• Communications for Statistical Applications and Methods
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• 제7권3호
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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.

• 산업경영시스템학회지
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• 제10권16호
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• pp.39-51
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• 1987

This paper deals with the case analysis of second order processes under sampled-data. Proportional Integral-Derivative(PID) control, and development of Decision Support Systems(DSS) for such processes. In this paper three techniques were described for identifying the dynamics of closed loop stable processes. The first, called pulse testing is a frequency-domain method, which yields the frequency response diagram of an open loop process. The second is a time-domain method which yields the gain and time constants of the process model. The third technique is based on step response and gives the parameters of PID controllers. The development of DSS design programs consisting of above three techniques will provide very powerful tools in the microcomputer based process control.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2003년도 추계학술대회
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• pp.55-63
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• 2003

Workflow Management System (WFMS) is a software system to support an efficient execution, control and management of complex business processes. Since traditional commercial systems mainly focus on automating processes, they don't have methods for enhancing the task performer's efficiency. In this paper, we propose a new method of executing business processes more efficiently in that a whole process is scheduled considering the degree of the participants' workload. The method allows managing the largest constraints among constituent resources of the process. We utilize DBR scheduling techniques to develop the method. We first consider the differences between workflow process models and DBR application models, and then develop the modified drum, buffer and rope. This leads us to develop WF-DBR (WorkFlow-DBR) that can control the proper size of the task performers' work list and arrival rate of process instances. Use of WF-DBR improves the efficiency of the whole process as well as the participants' working condition. We then carry out a set of simulation experiments and compare the effectiveness of our approach with that of scheduling techniques used in existing systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.248-250
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• 1986

This paper explain application of expert system techniques from the latest theories of artificial intelligence to industrial process control. This controller continuously monitors a loop's response to disturbances and adapts the tuning parameters (P.I.D) to provide the best response to load upset or set-point change.

• 경영과학
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• 제10권2호
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• pp.111-120
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• 1993

The most important factors for a product to survive in the market are cost and quality. In recent years, quality proceeds to cost. There are many techniques of use to improve the quality of a product. One of the techniques is applying statistical methods (especially Taguchi method) to real operational conditions for a continuous manufacturing process in P company. There are 91 factors to control in the process. So, we predetermined 7 main effect factors and 6 interactive effect factors by statistical methods and advices of engineers. With these 13 factors, we determined the optimal level of operations for the process.

• Industrial Engineering and Management Systems
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• 제8권3호
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• pp.139-147
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• 2009

Control charts are used to distinguish between chance and assignable causes in the variability of quality characteristics. When a control chart signals that an assignable cause is present, process engineers must initiate a search for the assignable cause of the process disturbance. Identifying the time of a process change could lead to simplifying the search for the assignable cause and less process down time, as well as help to reduce the probability of incorrectly identifying the assignable cause. The change point estimation by likelihood theory and the built-in change point estimation in a control chart have been discussed until now. In this article, we discuss two kinds of process change point estimation when the CUSUM ($\bar{x}$, s) control chart for monitoring process mean and variance simultaneously is operated. Throughout some numerical experiments about the performance of the change point estimation, the change point estimation techniques in the CUSUM ($\bar{x}$, s) control chart are considered.

• 대한안전경영과학회지
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• 제10권3호
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• pp.43-53
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• 2008

This study is carried out for the fire safety of the factory building, the fire risk reduction measure in compliance with an example approached in fire risk reduction systematically, contribute to reduce the fire risk. The analytical fire risk process of discovering, identifying, estimating and evaluating risk and control measure as risk reduction measures are core concept, applies loss prevention with loss control techniques. The painting process in the workplace where the fire hazard and death accident accompanies coexists. Loss prevention problem of creation prevention of dangerous atmosphere at workplace is health and human services problem of normal circumstances, must be inspected with problem of combustible gases at the time of fire explosion. Static electricity measure accomplished the risk control process thoroughly as the fire risk reduction process model with the ignition sources measure which is presented. Fire risk from within organizing will be able to classify with each field by detailedly but risk treatment process will be able to apply basically all the same concept. Consequently about risk management example from before, this study is proposed risk management techniques that standardized rightly in the actual condition of organization with one plan, with discovery of fire risk, the feedback process in compliance with a fire risk reduction and the review which control the result is joint responsibility of engineer, technical expert and manager as part of safety management to practice with the fact must be supervised.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 1999년도 추계학술대회
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• pp.217-236
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• 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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.214-217
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• 1987

In this paper self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in multiple ARMA process. This process is simplified as independent SISO ARMA process having offset terms. This offset was considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the parameter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results considers well with the analysis in case of linear interconnection.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.560-565
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• 1986

For the control of chemical process, optimal value of the process should be known at first. And process simulation is the previous step of optimal value calculation. However it is not a simple work to analyze chemical process system. Especially for the large scale chemical process system, many difficulties such as non-linearity and complexity caused by recycle streams should be overcome. In this paper, three strategies of large scale chemical process analysis were explained and discussed with case studies.