• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.669-686
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• 1997

In this research, an object-oriented Petri net model for representing a flexible process plan is proposed, which is hierarchically multi-faceted for supporting planning, scheduling, and shop floor control functions. The multi-faceted process plan model consists of the following: a) an object model which represents on object-oriented data model, b) a static model which represents a process flow model with process alternatives, and c) a dynamic model which represents a process activity model with resources alternatives, of a flexible process plan. Petri nets allow the static and the dynamic process plan models to be represented in a unified formalism with an ease of model transformation. The multi-faceted process plan model suggested in this paper, is illustrated with a prismatic port in comprehensive detail.

• Journal of The Korean Association For Science Education
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• v.27 no.8
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• pp.724-742
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• 2007

The purpose of this study was to develop a scientific inquiry model that makes scientific inquiry accessible to science teachers as well as students. To develop a scientific inquiry model, we investigated the research process demonstrated by ten scientists who were working at academic research institutions or industrial research institutions. We collected data through scientists' journal articles, lab meetings and seminars, and observation of their inquiry process. After we analyzed the scientists' inquiry strategies and processes of inquiry, we finally developed the Scientist's Methodology of Investigation Process model named SMIP. The SMIP model consists of four domains, 15 stages, and link questions, such as "if, why", and "how". The SMIP model stressed that inquiry process is a selective process rather than a linear or a circular process. Overall, these findings can have implication science educators in their attempt to design instruction to improve the scientific inquiry process.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.793-798
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• 2008

Extreme value inference deals with fitting the generalized extreme value distribution model and the generalized Pareto distribution model, which are recently combined to give a single model, namely a two-dimensional non-homogeneous Poisson exceedance point process model. In this paper, we extend the two-dimensional non-homogeneous Poisson process model to include non-stationary effect or dependence on covariates and then derive the likelihood for the extended model.

• The Journal of Society for e-Business Studies
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• v.3 no.2
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• pp.141-160
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• 1998

In order to achieve a successful introduction of CALS, an enterprise model which is a concise description of what an enterprise does is required. The enterprise model mainly consists of a process model and a data model. The process model describes processes that create, change, combine, or destroy the entities within the enterprise. Several process modeling methodologies have been proposed. Each modeling methodology requires its own modeling view point, elements, and syntax. In developing a process model for CALS, these models created at different view points are required to analyze and design a system in a broad view. This paper aims at proposing an integration methodology for a process model. Specifically, IDEF0, IDEF3, and Petri Net are considered to be integrated. An IDEF0 model describing static functions of enterprise is transformed to an IDEF3 model describing behaviour of a system with additional information. Also, the IDEF3 model is transformed to a Petri Net model. These transformations will be automatically accomplished once the additional information for the transformation is provided.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.347-358
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• 2012

Purpose: Given the mixture components - process variables experimental data, we propose the strategy to find the proper combined model. Methods: Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components - process variables experiments depend on the mixture components - process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. Results: First we choose the reasonable starting models among the class of admissible product models and practical combined models suggested by Lim(2011) based on the model selection criteria and then, search for candidate models which are subset models of the starting model by the sequential variables selection method or all possible regressions procedure. Conclusion: Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. The strategy to find the proper combined model is illustrated with examples in this paper.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.6
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• pp.59-67
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• 2013

This paper presents a neural net type process model for enhancing learning compensation function in hot strip finishing rolling mill. Adequate input and output variables of process model are chosen, the proposed model was designed as single layer neural net. Equivalent carbon content, strip thickness and rolling speed are suggested as input variables, and looper's manipulation variable is proposed as output variable. According to simulation result using process data to show the validity of the proposed process model, neural net type process model's outputs give almost similar data to process output under same input conditions.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.82-87
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• 1998

In order to provide a manufacturing system with efficiency and flexibility to cope with the changes in shop floor status, the integration of process planning and operations scheduling is required. In this paper, an integrated system of process planning and operations scheduling based on the concept of process net model and genetic algorithm is suggested. The process net model includes the alternative process plans. The integrated system is applied for prismatic parts.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.435-446
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• 2000

Statistical process control(SPC) and engineering process control(EPC) are two strategies for quality improvement that have been developed independently. EPC seeks to minimize variability by adjusting compensatory variables in order to make the process level close to the target, while SPC seeks to reduce variability by monitoring and eliminating causes of variation. One purpose of this paper is to propose the IMA(0,1,1) model as the in-control process model. For the out-of-control process model we consider two cases; one is the case with a step shift in the level, and the other is the case with a change in the nonstationarity. Another purpose is to suggest the use of an integrated process control procedure with adjustment and monitoring, which can consider the proposed process model effectively. An integrated control procedure will improve the process control activity significantly for cases of the proposed model, when compared to the procedure of using either EPC or SPC, since EPC will keep the process close to the target and SPC will eliminate special causes.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

• 한국디지털정책학회:학술대회논문집
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• 2006.06a
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• pp.197-204
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• 2006

This paper tried to develop differentiation strategies of policy process in governance. Firstly, we reviewed model of policy making(output-oriented model and process-oriented model, normative or idealistic approach and realistic or empirical approach, rational model and cognitive model etc). Now gumi city is making the policy based on the process-oriented model, realistic or empirical approach, cognitive model. So gumi city was winner the test of provinces innovation in 2005. Therefore, when we make the policy, consider these factor: citizen and public service personnel participate policy making process and control policy quality.