• Journal of Information Technology Services
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• v.23 no.1
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• pp.37-53
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• 2024

Recently, the application of microservice architecture has been increasing as information systems have shifted to cloud environments. The purpose of this paper was to analyze the case of applying microservice architecture to MES in the manufacturing field, summarize the results of how it was applied in practice, and find out the effects of the application. Based on the improvement project by applying microservice architecture to the existing steel manufacturing MES, 11 principles of microservice application were derived through literature research, and the implementation process and results were summarized according to these principles. In addition, through a comparison of systems in the service industry and the manufacturing industry, we investigated why the application of microservices was more active in the service industry and whether the application in the manufacturing industry can be expected to have the same effect. We also evaluated the results and changes in the overall system after implementation. In particular, we analyzed the SR (Service Request) processing status of users' requests for system changes and operators' requests to see how much the lead time was reduced. The results showed that 8 out of 11 microservice application principles were properly implemented according to the principles, but the remaining 3 were not applicable due to practical difficulties and organizational circumstances. Despite not following all of the principles, the project was able to be implemented without any problems, and the most noticeable change as a result of the microservices architecture was that the lead time was reduced by 9 days compared to the previous system. This proves that it is possible to quickly adapt to customer requirements, and it also proves that the system is more flexible and scalable than the existing monolithic system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.580-583
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• 2009

It is very important to minimize the maintenance cost on easy accessibility in the production information system, change of production process line, and system expansion for globalization of logistics and production in the steel and manufacturing. In this paper, we design applying design patterns of object-oriented as well as implement web-based integrated manufacturing management system using JSP for easy accessibility of users and reduction of maintenance cost on business expansion and system integration. In addition, The proposed MES system supports various functionality such as equipment master code management, equipment management, inspection management, repair management, failure management, and statistic management in detail.