• IE interfaces
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• v.15 no.3
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• pp.308-315
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• 2002

This study presents the web based cutting parameter selection system using Group Technology (GT). The GT is basically applied to classify and code the work material and cutting process which are main factors to affect cutting parameter selection. The proposed system has been designed to electronically select proper cutting conditions based on the stored GT database. The existing approaches used in most small and medium sized companies are basically to use manufacturing engineer's experience or to find the recommended values from the manufacturing engineers handbook. These processes are often time consuming and inconsistent, especially when a new engineer is involved. Consequently, the proposed system could automatically and consistently generate the proper cutting conditions (feed, depth of cut, and cutting speed) as soon as relatively simple data input is given thanks to the classified GT database.

• IE interfaces
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• v.9 no.1
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• pp.1-10
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• 1996

In this study, expert system for the selection of the optimal cutting speed and feed rate was developed using NEXPERT system shell. The NC system has been usually used inefficiently because the input command, which contains cutting speed, feed-rate and the depth of cut, is fixed value which depends on principally operator's experience and machining handbooks providing a guideline for applicable ranges. On the other hand, the optimal cutting conditions vary with time, and depend on tool and machine characteristics, work materials, and cost factor and so on. In this study, if cutting factors, such as, cutting method, material type, cutting depth, and tool nose radius are specified, our expert system gets the information about the standard cutting speed form the cutting speed database, and provides optimum feed rate for these cutting conditions. This cutting speed database can be updated by inputting valid cutting speed which is obtained form the practices.

• Korean Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.236-242
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• 1998

This paper presents a development of computer aided cutting tool selection techniques for rough and finish turning operations. The developed system,. which is one of important activities for computer aided operation planning, firstly implements operation sequencing. Then, from relations of the size of machined area, recommended finishing allowance and maximum depth of cut, a main machining method is selected, a number of cut is calculated, cutting tools including toolholders and inserts are selected, and values for cutting parameters are determined. A cutting tool selection procedure is proposed for toolholders and inserts of ISO code in rough cutting, and some important parameters such as holder style, tool approach angle, tool function and its direction are described in detail. In order to demonstrate the validity of the system a case study is performed.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.3
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• pp.53-60
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• 1992

This paper deals with developing an Expert system for tool selection using knowledge base system approach, and its application. For the sake of building of knowledge base, the information from process through sensor, tool handbook and interview with expert are referrenced and managed. The system developed shows good application flexibility in providing the actual cutting process with the selection of tool(insert, holder) and cutting conditions(feed, speed, rake type, and so on), is found as a useful system for real-time machining process. The Expert system for tool selection is written in TURBO PROLOG ver. 2.0 for inference engine capability, and can be run in interactive mode for user friendliness. In order to apply the system developed in actual cutting process, more parameters should be considered and scrutinized, and the system should be further extended in modular basis.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.4
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• pp.402-409
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• 2017

Selection of optimal cutting conditions is important for improving productivity and implementing efficient process control in metal machining. In this study, improvement of cutting conditions in machining using end-mills is studied by using deep-layered neural networks, which comprise an input layer, output layer, and two hidden layers. System networks are designed with inputs as cutting conditions, and they output the cutting force. A pseudo-inverse network is designed that has the adjustable cutting condition as output and cutting force and other cutting conditions as input. The combination of the system network and pseudo-inverse network enables selection or improvement of cutting conditions that results in the expected cutting force.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.170-174
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• 1990

The information with regard to the working range of lathe, cutting tool, cutting condition is managed as Database system for turning operation as one part of CAM system. Data with regard to the working range of lathe, cutting tool, cutting condition are stored by the DBMS(Data Base Management System) and can be added, modified, deleted and retrieved for realtime usages. Data stored in Database system are searched to select the most proper cutting tool and cutting condition with the input data fed from the design stage. Codes in regards to tool shape are displayed on graphic mode for easy selection for user and thus presents a good decision support for tool selection. The system developed in this work is operated by the pull down menu on the IBM PC/AT personal computer, or compatible series.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.104-107
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• 1996

This paper focuses on a automation selection of optimal cutting conditions and cycle time for multi-spindle metal cutting machines based on machining parameters and tool change schemes which are the two most common terms used in the metal cutting. In this research we used two step generative approach, step 1 is mathematical modeling for the selection fo optimal cutting conditions and the other is GMDH-Type modeling to estimate the system performance evaluation. We developed computer programs for these models and the fitting manufacturing examples are applied to this model and it was shown that the proposed approach has a good potential and offers a valuable tools to analyse the metal cutting system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.689-693
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• 1996

This paper was performed on the automatic selection of cutting condition on multispindle machine. the several mathematical relationships were formulated for simulataneous selection of machining parameters and tool changing scheme. In this research we used two step generative approach; step 1 is mathematical modeling for the selection of optimal cutting conditions and the other is GMDH-TYPE modeling to find prediction equation of system performance. thus in this paper, mathematical machining models combined with a heuristic GMDH-TYPE modeling to estimate the system performance, these models are developed computer programs for practical application and it was shown that the proposed approach has a good potential and offers a valuable tools to performance evaluation for metal cutting system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.354-358
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• 2004

There was not the evident analysis about the cutting process of CNC machining, and wouldn't be difficult to estimate the result of machining for the various cutting conditions. Therefore they were not founded the systemic technology about the optimum cutting conditions and selection of cutting tools. So this study have investigated the common facts for needs through the end-mill cutting machining by Machining-Centers or High-speed cutting machines, and developed the user-centered intelligent decision system to selection of the methodology about cutting conditions to improve the machining efficiency of end-mill cutting process.

• Proceedings of the KWS Conference
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• 1994.05a
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• pp.186-189
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• 1994

This paper proposes an expert system for the selection of the appropriate laser cutting variables from the available database. Optimum cutting conditions were searched and qualitative comments which are hard to choose as database variables were shown using the binary and fuzzy inference.