• 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.

• The Journal of Society for e-Business Studies
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• v.4 no.3
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• pp.95-118
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• 1999

There have been many research papers and practical implementations on the various EC(Electronic Commerce) aspects such as merchant system, security, payment gateway, legal and policy issues. However, it is very hard to find the systematic approaches and business process models from the viewpoint of the company willing to start B2C(Business-To-Customer) EC. Therefore, we develop business process models for the planning, systems analysis and design, implementation, and operation of internet shopping mall to suggest a guideline and reference model for the realization of successful B2C EC.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.3
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• pp.260-265
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• 2004

In order to analyze the shaped drawing process, it is necessary that the friction boundary condition between dies and blanks should be worked out the accurate numerical friction models. But, the existing numerical models of the drawing may be large different from the actual conditions. In this paper, accurate analysis of the drawing process should be subjected. It is to develop accuracy of the numerical friction models and potentialize to apply for the high speed forming work in the drawing process. Therefore, the results should improve the accuracy, cause the energy saving for the drawing process and finally expand the applying areas of the results.

• Korean Journal of Computational Design and Engineering
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• v.17 no.4
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• pp.294-302
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• 2012

Process mining is a useful methodology that can be used for extracting user patterns in log files in order to discover efficient or inefficient processes in organizations. In general, it is used to find and reduce differences between pre-defined processes and actually executed processes in an organization. In this paper, we propose a method to improve processes in PDM/PLM systems based on process mining. In order to improve and detect the inefficient processes, we gathered event logs from PDM/PLM systems and derived process models using several process mining techniques such as ${\alpha}$-algorithm mining, heuristics mining, and fuzzy miner. By comparing original process models with process mining results, it is possible to detect differences between predefined processes and real ones; thereby we can build improved process models for future application.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.149-158
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• 1987

The Adoption/Diffusion of Innovations(New Product), a topic of study and research that has frown rapidly in the past few decades, deals with how a new product is adopted in a society. It is of high importance to marketing organizations because New Products must be brought out continuously in order to service. The purpose of this paper is to examine the Adoption/Diffusion Models for New product which will help to analyze the Adoption/Diffusion process of Adopters. There are a number of models that, with varying degrees of success, have been used to predict market acceptance of new product. In this paper, following types of new product Adoption/Diffusion Models was suggested. (1) Adoption Models : The Alternative Models of Adoption. The Rogers Model of the Innovation Decision Process. (2) Diffusion Models : First Purchase Models(Basic Models, Extension of the Basic Models), Repeat Purchase Models

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.4
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• pp.89-96
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• 2002

This paper aims to develop an intelligent model for predicting top-bead width for the robotic GMA(Gas Metal Arc) welding process using BP(Back-propagation) neural network and multiple regression analysis. Firstly, based on experimental data, the basic factors affecting top-bead width are identified. Then BP neural network model and multiple regression models of top-bead width are established. The modeling methods and procedure are explained. The developed models are then verified by data obtained from the additional experiment and the predictive behaviors of the two kind of models are compared and analysed. Finally the modeling methods, predictive behaviors md the advantages of each models are discussed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.4
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• pp.128-134
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• 2008

Models of the deposition heights in the uncontrolled laser aided direct metal deposition process are constructed for the enhancement of the process integrity. Linear and non-linear statistical models as well as fuzzy model are utilized as the modeling methods. The predictability of the models are evaluated with the values of the sum of square error. The algorithm to use the models in the feedback controlled system is suggested to increase the deposition height accuracy within a layer.

• Journal of Power System Engineering
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• v.6 no.2
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• pp.54-59
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• 2002

The principle of the FDM(fused deposition modeling) process is based on the layer by layer manufacturing technology, like other RP(rapid prototyping) process. In the FDM process, each layer may have different shape. Therefore, the built model may have stairs shape on its surface. This stairs shape is one of the serious problems in the FDM process. Thus in this study, cube models and spherical models were fabricated by FDM process to investigate the influence of injection amount on surface roughness. Models with various road width were also built to investigate the influence of road width on surface roughness. Surface roughness of the models was measured and analyzed. The result obtained in this study are expected to help selecting the part build orientation for optimum surface roughness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.231-238
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• 2014

Optimum lot size calculation for real world manufacturing environment has been focused since last few decades. Several extensions have been made to the basic economic order and production order quantity models to realize the possible practical situations in industry. However, focus on work-in-process inventory has been ignored relatively. This paper provides a comprehensive review of the models developed for group technology based manufacturing environment focusing on work-in-process inventory. Models have been extended from a perfect manufacturing conditions to an imperfect manufacturing situation considering rework, rejection and inspection. Optimum lot size has been evaluated using a simple algebraic optimization approach. Significant parameters are highlighted using sensitivity analysis for the developed models. Numerical example is used to illustrate the utilization of such models in day-to-day production setups and the impact of significant factors' variation on total cost and optimum lot size.

• Journal of the Ergonomics Society of Korea
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• v.25 no.3
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• pp.67-75
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• 2006

HVIMs consists of simulated driver models implemented with series of mathematical functions and computerized vehicle dynamic models. To effectively model the perception process, as a part of driver models, psychophysical nonlinearity should be considered not only for the single-modal stimulus but for the stimulus of multiple modalities and interactions among them. A series of human factors experiments were conducted using the primary sensory of visual and auditory modalities to find out the effects of auditory cues in visual velocity estimation tasks. The variations of auditory cues were found to enhance/reduce the perceived intensity of velocity as the level changed. These results indicate that the conventional psychophysical power functions could not applied for the perception process of the HVIMs with multi-modal stimuli. 'Ruled surfaces' in a 3-D coordinate system(with the intensities of both kinds of stimuli and the ratio of enhancement, respectively for each coordinate) were suggested to model the realistic perception process of multi-modal HVIMs.