• Design & Manufacturing
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• v.15 no.1
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• pp.48-56
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• 2021

The quality of products produced by injection molding process is greatly influenced by the process variables set on the injection molding machine during manufacturing. It is very difficult to predict the quality of injection molded product considering the stochastic nature of manufacturing process, because the process variables complexly affect the quality of the injection molded product. In the present study we predicted the quality of injection molded product using Artificial Neural Network (ANN) method specifically from Multiple Input Single Output (MISO) and Multiple Input Multiple Output (MIMO) perspectives. In order to train the ANN model a systematic plan was prepared based on a combination of orthogonal sampling and random sampling methods to represent various and robust patterns with small number of experiments. According to the plan the injection molding experiments were conducted to generate data that was separated into training, validation and test data groups to optimize the parameters of the ANN model and evaluate predicting performance of 4 structures (MISO1-2, MIMO1-2). Based on the predicting performance test, it was confirmed that as the number of output variables were decreased, the predicting performance was improved. The results indicated that it is effective to use single output model when we need to predict the quality of injection molded product with high accuracy.

• Design & Manufacturing
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• v.18 no.3
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• pp.71-80
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• 2024

Sink marks are a common defect that occurs due to differences in shrinkage in areas with significant thickness variations in injection-molded parts. In this paper, we investigated the reduction of sink marks and the improvement of gas venting in injection molding processes using External Gas Injection (EGI). A mold was designed with considerations for EGI core pins, O-ring grooves to prevent gas leakage, and ejector-pin sealing. The sink marks were then examined through a series of experiments. When the delay time for injecting compressed air was set to 2.2 seconds, the depth of the sink marks was minimized. However, when the delay time was either too short or too long, the depth of the sink marks increased. There was almost no difference in the depth of the sink marks at discharge pressures of 30 and 50 bar of compressed air, but the sink marks were significantly reduced at a discharge pressure of 70 bar. Under the conditions of a 2.2-second delay time and a supply pressure of 70 bar, the smallest depth, 0.594 ㎛, was observed when the supply time was between 6 and 7 seconds. This represents a reduction of approximately 94% compared to the sink mark depth of 10.078 ㎛ observed with conventional injection molding. To verify the gas venting effect of compressed air injection, an experiment was conducted using non-dried PC. The silver streaks that appeared on the exterior of the molded part were completely eliminated when the air supply pressure was set to 20 bar. This indicates that by injecting compressed air into the mold cavity before injecting the resin, the appearance quality of the injection-molded part can be improved without the need to dry the resin in advance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.1
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• pp.113-119
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• 2013

Despite rapid changes in the structure of industry, manufacturing remains a key industry for economic progress, promotion of trade, increased employment, and the creation of new industries. Production technologies are essential for strengthening the competitiveness of small- and medium-sized manufacturing industries. However, it is very difficult to standardize and systematically propagate production technology from an experienced worker to an inexperienced worker because these technologies are generally improved by the skilled people in a workshop. In this study, we introduce a Web-based platform system consisting of a knowledge authoring tool, technology database, semantic database, and Web portal service for sharing production technologies for the exterior housing parts of mobile products. By investigating various cellular phone designs, reference form factors for three types of mobile phone housings were designed based on the standard features. In addition, several manufacturing technologies and considerable information such as reference mold designs and molding conditions optimized using CAE and recent R&D outputs are stored in this system.