• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.1
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• pp.11-18
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• 2020

The emergence of the flow-through cell (FTC) method has made up for the limitations of previous dissolution test methods, but the high cost of the FTC dissolution devices have seriously hindered the progression of research and application of the FTC. This new design uses a peristaltic pump to simulate the sinusoidal flow rate of a piston pump. The flow profile of each peristaltic pump was sinusoidal with a pulsation of 120 ± 1 pulses per minute, and the flow rate ranged from 1.0 - 36.0 mL/min. The flow control of each channel was adjusted independently so the flow errors of the seven channels were close to 2%. The structure of the system was simplified, and the cost was reduced through manual sampling and immersing the FTC in a water bath. The dissolution rate of the theophylline and aminophylline films was determined, and good experimental results were obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.36-42
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• 2021

With recent developments in the Fourth Industrial Revolution, the manufacturing industry has changed rapidly. Through key aspects of Fourth Industrial Revolution super-connections and super-intelligence, machine learning will be able to make fault predictions during the foam-making process. Polyol and isocyanate are components in polyurethane foam. There has been a lot of research that could affect the characteristics of the products, depending on the specific mixture ratio and temperature. Based on these characteristics, this study collects data from each factor during the foam-making process and applies them to machine learning in order to predict faults. The algorithms used in machine learning are the decision tree, kNN, and an ensemble algorithm, and these algorithms learn from 5,147 cases. Based on 1,000 pieces of data for validation, the learning results show up to 98.5% accuracy using the ensemble algorithm. Therefore, the results confirm the faults of currently produced parts by collecting real-time data from each factor during the foam-making process. Furthermore, control of each of the factors may improve the fault rate.