• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.617-618
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• 2012

• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.92-99
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• 2024

As semiconductor processes require several nanometers precision, the importance of motor control is increasing in semiconductor equipment. Due to unpredictable uncertainties such as friction and mechanical vibrations achieving precise position control in semiconductor processes is challenging. The internal model principle-based controller is a control technique that ensures robust steady-state performance by incorporating a model of the reference and disturbance. The disturbance observer-based controller is a prominent robust control technique implemented to cope with various nonlinearities and uncertainties. Provided that the two controllers can be designed to exhibit equivalent performance under certain conditions, this paper demonstrates through experiments that they yield identical results for the case of a BLDC position control problem. The experimental results also indicate that they can offer enhanced robustness compared with the conventional PID controller in the presence of a time-varying disturbance.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.52-55
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• 2024

In this paper, a state change study was conducted through Frequency Domain Reflectometry (FDR) technology for the process chamber of plasma equipment for semiconductor manufacturing. In the experiment, by direct connecting the network analyzer to the RF matcher input of the 300 mm plasma enhanced chemical vapor deposition (PECVD) chamber, S11 was measured in a situation where plasma was not applied, and the frequency domain reacting to the chamber state change was searched. Response factors to changes in the status, such as temperature, spacing of the heating chuck, internal pressure difference, and process gas supply state were confirmed. Through this, the frequency domain in which a change in the reflection value was detected through repeated experiments. The reliability of the measured micro-displacement was verified through reproducibility experiments.

• Journal of Korea Trade
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• v.25 no.6
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• pp.78-104
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• 2021

Purpose - Semiconductors are a significant export item for Korea that is expected to continue to contribute significantly to the Korean economy in the future. Thus, the semiconductor industry is a critical component in the 4th Industrial Revolution and is expected to continue growing as the non-face-to-face economy expands as a result of the COVID-19 pandemic. In this context, this paper aims to empirically investigate how semiconductors are imported and exported in Korea from a global supply chain perspective by analysing import and export data at the micro-level. Design/methodology - This study conducts a multifaceted analysis of the global supply chain for semiconductors and related equipment in Korea by examining semiconductor imports and exports by semiconductor type, year, target country, mode of transportation, airport/port, and domestic region, using import/export micro-data. The visualisation, flow analysis, and Bayesian Network methodologies were used to compensate for the limitations of each method. Findings - Korea is a major exporter of semiconductor memory and has the world's highest competitiveness but is relatively weak in the field of system semiconductors. The trade deficit in 'semiconductor equipment and parts' is clearly growing. As a result, continued investment in 'system semiconductors' and 'semiconductor equipment and parts' technology development is necessary to boost exports and ensure a stable supply chain. Originality/value - Few papers on semiconductor trade in Korea have been published from the perspective of the global supply chain or value chain. This study contributes to the literature in this area by focusing on import and export data for the global supply chain of the Korean semiconductor industry using a variety of approaches. It is our hope that the insights gained from this study will aid in the advancement of SCM research.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.252-261
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• 2014

A Bayesian network (BN) based fault diagnosis framework for semiconductor etching equipment is presented. Suggested framework contains data preprocessing, data synchronization, time series modeling, and BN inference, and the established BNs show the cause and effect relationship in the equipment module level. Statistically significant state variable identification (SVID) data of etch equipment are preselected using principal component analysis (PCA) and derivative dynamic time warping (DDTW) is employed for data synchronization. Elman's recurrent neural networks (ERNNs) for individual SVID parameters are constructed, and the predicted errors of ERNNs are then used for assigning prior conditional probability in BN inference of the fault diagnosis. For the demonstration of the proposed methodology, 300 mm etch equipment model is reconstructed in subsystem levels, and several fault diagnosis scenarios are considered. BNs for the equipment fault diagnosis consists of three layers of nodes, such as root cause (RC), module (M), and data parameter (DP), and the constructed BN illustrates how the observed fault is related with possible root causes. Four out of five different types of fault scenarios are successfully diagnosed with the proposed inference methodology.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.121-126
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• 2017

