Coating is a type of paint. It protects a product forming a film layer on the product and assigns various properties to the product. Coating is one of the fields which is being studied actively in the polymer industry. Importance of coating in various industries is more increased. However, mixing process has been performing in dependence on operator's experience. In this paper, we found the relationship between each data from coating formulation process. We propose a framework to analyze the coating formulation process as well. It can improve the coating formulation process. In particular, the suggested framework may reduce degradation and loss costs due to absence of standard data which is accurate formulation criteria. Also it suggests responses to errors which can be occurred in the future through the analysis of the error data generated in mixing step.
The research for coatings is one of the most popular and active research in the polymer industry. For the coatings, electronics industry, medical and optical fields are growing more important. In particular, the trend is the increasing of the technical requirements for the performance and accuracy of the coatings by the development of automotive and electronic parts. In addition, the industry has a need of more intelligent and automated system in the industry is increasing by introduction of the IoT and big data analysis based on the environmental information and the context information. In this paper, we propose an optimization model for the design of experiments based coating formulation data objects using the Internet technologies and big data analytics. In this paper, the coating formulation was calculated based on the best data analysis is based on the experimental design, modify the operator with respect to the error caused based on the coating formulation used in the actual production site data and the corrected result data. Further optimization model to correct the reference value by leveraging big data analysis and Internet of things technology only existing coating formulation is applied as the reference data using a manufacturing environment and context information retrieval in color and quality, the most important factor in maintaining and was derived. Based on data obtained from an experiment and analysis is improving the accuracy of the combination data and making it possible to give a LOT shorter working hours per data. Also the data shortens the production time due to the reduction in the delivery time per treatment and It can contribute to cost reduction or the like defect rate reduced. Further, it is possible to obtain a standard data in the manufacturing process for the various models.
Massive data occurred in a manufacturing place is able to fulfill very important roll to improve the manufacturing process. Domestic manufacturing business has been making an multilateral effort to react the change of manufacturing circumstance, but it undergoes many difficulties due to technical weakness. Coatings is a type of paint. It protect products by forming a film layer on the products and assigns various properties to those. The research of coatings is one of the fields studied actively in the polymer industry. The importance of the coatings in various industries is more increased. However, the industry still performs a mixing process in dependence on operator's experiences. In this paper, we propose a design for realtime monitoring system and data analysis verification TA to improve the manufacturing process using HW-SW integrated framework. Analysis results from the proposed framework are able to improve the coatings formulation process by collecting more quantitative reference data for work and providing it to work place. In particular, the framework may reduce the deterioration and loss cost which are caused by absence of a standard data as a accurate formulation criteria. It also may suggest a counterplan regarding errors which can be occurred in the future by deriving a standard calibration equation from the analysis using R and Design of Experiments about an error data generated in the mixing step.
Data visualization technology helps people easily understand various data and its analysis result, so usefulness of it is expected in the real industrial manufacturing sites. The large amount of data which is occurred at the manufacturing sites is able to fulfill very important roll to improve the manufacturing process. In this paper, we propose an information visualization for the manufacturing process optimization based on design of experimental and data analysis. The manufacturing process may be improved and be reduced cause of faulty by providing the easy-process analysis to understand the operation site through the information visualization of data analysis result.
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