• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.132-139
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• 2009

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.773-788
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• 2000

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for processes 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 needs for a process control proceduce which combines the tow strategies. This paper considers a combined scheme which simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process model under consideration is an integrated moving average(IMA) process with a step shift. The EPC part of the scheme adjusts the process back to target at every fixed monitoring intervals, which is referred to a repeated adjustment scheme. The SPC part of the scheme uses an exponentially weighted moving average(EWMA) of observed deviation from target to detect special causes. A Markov chain model is developed to relate the scheme's expected cost per unit time to the design parameters of he combined control scheme. The expected cost per unit time is composed of off-target cost, adjustment cost, monitoring cost, and false alarm cost.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.74-83
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• 2002

Process capability indices as an important kind of indices are intended to provide single-number assessments of the inherent process capability to meet specification limits on quality characteristic(5) of interest. In this paper the condition for the application of process capability indices is analyzed. On the basis of process capability indices, dynamic process capability indices as a new kind of indices to show the current process capability are discussed and the condition for the application of dynamic process capability indices is exhibited. Comparison between process capability index and dynamic process capability index and comparison between $D_p$ and $D_pk$ are made and the conclusions provide the approach for process control. According to the requirement of process capability indices provided by customer, quality control based on process capability indices dynamic process capability indices is discussed.

• Journal of the Korean Statistical Society
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• v.29 no.3
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• pp.319-336
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• 2000

A mixed model with a white noise process and an IMA(0,1,1) process is considered as a process model. It is assumed that the process is a white noise in the absence of a special cause and the process changes to an IMA(0,1,1) due to a special cause. One useful scheme in measuring the process level is to use the variable measurement interval (VMI) between measurement times according to the value of the previous chart statistic. The advantage of the VMI scheme is to measure the process level infrequently when in control to save the measurement cost and to measure frequently when out of control to save the off-target cost. This paper considers the VMI scheme in order to detect changes in the process model from a white noise to an IMA(0,1,1). The VMI scheme is shown to be effective compared to the standard fixed measurement interval (FMI) scheme in both statistical and economic contexts.

• Ocean Systems Engineering
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• v.2 no.1
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• pp.49-68
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• 2012

In this paper, an offshore process front end engineering design (FEED) method is systematically introduced and reviewed to enable efficient offshore oil and gas production plant engineering. An integrated process engineering environment is also presented for the topside systems of a liquefied natural gas floating production, storage, and offloading (LNG FPSO) unit, based on the concepts and procedures for the process FEED of general offshore production plants. Various activities of the general process FEED scheme are first summarized, and then the offshore process FEED method, which is applicable to all types of offshore oil and gas production plants, is presented. The integrated process engineering environment is presented according to the aforementioned FEED method. Finally, the offshore process FEED method is applied to the topside systems of an LNG FPSO in order to verify the validity and applicability of the FEED method.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1240-1245
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• 2009

The throughput characteristics of the cluster tool with dual blade robot are analyzed. Using equipment's cycle time chart of the equipment, simple analytic form of the throughput is derived. Then, several important throughput characteristics are analyzed by the throughput formula. First, utilization of the process chamber and the robot are maximized by assigning the equipment to the process whose processing time is near the critical process time. Second, rule for selecting optimal number of process chambers is suggested. It is desirable to select a single process chamber plus a single robot structure for relatively short time process and multi process chambers plus a single robot, namely cluster tool for relatively long time process. Third, throughput variation between equipments due to the wafer transfer time variation is analyzed, especially for the process whose processing time is less than critical process time. And the throughput and the wafer transfer time of the equipments in our fabrication line are measured and compared to the analysis.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.98-105
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• 1999

As the IC(Integrated Circuit) has been densified and complicated, it is required to thorough process control to improve yield. Experts, for this purpose, focused on the process analysis automation, which is came from the strict data management in semiconductor manufacturing. In this paper, we presents the process analysis system that can analyze causes, for a output after processes. Also, the plasma etching process that highly affects yield among semiconductor process is modeled to predict a output before the process. To approach this problem, we use adaptively trained neural networks that exhibit superior accuracy over statistical techniques. And in comparison with methods in other paper, a method that history of trend for input data is considered is shown to offer advantage in both learning and prediction capability. This research regards CD(Critical Dimension) that is considerable in high integrated circuit as output variable of the prediction model.

• Transactions of Materials Processing
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• v.8 no.6
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• pp.541-553
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• 1999

Cold forging is a special type of forging process in which metal is forced to flow plastically under compressive force into a variety of shapes in room temperature. Gear blank, which is produced by cold forging, is concerned with the production method of transmission gear. Based on the results of simulation of the current four-stage process, the gear blank forging process for improving the conventional process sequence is designed. The rigid plastic finite element analysis for improving the conventional process. The new process consists of three stage operations with one annealing treatment after first operation. Based on the results of simulation of the proposed process, a required equipment could be selected. The new designed process appears to be more economical in producing the gear blank.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.895-898
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• 1997

These days, most of new materials, which is in use widely as cutting process materials have a characteristic in common. That is hard cutting. So, it happens that hardness by cutting temperature. And hardness on cutting process has an effect on tool wear or life shortness of tools. To solve these problems hot-machining is proposed. When a material is heated, organization of material is soften. So cutting process becomes easy. When such a hot-machining method applies on drilling process and then heated material is processed, cutting force is less than usual drilling process cutting force. In this paper, when a material is heated, cutting force on drilling process is measured. It is decided that the best suitable temperature area. And it suggest that the better hot-machining condition as surface accuracy is measured.

• Journal of Information Technology Applications and Management
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• v.9 no.3
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• pp.113-127
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• 2002

The effort for software process improvement is lately surging its interest though it does not satisfy both developer and receiver In terms of low productivity, quality, delay and increasing cost. According to current research, software process improvement contributes to improvement of productivity, its Duality, reduction of development time and cost, and the prediction of the time limit for delivery, which means software process improvement affects competitive advantage among developers. The latest research is whether the investment for information technology substantially had effect on improvement of productivity. That is, software process improvement and maturity of software industries has influence upon economic efficiency and as a result, it plays an important role in whole industries. This research is that how does software process improvement using CMM (Capability Maturity Model) and SPICE (Software Process Improvement and Capability dEtermination) have a effect on factors of software engineering, and how does it have influence upon competitive advantage among SI firms. For this research, reusability, customizability, participation, and review & inspection are set to independent variable and process flexibility and process predictability are set to mediate Variable. Finally, competitive advantage among SI firms Is set to dependent variable. The targets for survey are laborers who work for SI firms. The result of this research is as follows: 1 ) Reusability, Customizability and participation is not rejected but review and Inspection is rejected in process flexibility which has significant level 0.05. 2) Reusability, Customizability and participation is not rejected but review and inspection Is rejected in process predictability which has significant level 0.05. 3) Process flexibility is not rejected and process predictability Is rejected in the competitive advantage of 51 industries which has significant level 0.05