• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.53-58
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• 2023

The storage capacity of 3D-NAND flash memory has been enhanced by the multi-layer dielectrics. The deposition process has become more challenging due to the tight process margin and the demand for accurate process control. To reduce product costs and ensure successful processes, process diagnosis techniques incorporating artificial intelligence (AI) have been adopted in semiconductor manufacturing. Recently there is a growing interest in process diagnosis, and numerous studies have been conducted in this field. For higher model accuracy, various process and sensor data are required, such as optical emission spectroscopy (OES), quadrupole mass spectrometer (QMS), and equipment control state. Among them, OES is usually used for plasma diagnostic. However, OES data can be distorted by viewport contamination, leading to misunderstandings in plasma diagnosis. This issue is particularly emphasized in multi-dielectric deposition processes, such as oxide and nitride (ON) stack. Thus, it is crucial to understand the potential misunderstandings related to OES data distortion due to viewport contamination. This paper explores the potential for misunderstanding OES data due to data distortion in the ON stack process. It suggests the possibility of excessively evaluating process drift through comparisons with a QMS. This understanding can be utilized to develop diagnostic models and identify the effects of viewport contamination in ON stack processes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.1
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• pp.7-16
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• 2003

At present, company has to produce a product that consumer like with a competitive price, a good quality, and a fitting time to supply. Process control and quality control are very important to supply with a product uniformly and inexpensively. Process control is given much weight in the quality control in manufacturing system. Statistical process controls(SPC) that are used in process generally have major impact on manufacturing, product design activities, and process development potentially. Control charts in statistical process control method can be interpreted the data from quality characteristics in production process and discriminated between chance variation and assignable variation in process. In addition, control chart can be used to monitor the process output and detect when changes in the inputs are required to bring the process back to an in-control state. The models that relate the influential inputs to process outputs help determine the nature and magnitude of the adjustments required. In this paper, the characteristic of product quality is monitored by control chart during the machining process and construction of quality control cycle is considered to divide into two types in this case that different assignable causes lead to shifts having different magnitudes. Then we are intended to find a process shift magnitude which has economical quality cost policy and are considered to quality cost functions to find a process shift magnitude. Those costs are categorized into the well-known categories of prevention, appraisal, and internal failure and external failure. This paper ends with numerical examples that demonstrate the usefulness of the model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.1-6
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• 2017

Process capability is well known in quality control literatures. Process capability refers to the uniformity of the process. Obviously, the variability in the process is a measure of the uniformity of output. It is customary to take the 6-sigma spread in the distribution of the product quality characteristic as a measure of process capability. However there is no reference of process capability when maximum material condition is applied to datum and position tolerance in GD&T (Geometric Dimensioning and Tolerancing). If there is no material condition in datum and position tolerance, process capability can be calculated as usual. If there is a material condition in a feature control frame, bonus tolerance is permissible. Bonus tolerance is an additional tolerance for a geometric control. Whenever a geometric tolerance is applied to a feature of size, and it contains an maximum material condition (or least material condition) modifier in the tolerance portion of the feature control frame, a bonus tolerance is permissible. When the maximum material condition modifier is used in the tolerance portion of the feature control frame, it means that the stated tolerance applies when the feature of size is at its maximum material condition. When actual mating size of the feature of size departs from maximum material condition (towards least material condition), an increase in the stated tolerance-equal to the amount of the departure-is permitted. This increase, or extra tolerance, is called the bonus tolerance. Another type of bonus tolerance is datum shift. Datum shift is similar to bonus tolerance. Like bonus tolerance, datum shift is an additional tolerance that is available under certain conditions. Therefore we try to propose how to calculate process capability index of position tolerance when maximum material condition is applied to datum and position tolerance.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.141-162
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• 2011

The controls of Information Systems (IS) have been an more critical issue controls as the sophistication and integration of IS is more proceeded. ITGI (The Information Technology Governance Institute) of ISACA (Information Systems Audit and Control Association) has suggested COBIT (Control Objectives for Information and related Technology) and this has been widely recognized the evaluation model of IS controls. In COBIT, IS was evaluated in terms of process, information quality, and IT resources. This study used COBIT in order to suggest and empirically test an evaluation model of IS service. The data was collated from one major Chinese SI (Systems Integration) company in four domains of processes : planning and organization, acquisition and implementation, delivery and support, and monitoring. Seven factors are extracted using an exploratory factor analysis as follows : Overall IT planning process, technological assessment process in IT planning of IT, cost-benefit assessment process in IT planning, implementation process, support process, monitoring process, post-implementation evaluation process. The results of confirmatory analysis of three alternative measurement models indicated that the measurement model with one inherent or conceptual variable has greater model fitness than the other models. This study suggests the logical and general way to test and apply COBIT in evaluating IS services.

