCs for evaluating the feasibility of the tool on September and October 2002. The major results of the study were as follows; The quality assessment tool developed in the study consisted of four domains: strategic planning, program management, monitoring and evaluation, and resources and information. The strategic planning dealt with the function of the planning staff and committees, community data analysis, the feasibility of the program, and the approach methods for attaining the goal of the program. The program management included the items on the qualification and power of the program staff. The monitoring and evaluation included the items on the reporting and communication among program units, and feed back after monitoring. Finally, the resources and information dealt with community networking, clients' response, and consulting activity of the staff. The validity of the tools was tested and partly supported by both formative and criterion-related methods. The assessment tools developed in this study could be used by health promotion workers in the self-evaluation of the program quality. In conclusion, the quality assessment tool developed in the study will be a good safeguard for assuring the quality of the process of health promotion programs.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.4 no.2
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• pp.18-24
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• 1995

In order to achieve the autimation and untended system of manufacturing process, it is necessary that the monitoring system check up the disorder of machine tool or the conditions of tool wear for the maximum use of cutting tool. In the metal cutting Process, AE signal is detected by AE sensor, then amplified and transmitted to an Locan-AT. The experiment was performed to SM25C and STS304 steels at uniform feedrate, cutting speed and depth of cut, The results of experimental data apparently showed emission intensity vary due to increasing of tool wear at the 165kHz, 200kHz in the SM25C and 140kHz, 165kHz, 200kHz, in the STS304 respectively Therefore, it is possible to predict the tool wear. This study is intended to suggest the way to the automation and untended system of machine tool through the system monitoring tool wear by using AE signal.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.174-181
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• 1999

In this paper the technique to predict tool wear theoretically in shearing process is suggested. The tool wear in the process affects the tolerances of final pans, metal flows and costs of processes. In order to predict the tool wear the deformation of workpiece during the process is analyzed by using non-isothermal finite element program. The ductile fracture criterion and the element kill method are also used to estimate if and where a fracture will occur and to investigate the features of the sheared surface in shearing process. Results obtained from finite element simulation, such as nodal velocities and nodal forces, are transformed into sliding velocity and normal pressure on tool monitoring points respectively. The monitoring points are automatically generated and the wear rates on these points are accumulated during the process. It is assumed that the wear depth on the tool surface is linear function of the lot sizes based upon the known experimental results. The influence of clearance between die and punch upon tool wear is also discussed.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.136-142
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• 1996

Automatic monitoring of cutting process is one of the most important technology in machining. AE sensing technology has been applied to monitoring process and proved to be effective in detecting tool abnor- malities such as tool wear and fracture. In this experimental study. AE signals were detected from the tool holder for continuous and interrupted cutting, which obtained from changing workpice material configuration, under control of constant cutting speed from CNC lathe. From statistical and frequency analysis, the AE signals were analyzed to obtaining the characteristics of continuous and interrupted cutting conditions and tool failure. The Kurtosis values decreased but RMS voltages increased as the cutting speed increased, in both continuous and interrupted cutting. RMS voltage is suddenly increased but Kurtosis value is suddenly decreased when tool failure condition. Power spectrum density of AE signals when tool failure reaches extreme value around 0.065 cycles/ .mu. m.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.94-103
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• 1993

In this work, the imaginary part of the inner modulation transfer function of the cutting dynamics is introduced for tool wear monitoring. Time-series method is utilized to construct the general three dimensional cutting dynamics whose imaginary part of the inner modulation transfer funcition shows the proportionality to tool wear at the natural frequency of the machine tool dynamics. Thus model is reduced to single-input single-output model without altering the proportionality characteristics to tool wear and implemented to the dual computer system in which one computer performs measurement while the other calculates the imaginary part of the inner modulation transfer function of the cutting dynamics by the batch least square method. The values of the imaginary part at the natural requency of the machine tool structure in the cutting direction are compared to the one calculated during machining with a brand new tool to decide the current status of the tool. The experiments shows the relevance of the proposed concept.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.97-106
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• 2007

In this paper, the business process was easily modeled by distinguishing between the business process and work logic. Based on this model, B2Bi collaboration Workflow modeling tool, which facilitates collaboration, was designed and implemented. The collaboration workflow modeling tool consists of 3 components; business process modeling tool, execution engine and monitoring tool. First, a business process modeling tool is used to build a process map that reflects the business logic of an application in a quick and accurate manner. Second an execution engine provides a real-time execution environment for business process instance. Third, a monitoring tool provides a real-time monitoring function for the business process that is in operation at the time. In addition to this, it supports flexibility and expandability based on XML and J2EE for the linkage with the legacy system that was used previously, and suggests a solution for a new corporate strategy and operation.