• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.114-117
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• 2005

An expert system is a system that employs human knowledge captured in a computer to solve problem that ordinarily require human expertise. Well-designed expert systems imitate the reasoning processes experts use to solve specific problem. Specially, expert systems are used to the engineer in manufacturing industry for the process control, production management and system management. In this paper, we propose the design process expert system for product design process in manufacturing industry and we present introduction and contents of design process expert system methodology and software for the air purifier design system. This system will be helpful to improvement of design process for the air purifier production.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.3
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• pp.104-109
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• 2012

Recently, the deburring process which is last process of manufacture is one of the important process for complete product. The manual deburring process can cause not only higher error rate but also irregular shape and quality of product. Therefore, Shape Guided Automatic Deburring Machine has been developed to resolve the above problems. But the Shape Guided Automatic Deburring Machine have been applied only to produce a circular product. Therefore, this machine is difficult to apply to products of various shapes. To solve this problem, we would like to develop Generalized Shape Guided Automatic Deburring Machine applicable to various shapes. To this end, we have done the modeling and design using CATIA program and have performed machine simulation.

• Korean journal of food and cookery science
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• v.10 no.2
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• pp.138-141
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• 1994

Whole, peeled sweetpotatoes were subjected to four different processes: 15 min microwave heating followed by 15 min baking (1), 90 min baking (2), 15 min microwave heating (3), and 15 min boiling followed by 15 min microwave heating (4). Samples of green and cured roots were used in the study. Scanning electron photomicrographs revealed that cured roots contained larger numbers of starch granules in the parenchyma cells than green roots, most of them compounded. The starch in cooked green roots was gelatinized while for cured roots it was mostly hydrolyzed into dextrins and sugars. Starch in process (3) roots was mostly gelatinized while in process (1) and process (2) roots gelatinized starch appeared in little quantity, thus it was primarily converted to dextrins and sugars. The process (4) resulted in little conversion of starch. The process (1) product resulted in a similar product to the process (2) product.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.23-27
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• 2017

This paper aims to develop a prediction model for the product quality of a casting process. Prediction of the product quality utilizes an artificial neural network (ANN) in order to renovate the manufacturing technology of the root industry. Various aspects of the research on the prediction algorithm for the casting process using an ANN have been investigated. First, the key process parameters have been selected by means of a statistics analysis of the process data. Then, the optimal number of the layers and neurons in the ANN structure is established. Next, feed-forward back propagation and the Levenberg-Marquardt algorithm are selected to be used for training. Simulation of the predicted product quality shows that the prediction is accurate. Finally, the proposed method shows that use of the ANN can be an effective tool for predicting the results of the casting process.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2002.05a
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• pp.82-85
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• 2002

A systematic investigation for process design in deep drawing is necessary for quality improvement of drawn cups. This study has been concentrated mainly on the influence of process design scheme on product qualities in cylindrical cup drawing. Three types of process design scheme were chosen in this study. That is, Case 1 is to finish drawing a cup of 50m in diameter in one stage, Case 2 and Case 3 are redrawing the drawn cups of 55, 65 mm in diameter to the final size respectively. Though experiments the maximum drawing force in two-stage cup drawing could be reduced up to 35% as compared with that of one-stage cup drawing. In addition, the Case 2 and Case 3 processes showed better product qualities than the Case 1 process when comparing distributions of thickness, hardness, dimensional accuracy.

