• Journal of the Korea Safety Management & Science
• /
• v.14 no.3
• /
• pp.167-174
• /
• 2012

In the manufacturing process the most widely used $\bar{X}$ chart has been applied to control the process mean. Also, Accelerated Life Test(ALT) is commonly used for efficient assurance of product life in development phases, which can be applied in production reliability acceptance test. When life data has lognormal distribution, through censored ALT design so that censored ALT data has asymptotic normal distribution, $ALT\bar{X}$ control chart integrating $\bar{X}$ chart and ALT procedure could be applied to control the mean of process in the manufacturing process. In the situation that process variation is controlled, $Z_p$ control chart is an effective method for the very small fraction nonconforming of quality characteristic. A simultaneous control scheme with $ALT\bar{X}$ control chart and $Z_p$ control chart is designed for the very small fraction nonconforming of product lifetime.

• The Journal of Information Systems
• /
• v.14 no.3
• /
• pp.1-8
• /
• 2005

This paper formally defines a role-driven security and access control model of a business process in order eventually to provide a theoretical basis for realizing the secured business process management systems. That is, we propose a graphical representation and formal description of the mechanism that generates a set of role-driven security and access control models from a business process modeled by the information control net(ICN) modeling methodology that is a typical business process modeling approach for defining and specifying business processes. Based upon the mechanism, we are able to design and accomplish a secured business process management system that provides an unified resource access control mechanism of the business process management engine domain's and the application domain's. Finally, we strongly believe that the secured access control policies from the role-driven security and access control model can be easily transformed into the RBAC(Role-based Access Control) model that is a standardized security technology for computer and communications systems of commercial and civilian government organizations.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.350-350
• /
• 2000

Since the heat exchange system, such as the boiler of power plant, gas turbine, and radiator require a high rate heat efficiency and the efficiency of these systems is depended on the control methods. However, it is important f3r operator to understand control system of these systems. In order to properly apply control equipment to these process control systems, such as boiler, any other heat process, or process control system it is necessary to understand the basic aspects and operation principle of the process that relate control, interrelationships of the process characteristics, and the dynamics that are involved. Generally, PID controllers are used in these systems but it is difficult for engineer to understand the complex dynamics and the tuning method because of the coupling action and disturbance in the system loop. In this paper, we design an effective experimental system fur automatic control education and analyze its characteristics through experimental system and industrial plant control software to study how they can team automatic control system by experiments.

• Proceedings of the Safety Management and Science Conference
• /
• 1999.11a
• /
• pp.217-236
• /
• 1999

Engineering process control (EPC) is one of the techniques very widely used in process. EPC is based on control theory which aims at keeping the process on target. Statistical process control (SPC), also known as statistical process monitoring. The main purpose of SPC is to look for assignable causes (variability) in the process data. The combined SPC/EPC scheme is gaining recognition in the process industries where the process frequently experiences a drifting mean. This paper aims to study the difference between SPC and EPC in simple terms and presents a case study that demonstrates successful integration of SPC and EPC for a product in drifting industry. Statistical process control (SPC) monitoring of the special causes of a process, along with engineering feedback control such as proportional-integral-derivative (PID) control, is a major tool for on-line quality improvement.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.45
• /
• pp.237-246
• /
• 1998

In most statistical process control(SPC), control charts are used in which samples are taken and a suitable statistic is determined and plotted. In these control charts, control limits, ${\mu}{\pm}textsc{k{\sigma}}$, from which a decision is made are mostly ${\mu}{\pm}3{\sigma}$ and current literature in control charts are mainly concerned with detecting a shift in the mean. Therefore, when $\sigma$ is increased considerably after a long time, using control limits set at the first time causes a great deal of economic loss. In this paper the solutions to determine new control limits which maximizes the profit per unit produced and reduce $\sigma$ to economically optimal level for a certain cost when $\sigma$ is increased due to process deterioration are proposed. By applying new control limits, $\alpha$ error decreases considerably compared to apply initial control limits when $\sigma$ is increased due to process deterioration. Therefore, false alarm investigation cost drops down to the level of initial a error. And also this solution provides useful information regarding replacement of a process when the process is reviewed regularly.

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

• Journal of the Korean Society for Precision Engineering
• /
• v.12 no.3
• /
• pp.82-91
• /
• 1995

The purpose of this research is to develop a new real-time process control system. In this paper, a theoretical method for acquiring the control limit of cutting process(cutting surface) according to the required value(geometric tolerance) based on geometrical relations was propsed. In particular, the three following points are amphasized. Firstly, the process control was based on the cutting process, and the control limit was determined from the analysis of geometrical relations. Secondly, AMGD(Actual Measured Geometrical Deviation) was used as a new substitute value in process analysis. Thirdly, fuzzy reasoning was introduced to get the control limit flexibility according to the variations in the required value and general consideration of each measurememnt items.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.463-467
• /
• 1986

Here are summarized the trends and the problems of process control. And both the structure and the elements of digital computer based process control systems are also illuminated ; Briefly introduced the factors, of importance, influencing design strategy, and those to be considered when the process control is applied to physical systems using computer and computer-related instruments.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2004.04a
• /
• pp.425-429
• /
• 2004

Process adjustment Is a complimentary tool to process monitoring in process control. Process adjustment directs on maintaining a process output close to a target value by manipulating another controllable variable, by which significant process improvement can be achieved. Therefore, this approach can be applied to the 'Improve' stage of Six Sigma strategy. Though the optimal control rule minimizes process variability in general, it may not properly function when special causes occur in underlying process, resulting in off-target bias and increased variability in the adjusted output process, possibly for long periods. In this paper, we consider a responsive feedback control system and the minimum mean square error control rule. The bias in the adjusted output process is investigated in a general framework, especially focussing on stationary underlying process and the special cause of level shift type. Illustrative examples are employed to illustrate the issues discussed.

• Journal of Korean Society for Quality Management
• /
• v.32 no.2
• /
• pp.201-211
• /
• 2004

Process adjustment is a complimentary tool to process monitoring in process control. Process adjustment directs on maintaining a process output close to a target value by manipulating another controllable variable, by which significant process improvement can be achieved. Therefore, this approach can be applied to the 'Improve' stage of Six Sigma strategy. Though the optimal control rule minimizes process variability in general, it may not properly function when special causes occur in underlying process, resulting in off-target bias and increased variability in the adjusted output process, possibly for long periods. In this paper, we consider a responsive feedback control system and the minimum mean square error control rule. The bias in the adjusted output process is investigated in a general framework, especially focussing on stationary underlying process and the special cause of level shift type. Illustrative examples are employed to illustrate the issues discussed.