• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.234-238
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• 1996

In this paper, Plasma-Enhanced Chemical Vapor Deposition (PECVD) modeling using Polynomial Neural Networks (PNN) has been introduced. The deposition of SiO2 was characterized via a 25-1 fractional factorial experiment, was used to train PNNs using predicted squared error (PSE). The optimal neural network structure and learning parameters were determined by means of a second fractional factorial experiment. The optimized networks minimized both learning and prediction error. From these PNN process models, the effect of deposition conditions on film properties has been studied. The deposition experiments were carried out in a Plasma Therm 700 series PECVD system. The models obtained will ultimately be used for several other manufacturing applications, including recipe synthesis and process control.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.6
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• pp.130-138
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• 2012

There are increasing demands from the industry for intelligent robot-calibration solutions, which can be tightly integrated to the manufacturing process. A proposed solution can simplify conventional robot-calibration and teaching methods without tedious procedures and lengthy training time. iGPS(Indoor GPS) system is a laser based real-time dynamic tracking/measurement system. The key element is acquiring and reporting three-dimensional(3D) information, which can be accomplished as an integrated system or as manual contact based measurements by a user. A 3D probe is introduced as the user holds the probe in his hand and moves the probe tip over the object. The X, Y, and Z coordinates of the probe tip are measured in real-time with high accuracy. In this paper, a new approach of robot-calibration and teaching system is introduced by implementing a 3D measurement system for measuring and tracking an object with motions in up to six degrees of freedom. The general concept and kinematics of the metrology system as well as the derivations of an error budget for the general device are described. Several experimental results of geometry and its related error identification for an easy compensation / teaching method on an industrial robot will also be included.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.847-858
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• 2001

This paper considers the control model identification and H(sub)$\infty$ controller design for a tandem cold mill (TCM). In order to improve the performance of the existing automatic gauge control (AGC) system based on the Taylor linearized model of the TCM, a new mathematical model that can complement the Taylor linearized model is constructed by using the N4SID algorithm based on subspace method and the least squares algorithm based on ARX model. It is shown that the identified model had dynamic characteristics of the TCM than the existing Taylor linearized model. The H(sub)$\infty$ controller is designed to have robust stability to the system parameters variation, disturbance attenuation and robust tracking capability to the set-up value of strip thickness. The H(sub)$\infty$ servo problem is formulated and it is solved by using LMI (linear matrix inequality) techniques. Simulation results demonstrate the usefulness and applicability of the proposed H(sub)$\infty$ controller.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.4
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• pp.3-7
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• 2006

Confocal scanning microscopy is a measurement technique used to observe micrometer and sub-micrometer features due to its high resolution, nondestructive properties, and 3D surface profiling capabilities. The design, implementation, and performance test of a confocal scanning microscopy system are presented in this paper. A short-wavelength laser (405 nm) and an objective lens with a high numerical aperture (0.95) were used to achieve the desired high resolution, while the x- and y-axis scans were implemented using an acousto-optic deflector and galvanomirror, respectively. An objective lens with a piezo-actuator was used to scan the z-axis. A spatial resolution of less than 138 nm was achieved, along with successful 3D surface reconstructions.

• Smart Structures and Systems
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• v.5 no.2
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• pp.153-171
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• 2009

In this paper, the analytical fault detection and diagnosis (FDD) is presented using model-based and signal-based methodology with wavelet analysis on signals obtained from sensors and sensor networks. In the model-based FDD, we present the modeling of contact interface found in soft materials, including the biomedical contacts. Fingerprint analysis and signal-based FDD are also presented with an experimental framework consisting of a mechanical pneumatic system typically found in manufacturing automation. This diagnosis system focuses on the signal-based approach which employs multi-resolution wavelet decomposition of various sensor signals such as pressure, flow rate, etc., to determine leak configuration. Pattern recognition technique and analytical vectorized maps are developed to diagnose an unknown leakage based on the established FDD information using the affine mapping. Experimental studies and analysis are presented to illustrate the FDD methodology. Both model-based and wavelet-based FDD applied in contact interface and manufacturing automation have implication towards better quality of life by applying theory and practice to understand how effective diagnosis can be made using intelligent FDD. As an illustration, a model-based contact surface technology an benefit the diabetes with the detection of abnormal contact patterns that may result in ulceration if not detected and treated in time, thus, improving the quality of life of the patients. Ultimately, effective diagnosis using FDD with wavelet analysis, whether it is employed in biomedical applications or manufacturing automation, can have impacts on improving our quality of life.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.398-403
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• 2004

The demand of high speed machining is increasing because the high speed cutting providers high efficiency of process, short process time, improved metal removal capacity and better surface finish. Active magnetic bearings allow much high surface speed than conventional ball bearings and therefore greatly suitable for high speed cutting. The automatic control concept of magnetic bearing system provides ability of intelligent control of spindle system to increase accuracy and flexibility by means of adaptive vibration control. This paper describes a design and development of a milling spindle system which includes built-in motor with power 5.5㎾ and maximum speed 70,000rpm, HSK-32C tool holer and active magnetic bearing system. Magnetic actuators are designed for satisfying static load condition. The Performances of manufactured spindle system was examined for its static and dynamic stiffness, load capacity, and rotational accuracy. This spindle was run up to 70,000 rpm stably, which is 3.5 million DmN.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.130-145
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• 2004

This paper addresses the integrated problem of process planning and scheduling in FMS (Flexible Manufacturing System). The integration of process planning and scheduling is important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called asymmetric multileveled symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. Efficient genetic representations and operator schemes are considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and existing evolutionary algorithms. The experimental results show that the proposed algorithm outperforms the compared algorithms.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.4
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• pp.87-92
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• 2019

In this paper, a closed hydroponics device was designed and fabricated to grow and harvest plants in a small space for safe consumption, which enables horticultural activities that are difficult to perform due to space constraints from urbanization. This device also aimed to minimize the air pollution of crops. To obtain data for the optimal growth conditions for crops in this intelligent plant-growing system, sensors were used to measure and control the growth conditions. To investigate the optimal growth conditions, blue lettuce and crown daisy were selected as representative crops. The growth rates were comparatively analyzed through four experiments for each plant. This hydroponics device was used to collect data on growth rates that are altered depending on cultivation conditions, which can then be used to study methods to control the growth rate of crops.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.249-257
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• 1992

An automated machining system involves concurrent use of manufacturing resources, alternative process plans, and flexible routings. High investment in the installation of automated facilities requires an efficient scheduling system that is able to allocate the resources specified for operations over a scheduling horizon. The primary emphasis of this paper is to generate schedules that accurately reflect details of the automated environment and the objectives stated for the system. In this paper, a scheduling algorithm for automated machining is presented. Using the previous simulation research for this topic, a rule-based scheduling system is constructed. An architecture for an intelligent scheduling system is proposed, and the system has a high potential to provide efficient schedules based on the task-specific knowledge for the dynamic scheduling environment