• Transactions of Materials Processing
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• v.11 no.8
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• pp.716-723
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• 2002

A systematic investigation for the process design in deep drawing is necessary to improve the quality of drawn cups. This study concentrates mainly on the influence of process desing scheme on the product qualities in cylindrical cup drawing. Three types of process design scheme were chosen in this study. Case 1 is to draw a finished cup of 50mm in diameter in one stage, Case 2 and Case 3 are redrawing the first drawn cups of 55, 65mm in diameter to the final size respectively. Through experiments the maximum drawing force in two-stage cup drawing can be reduced up to 24% as compared with that of one-stage cup drawing. In addition, Case 3 process results in better product qualities than the other two processes in terms of the distributions of thickness and hardness.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.325-334
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• 2015

Nowadays, crowdsourcing has become a popular concept and is widely used in many social, economical and technological areas. For consumer product design, crowdsourcing is implemented extensively with many cases. Although there has been a lot of research on the application of crowdsourcing for product design, the big picture of how factors influence the participartion of individuals from the crowd in a crowdsourcing project for product design has not yet been understood. This paper aims to investigate the relationships of crowd participation and influencing factors including: process, product, and reward. To do this, we conducted a survey on a crowd of engineering individuals and analyzed the collected data with data mining techniques. Main findings include the relationships of crowd participation versus process, product, and reward factors as well as regression models to predict crowd participation.

• The Research Journal of the Costume Culture
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• v.10 no.1
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• pp.49-59
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• 2002

The type of product and consumer characteristis have known to play an important role in the post-purchase behavior. The issue related to the effects of clothing type and sex on the process of consumer satisfaction formation, would be helpful to understand the past-purchase consumer behavior. Therefore, the objective of this study was to clarify differences in the process of satisfaction formation in relation to clothing type and sex. The study was conducted in three steps. Through the two steps, measurement instruments were developed. At the last step, judgement sampling method was utilized to collect the data and subjects were 614 university students. Factor analysis and path analysis were used to analyze the data. The process of consumer satisfaction formation in formal wear and casual wear showed some differences. In the case of format wear, only expressive product performance was found to play an important role in the process of consumer satisfaction formation. However in the case of casual wear, both expressive and instrumental product performances had influence upon clothing satisfaction directly or through consumption emotion. The results revealed a similar tendency in the process of satisfaction formation between male and female groups. However in the male group the consumption emotion had a greater effect on the process of consumer satisfaction formation than in the female group it did.

• IE interfaces
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• v.20 no.2
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• pp.112-120
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• 2007

As the market rapidly changes, the speed of new product development is highlighted as a critical element which determines the success of firms. While firms endeavor to accelerate the development speed, frequent iterations in a development process hinders the effort of acceleration. For this reason, many previous researches tried to find the optimal structure of the development process which minimizes the number of iterations. However, such researches have a limitation in that they can be applied to only a single-project environment. In a multi-project environment, waiting time induced by lack of resources also delays the process as well as the iterations do. In this paper, we propose dynamic sequencing method focusing on both iterations and waiting time for reducing the durations of development projects in a multi-project environment. This method reduces the waiting time by changing the sequence of development tasks according to the states of resources. While the method incurs additional iterations, they are expected to be offset by the reduced waiting time. The results of simulation show that the dynamic sequencing method dramatically improves the efficiency of a development process. Especially, the improvement is more salient as projects are more crowded and the process is more unbalanced. This method gives a new insight in researches on managing multiple development projects.

• Design & Manufacturing
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• v.16 no.3
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• pp.50-57
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• 2022

The qualities of the products produced by injection molding are strongly influenced by the process variables of the injection molding machine set by the engineer. It is very difficult to predict the qualities of the injection molded product considering the stochastic nature of the manufacturing process, since the processing conditions have a complex impact on the quality of the injection molded product. It is recognized that the artificial neural network(ANN) is capable of mapping the intricate relationship between the input and output variables very accurately, therefore, many studies are being conducted to predict the relationship between the results of the product and the process variables using ANN. However in the condition of a small number of data sets, the predicting performance and robustness of the ANN model could be reduced due to too many input variables. In the present study, the ANN model that predicts the length of the injection molded product for multiple combinations of process variables was developed. And the accuracy of each ANN model was compared for 8 process variables and 4 important process inputs that were determined by the feature selection. Based on the comparison, it was verified that the performance of the ANN model increased when only 4 important variables were applied.