• Archives of design research
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• v.13
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• pp.212-221
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• 1996

The necessity of imformation on product design process is increased in recently years, because a product can be called a mass of information and becomes more complex as long as technology is developed. But the present product development method is like a relay race. In this sequential process, information is transferred from one department to other departments like \"over the wall\". And communication gaps among departments are generated, so imformation cannot be controlled very well. Therefore it is needed to innovate the design process. The information system proposedin this study is an application software which can be useful for integrated product design process. It has been developed primarily for use in IBN PC and windows environment. It comprises four functional modules; functions of handing the overall project information (document, ideaskech, rendering, drawing); functions of decision making production problems in design project process; functions of groupware which can link with other departments; functions of comprehensive database with production.roduction.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.23-26
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• 2000

It is noted that many econometric time series have long-memory properties. A long-memory process, or strongly dependent process, is characterized by hyperbolic decaying autocorrelations and unbounded spectral density at the origin. Since the long-memory property can be observed by data obtained from rather a long period, there is some possibility of parameter change in the process. In this paper, we consider the estimation of change-point when there is a change in the variance of a long-memory process. The estimator is based on some reasonable statistic and the consistency is shown using Taqqu's strong reduction theorem

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.1-10
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• 1998

Process planning is a very complex task and requires the dynamic informatioon of shop foor and market situations. Process plan selection is one of the main problems in the process planning. In this paper, we propose a new process plan selection model considering operation flexibility for the computer aided process planing. The model is formulated as a 0-1 integer programming considering realistic shop factors such as production volume, machining time, machine capacity, transportation time and capacity of tractors such as production volume, machining time, machine capacity, transportation time capacity of transfer device. The objective of the model is to minimize the sum of the processing and transportation time for all parts. A genetic algorithm a, pp.oach is developed to solve the model. The efficiency of the proposed a, pp.oach is verified with numerical examples.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.179-184
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• 2004

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been need for an integrated process control (IPC) procedure which combines the two strategies. This article considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process disturbance model under consideration is an IMA(1,1) model with a location shift. The EPC part of the scheme adjusts the process, while the SPC part of the scheme detects the occurrence of a special cause. For adjusting the process repeated adjustment is applied by compensating the predicted deviation from target. For detecting special causes the two kinds of exponentially weighted moving average (EWMA) control chart are applied to the observed deviations: One for detecting location shift and the other for detecting increment of variability. It was assumed that the adjustment of the process under the presence of a special cause may change any of the process parameters as well as the system gain. The effectiveness of the IPC scheme is evaluated in the context of the average cost per unit time (ACU) during the operation of the scheme. One major objective of this article is to investigate the effects of the process parameters to the ACU. Another major objective is to give a practical guide for the efficient selection of the parameters of the two EWMA control charts.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.104-111
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• 2008

A process mining is considered to support the discovery of business process for unstructured process model, and a process mining algorithm by using the associated rule and sequence pattern of data mining is developed to extract information about processes from event-log, and to discover process of alternative, concurrent and hidden activities. Some numerical examples are presented to show the effectiveness and efficiency of the algorithm.

• Journal of the Korean Society of Tobacco Science
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• v.23 no.1
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• pp.53-59
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• 2001

To decrease of deviations from target specifications and excessive variability around targe, we exclusively designed statistical process control system involving general manager and expert tool for cigarette manufacturing process. This system is a unique programming environment for the development of total process control software including various control charts according to data type and process capability analysis. Also this system includes the statistical analysis module to analyze defective causes immediately when inferior products are made and the module to offer regular reports. This system is customized considering the manufacture environment based on the opinions of workers.