• Journal of the Korean Society for Precision Engineering
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• v.14 no.1
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• pp.108-118
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• 1997

The heterarchical structure provides a more attractive solution to the conventional hierarchical structure as the density and level of distrubution of computing resources in manufacturing system expands. Tracing the evolution of control structures for automated manufacturing systems, this paper discusses the design principles for heterarchical system to reduce complexity, increase extendability, flexible configurability and suggests a good example of real-time adaptation using the concept of intelligent agent of manufac- turing entities and fault diagmosis system.

• Asia pacific journal of information systems
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• v.9 no.2
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• pp.19-37
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• 1999

Computer aided process planning(CAPP) is a key for implementing CIM. It is bridge between CAD and CAM and translates the design information into manufacturing instructions. Generally, manufacturing is an area where intelligent systems will not be able to rely on methods requiring formalized knowledge. Manufacturing lacks a body of knowledge that is specific, formalized, and rigorous, and which can be coded as rules or procedures. Thus expertise in manufacturing is developed over a period of many years. Case-based reasoning(CBR) offers a new approach for developing intelligent system. In the case-based approach the problem solving experience of the experts is encoded in the form of cases. CBR's retrieval process can be divided to two step. The first step is matching step, and the second step is selection step. For selecting base case, new preference heuristics were introduced using similarity concept. Similarity concept has three has three dimensions, i.e. entity similarity, structural similarity, and goal similarity. In this paper, bolt's process planning was selected an application domain. Following the test result, the new preference heuristics were approved as a useful procedure in CAPP.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.2
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• pp.83-91
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• 1997

Interactive measuring Part Program Generating Tools (IMPPGT) realized on the FANUC 15MA using touch trigger probes and interactive macro functions of the CNC were developed for intelligent measuring and inspection systems on the machine tools. Machine tools. Menu driven measuring and inspection functions of the IMPPGT were studied and implemented on the CNC through the macro executor and ROM writer. In order to automate measurement and inspection procedures in machine shops, measuring G Code system was also proposed. Using the developed measuring G Code system on the machine tool, untended measurement and inspection operation was able to be realized in FMS lines.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.1
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• pp.20-23
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• 2000

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.584-590
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• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.159-173
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• 2002

The goal of this research is to develop of an intelligent injection mold process planning system using Case-Based Reasoning. Injection mold process planning is the planning of manufacturing process to produce an injection mold economically and efficiently. Automation of the process planning is required because the problems of handmade scheduling, the difficulty of training experts for process planning, the lack of domain experts, the spread of CAD/CAM system and flexible manufacturing. This research uses Case-Based Reasoning because the injection mold process planning is devised variously and complicatedly, but the process planning of similar injection molds is very similar to each other. The system that is developed by this research uses cases that are collected in a case base when planning the process of new injection mold. New injection mold process planning is devised by retrieving a case that was made from the most similar injection mold. This research presented and composed the cases of injection mold process planning, and devised a method of search and adaptation, and developed an intelligent injection mold process planning system with the experimental results.

• Laser Solutions
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• v.11 no.4
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• pp.21-28
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• 2008

Remote Laser welding technology for manufacturing automotive body is studied. Laser welding and industrial robot systems are used for the robot based laser welding system. The laser system is used 1.6kW Fiber laser(YLR-1600) of IPG. The robot system is used HX130-02 of Hyundai Heavy Industry(payload : 130kg). The robot based laser welding system is equipped with laser scanner system for remote laser welding. The welding joints of steel plate and steel plate coated with zinc are butt and lapped joints. The quality test of the laser welding are through the observation the shape of bead on plate and cross-section of welding part. During past three years the laser system, 4kW Nd:YAG laser (HL4006D) of Trumpf was used and the robot system, IRB6400R of ABB (payload:120kg) was used. The new laser source, robot and laser scanner system are used to increase the processing speed and to improve the process efficiency. This paper introduces the robot based remote laser welding system to resolve the limited welding speed and accuracy of the conventional laser welding system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1489-1492
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• 1997

To increase reliability and performance of an IMS(Intelligent Manufacturing System), fault tolerant control based on an accurate fault diagnosis is needed. In this paper, robot FDI(fault detection and identification) is proposed for IMS where the robot is controlled with state estimates of a nonlinear filter using a mathematical robot model. The Chi-square distribution is applied fault detection and fault size is estimated by a proposed bias filter. Performance of the proposed algorithm is tested by simulation for studies.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.666-673
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• 1998

To increase reliability and performance of an IMS(Intelligent Manufacturing System), fault tolerant control based on an accurate fault diagnosis is needed. In this paper, robot FDI(fault detection and identification) is proposed for IMS where the robot is controlled with state estimates of a nonlinear filter using a mathematical robot model. The Chi-square test and GLR(General likelihood ratio) test are applied for fault detection and fault size is estimated by a proposed bias filter. Performance of the proposed algorithm is tested by simulation for studies.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.264-269
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• 2005

Advances in sensors, actuators, and computers and developments In information systems offer unprecedented opportunities to implement highly ambitious automation, control and decision strategies. There are also new challenges and demands for control and automation in modern industrial practices. There is a growing need for an active participation from the information systems in industrial, manufacturing and process industry environments because currently there are many control problems. This paper provides pattern recognition to the monitoring system for solvent manufacturing process and shows performance in real-time response with multiple input signals. Data is teamed by a multilayer feedforward network trained by error-backpropagation. The two kinds of test results show that the trained network has the ability to show the current system status with different input data sets.