• 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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.12
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• pp.2949-2961
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• 1993

Dynamic cutting process can be represented by a closed-loop0 system consisted of machine tool structure and pure cutting process. On this paper, cutting system is modeled as a six degrees of freedom system using MARV(Modified Autoregressive Vector) model in face milling, and the modeled dynamic cutting process is used to predict dynamic cutting force component. Based on the double modulation principle, a dynamic cutting force model is developed. From the simulated relative displacements between tool and workpiece the dynamic force domponents can be calculated, and the dynamic force can be obtained by superposition of the static force and dynamic force components. The simulated dynamic cutting forces have a good agreement with the measured cutting force.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1950-1955
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• 1991

A fuzzy dynamic learning controller is proposed and applied to control of time delayed, non-linear and unstable chemical processes. The proposed fuzzy dynamic learning controller can self-adjust its fuzzy control rules using the external dynamic information from the process during on-line control and it can create th,, new fuzzy control rules autonomously using its learning capability from past control trends. The proposed controller shows better performance than the conventional fuzzy logic controller and the fuzzy self organizing controller.

• Journal of Korea Technology Innovation Society
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• v.4 no.1
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• pp.32-48
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• 2001

Many Korean companies have grown up through technology import, learning, development, innovation and export. This process is called as "the dynamic development process of technology". Among many companies which have grown up by way of this process, the Hyundai Motor Company has shown a very remarkable achievement in technological growth. In short, this paper deals with the growth of Korean companies in the view of the dynamic development process of technology. As a case study, the paper analyzes the Hyundai Motor Company.r Company.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.13-20
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• 2009

Development of a dynamic engine model is essential to predict and analyze of dynamic characteristics from a natural gas engine. Reducing the harmful exhaust emissions can be accomplished by a precise air-fuel ratio control. In this paper, the dynamic engine model was proposed and included mixture formation and intake process because the dynamic characteristics can be affected by the mixture components such as an air and a gaseous fuel. The air mass flow, the partial pressure ratio, and the gas constant are changed by variations of the components in the mixture formation and intake process. The dynamic engine model is applied to the natural gas engine for validation test. Experimental results show that the dynamic engine model is effective to predict the dynamic characteristics of the natural gas engine.

• Korean Journal of Computational Design and Engineering
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• v.15 no.3
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• pp.204-211
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• 2010

Recently, business process management has become an important concept to define and execute business process. During the execution of the collaborative business processes defined by the consensus with manufacturing enterprises, a lot of variations can be occurred by various internal and external factors related to business. From this reason, manufacturing enterprises have tried to seek for a technology to define and execute the collaborative business process systematically under the dynamic situations approving process variation. This study defines the collaborative business process among manufacturing enterprises at first and proposes its execution technology under the dynamic situations. Here, the proposed execution technology includes the authority management of each process, sub-process, and activity for security, the forced execution of the incomplete process containing the undefined sub-process, the re-execution in a certain range of business process for correcting errors, and the dynamic selection of sub-process. Furthermore, this study implements a prototype system to check the validity of its application under the dynamic situations.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.175-190
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• 1997

Organizational change projects such as Business Process Redisign (BPR) have been perceived to incur high risk due to their high management complexity, enterprise-wide impace, and steep project cost. This research intends to reduce such risk by developing a systematic process redesign methods, called Dynamic Process Modeling (DPM) method. DPM integrates the customer-oriented business process modeling technique with computerized visual simulation technique to promote better understanding of the target process and enable performance simulation of the proposed redesign alternatives prior to actual BPR implementations. For the cusstomer-oriented process modeling, we propose Dynamic-Event Process Chain (Dynamic-EPC) extending from the conceptual customer process model, Event-Process Chain (EPC). We compare DPM with four other implementation-level process modeling methods over eight criteria and demonstrate its effectiveness by applying it to the real-world hospital BPR case.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.122-132
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• 1999

This study describes a dynamic model of the hydroforming process which is used for precision forming of sheet metals. To help the controller design for the control of the forming pressure needed for this process as well as to investigate the effect of system parameters on the dynamic behavior, dynamic modeling is performed with emphasis on hydraulic servo system which actuates the forming machine. Since the model contains several unknown parameters, these were estimated via a least square parameter identification method. Based upon the identified model, a series of simulations were performed for various operating conditions. The results were compared with those of the experiments to verify the validity of the proposed model. The comparison study shows that the proposed dynamic model can describe dynamic behavior of the forming pressure of the hydroforming process to desirable accuracy.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.38 no.2 s.115
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• pp.1-8
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• 2006

In this study a process simulation method was used to analyze the accumulation phenomena of anionic starch in the process white water as the closure level of a fine paper making process is increased. A pilot paper machine was used as a model process. Dynamic simulations of the influence of white water usage ratio and uncoated broke addition ratio on the variation of process variable was monitored as a function of time. Results from the dynamic simulations showed that the volume of reservoirs affected the dynamic behavior of the process. The dynamic behavior of flow rate and dissolved starch concentration in process units were different from each other. The speed of the change of dissolved starch concentration in process units was depend on the starting point of the change of dissolved starch concentration, the length of circulation loop, and the volume of reservoirs.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.263-278
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• 2004

This paper reviews dynamic programming (DP), surveys approximate solution methods for it, and considers their applicability to process control problems. Reinforcement Learning (RL) and Neuro-Dynamic Programming (NDP), which can be viewed as approximate DP techniques, are already established techniques for solving difficult multi-stage decision problems in the fields of operations research, computer science, and robotics. Owing to the significant disparity of problem formulations and objective, however, the algorithms and techniques available from these fields are not directly applicable to process control problems, and reformulations based on accurate understanding of these techniques are needed. We categorize the currently available approximate solution techniques fur dynamic programming and identify those most suitable for process control problems. Several open issues are also identified and discussed.