Kiwook Song

An effective procedure for sensor variable selection and utilization in plasma etching for semiconductor manufacturing

Abstract Plasma etching processes have a potentially large number of sensor variables to be utilized, and the number of the sensor variables is growing due to advances in real-time sensors. In addition, the sensor variables from plasma sensors require additional knowledge about plasmas, which becomes a big burden for engineers to utilize them in this filed. Thus an effective procedure for sensor variable selection with minimum plasma knowledge is needed to develop in plasma etching. The integrated squared response (ISR) based sensor variable selection method which facilitates collecting and analyzing sensor data at one time with regard to manipulated variables (MVs) is suggested in this paper. The reference sensor library as well as sensor ranking tables constructed on the basis of ISR can give insight into plasma sensors. The ISR based sensor variable selection method is incorporated with relative gain array (RGA) or non-square relative gain array (NRGA) for effective variable selection in building a virtual metrology (VM) system to predict critical dimension (CD) in plasma etching. The application of the technique introduced in this paper is shown to be effective in the CD prediction in plasma etching for a dynamic random access memory (DRAM) manufacturing. The procedure for sensor variable selection introduced in this paper can be a starting point for various sensor-related applications in semiconductor manufacturing.

Implementation of a robust virtual metrology for plasma etching through effective variable selection and recursive update technology

Virtual metrology (VM) is attracting much interest from semiconductor manufacturers because of its potential advantages for quality control. Plasma etching equipment with state-of-the-art plasma sensors are attractive for implementing VM. However, the plasma sensors requiring physical understanding make it difficult to select input parameters for VM. In addition, those sensors with high sensitivity frequently cause several issues in terms of VM performance. This paper will address plasma sensor issues in implementing a robust VM, where self-excited electron resonance spectroscopy, optical emission spectroscopy, and VI-probe are utilized for critical dimension prediction in a plasma etching process. An optimum sensor selection technique which can give insight into effectiveness of plasma sensors is introduced. In this technique, a numerical criterion, integrated squared response, is proposed for effective selection of important sensors for particular manipulated variables. Sensor data shift across equipmen...

Optimal operation strategy of batch vacuum distillation for sulfuric acid recycling process

Abstract Vacuum distillation techniques are widely used in food, biological, pharmaceutical, and wastewater treatment industries. Because of its operation at low temperatures, vacuum distillation prevents the thermal decomposition of materials and alleviates corrosion processes; however, condenser size can be dramatically increased because of reductions in mean temperature differences under the vacuum operation. In batch vacuum distillation processes, vapor generation rate and mean temperature differences are changed with time. In view of these characteristics of batch operation, this paper suggests a novel methodology to minimize the condenser size in batch vacuum distillation processes. The target process is a sulfuric acid recycling system in semiconductor manufacturing plants. In this paper, an equation-oriented dynamic model is established and optimization problem is formulated. By solving the nonlinear programming problem, the condenser size is dramatically reduced when operation time is fixed. In contrast, operation time is greatly shortened when the installed condenser surface area is fixed.

Multiple input multiple output controller design to match chamber performance in plasma etching for semiconductor manufacturing

In semiconductor manufacturing, multiple chambers utilized for the same process step often experience performance variation. This chamber to chamber performance variation has affected the yield of wafers, but there are no standard procedures to reduce them in semiconductor manufacturing. This paper introduces chamber matching in plasma etching as one of the core issues in semiconductor manufacturing and suggests a step-by-step procedure to address chamber matching issues. A brief review of two approaches, fault detection and classification and equipment control, is given and a step-by-step procedure of the equipment control approach is introduced. To design a multiple input-multiple output controller, a decomposed etch rate map makes it possible to analyze etch rate performance between chambers and to define controlled variables. Optimum variable selection techniques, such as singular value analysis and relative gain array methods, and dynamic optimization with constraints are suggested in this paper. In ...

A decomposition methodology for dynamic modeling of cold box in offshore natural gas liquefaction process

Abstract Natural gas liquefaction process using mixed and/or cascade refrigerant is popular in onshore LNG (liquefied natural gas) plant. Similar attempt has been adopted for FLNG (floating LNG) but still needed for the improvement of the process to enhance its efficiency as well as reliability. The dynamic modeling of cold box which is a core equipment in LNG/FLNG plant enabling to liquefy natural gas is crucial in order to develop or improve a liquefaction process concerning operability and controllability. A decomposition methodology for dynamic modeling of cold box in the case of lack of internal design data at early design stage is presented. The proposed methodology is validated through the industrial application of offshore natural gas liquefaction process and expected to be extensively applied to the various process designs which require dynamic simulation of cold box unit.

Dynamic simulation of natural gas liquefaction process

Abstract Dynamic simulation of the process can be used to develop reliable and cost-minimizing control philosophy. In this work, dynamic model of natural gas liquefaction process by mixed refrigerant is developed using commercial simulator. Dynamic model development process of the plate-fin heat exchanger is discussed in detail. Two step decomposition algorithm of updating k values and UA values for the cold-box is proposed. The procedure is applied to a propane precooled mixed refrigerant process. Feed disturbance of natural gas is simulated for dynamic performance test of the liquefaction cycle.

Hybrid Compressor Model for Optimal Operation of CDA System

Abstract CDA(Compressed Dry Air) is an essential utility to be used in a variety of processes in LCD(Liquid Crystal Display) production industry. Since the demands for CDA fluctuate largely from moment to moment, it is common to supply compressed air with a number of small-capacity compressors rather than few large-capacity ones. In order to meet the varying demands, operation conditions of compressors change at every second and hence the efficiency of compressors is low. To find optimal operating strategy of such compressor network, first a hybrid modeling technique of ideal model and empirical model is developed to predict efficiency and power consumption of each compressor in the network. Then, optimization procedure is applied to search optimal operation strategy. The proposed method was applied to actual off-line data of LCD production industry and about 5% of annual power consumption was saved by optimization.