EES System support to maximize equipment efficiency by providing real-time information of main equipment which has a significant effect on product quality and productivity, and to prevent equipment failure by detecting equipment abnormality in advance. Smart Equipment Engineering System(S-EES) integrates the activities performed at equipment that are the core of production activities and manages them by system so as to maximize the efficiency of equipment and raise the quality level of products to one level. In other words, when the product is put into the equipment, the recipe is downloaded through the RMS, the recipe is set to the optimal condition through R2R(process control), and the system detects and controls the abnormality of the equipment during operation through the FDC function in real time it means. In this way, we are working with the suitable recipe that matches the lot of product, detecting the abnormality of the equipment during operation, preventing the product from being defective, and establishing a system to maximize the efficiency through real-time equipment management. In this study, we review the present status and problems of equipment management in actual production lines, collect the requirements of the manufacturing line for the PCB line, design and develop the system, The measurement model was studied.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.151-159
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• 2007

It is very important to collect all production-related status values during the manufacturing process of semiconductor. The analysis results of the collected data can be used for the operation rate, fault diagnosis, process control and removal of predicted obstacles of equipments, eventually contributing to the improvement of production efficiency. For this propose. many IC makers have adopted EES(Equipment Engineering System). As the use of web has become a daily lift activity lately, it has been suggested to expand the scope of monitoring equipments using HTTP or SOAP protocols. To fulfill the web-based EES, EDA(Equipment Data Aquisition) should be facilitated first by integrating and standardizing various forms of messages generated from many different semiconductor equipments. In this paper, a method for integration between different types of information is suggested based on the analysis of various protocols used for the communication between semiconductor equipments. In addition, a software architecture to support the method is desisted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.5906-5911
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• 2014

Currently, there are many processes of package assembly and inspections of real fields that examine whether a manufactured semiconductor can be operated regularly and can endure low humidity or high temperatures. As the inspection equipment of a semiconductor test handler picker has been used at the inspection process, these inspection equipment frames were modelled in 3D and these models were analyzed using 3 kinds of fatigue loadings. As the analysis result, maximum deformation occurred at the midparts of the frames at cases 1 and 2. Among the cases of nonuniform fatigue loads, the 'SAE bracket history' with the severest change in load became the most unstable but the 'Sample history' became the most stable. Fatigue analysis result can be used effectively with the design of an inspecting equipment frame of a semiconductor test handler picker to examine the prevention and durability against damage.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.126-130
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• 2021

The ball grid array is one of the packaging methods that used in high density printed circuit board. Solder void defects caused by voids in the solder ball during the BGA process do not directly affect the reliability of the product, but it may accelerate the aging of the device on the PCB layer or interface surface depending on its size or location. Void inspection is important because it is related in yields with products. The most important process in the optical inspection of solder void is the segmentation process of solder and void. However, there are several segmentation algorithms for the vision inspection, it is impossible to inspect all of images ideally. When X-Ray images with poor contrast and high level of noise become difficult to perform image processing for vision inspection in terms of software programming. This paper suggests the solution to deal with the suggested problem by means of using Mask R-CNN instead of digital image processing algorithm. Mask R-CNN model can be trained with images pre-processed to increase contrast or alleviate noises. With this process, it provides more efficient system about complex object segmentation than conventional system.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.96-103
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• 2023

This paper presents a robust position tracking controller for a motor used in semiconductor equipment, utilizing the motor angle measurement. Precise position control is challenging due to the presence of uncertainties in various motor applications. The proposed controller consists of a PD (Proportional-Derivative) controller and a PIO (Proportional-Integral Observer) to estimate the system's state and equivalent disturbance compensating for the uncertainties. Since the stability alternates as the observer gain increases, we have investigated it through the closedloop root locus under the system parameters change. The analysis has showed that the inertia of the motor is the main parameter that affects it, and by adjusting the control gain appropriately, the system can be rendered to be stable even when the inertia of the motor changes. The effectiveness of the proposed control algorithm is validated through computer simulations, followed by a comparison of its performance with the results of a previous study.