• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.3
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• pp.130-134
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• 2016

Due to the need for advanced technologies in the automotive industry, the demand for lighter and safer vehicles has increased. Even though various nonferrous metals, like Aluminum, Magnesium and also Carbon Fiber Reinforced Plastic (CFRP), have been implemented in the automotive industry, a lot of technical research and development is still focused on ferrous metals. In particular, the market volume of High Strength Steel (HSS) parts and Ultra High Strength Steel (UHSS) by hot press forming parts has expanded significantly in all countries' automotive industries. A new tool steel, High Thermal-Conductivity Tool Steel (HTCS), for stamping punches and dies has been developed and introduced by Rovalma Company (Spain), and it is able to support better productivity and quality during hot press forming. The HTCS punches and dies could help to reduce cycle time due to their high thermal conductivity, one of the major factors in hot press forming operation. In this study, test dies were manufactured in order to verify the high thermal conductivity of HTCS material compared to SKD6. In addition, thermal deformation was inspected after the heating and cooling process of hot press forming. After heating and cooling, the test dies were measured by a 3D scanner and compared with the original geometry. The results showed that the thermal deformation and distortion were very small even though the cooling time was reduced by 2 seconds.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.12
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• pp.1647-1653
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• 2011

The cycle time in injection moulding greatly depends on the cooling time of the plastic part that is controlled by cooling channels. Cooling channels are required to facilitate the heat transfer rate from the die to the coolant without reducing the strength of the die. Employing layered manufacturing techniques (LMT), a die embedding conformal cooling channels can be fabricated directly while conventional cooling channels are usually made of straight drilled hole. Meanwhile, H13 tool steel is widely used as the die material because of its high thermal resistance and dimensional stability. However, H13 with a low thermal conductivity is not efficient for certain part geometries. In this context, the use of functionally graded materials (FGMs) between H13 and copper may circumvent a tradeoff between the strength and the heat transfer rate. This paper presents a method for modeling of conformal cooling channels made of FGMs.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.67-79
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• 2009

Because a product in the car industry has a short life cycle in recent years, the process planning and the manufacturing lines have to be changed frequently. Most of time, repositioning an existing facility and modifying used control information are faster than making completely new process planning. However, control information and control code such as PLC code are difficult to understand. Hence, industries prefer writing a new control code instead of using the existing complex one. It shows the lack of information reusability in the existing process planning. As a result, to reduce this redundancy and lack of reusability, we propose a SOS-Net modeling method. SOS-Net is a standard methodology used to describe control information. It is based on the Device Structure which consists of sensor information derived from device hardware information. Thus, SOS-Net can describe a real control state for automated manufacturing systems. The SOS-Net model is easy to understand and can be converted into PLC Code easily. It also enables to modify control information, thus increases the reusability of the new process planning. Proposed model in this paper plays an intermediary role between the process planning and PLC code generation. It can reduce the process planning and implementation time as well as cost.

• Design & Manufacturing
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• v.17 no.1
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• pp.56-63
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• 2023

In this study, the vibration signal of the mold was measured and analyzed to monitor the process information and characteristics during the press molding process. A necklace-type picture frame mold was used for press molding, and the vibration signal was measured by GY-61 acceleration sensor module attached to the surface of the upper (movable) mold base. The change of the vibration signal of the mold according to press speed was analyzed. As a result, the vibration signal had a large change at five sections: "Holder contact", "Punch contact and start of pressing", "End of pressing", "Mold open", and "Demolding". The time difference between "Punch contact and start of pressing" and "End of pressing" means the pressing time which is the actual time the material is molded under pressing pressure. The time intervals for each section, represented by the time interval between "Holder contact" and "Punch contact and start of pressing", can be used to compare and evaluate the press speed applied to the process. By comparing the vibration signals at 60 rpm and 90 rpm, the amplitude at the section of "Punch contact and start of pressing" increased as the press speed increased. This result means that as the press speed increases, more force and pressure is applied to the material. Also, the peak values of the other sections were found to increase as the press speed increased. It was found that the pressing time, the time interval between "Punch contact and start of pressing" and "End of pressing", decreases as the pressing speed increases. Similarly, press speed factor, the time interval between "Holder contact", and "Punch contact and start of pressing", is found to be shorter. Therefore, based on the result of this study, the pressing time, press speed, pressing(punching) pressure of each cycle can be monitored by measuring the vibration signal of the mold. Also, it was confirmed that the level and trend of process information and characterization can be evaluated as the change of the mold vibration during press molding.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.407-410
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• 1998

Configuration is a set of building block processes, a series of selection and combining parts or components which composes a whole thing. A whole thing could be such a configurable object as manufacturing product, network system, financial portfolio, system development plan, project team, etc. Configuration problem could happen during any phase of product life cycle: design, production, sales, installation, and maintenance. Configuration has long been one of cost and time consuming work, because only high salaried technical experts on product and components can do configuration. Rework for error adjustments of configurations at later process causes far much cost and time, so accurate configuration is required. Under the on-line electronic commerce environment, configuration problem solving becomes more important, because component-based sales should be done automatically on the merchant web site. Automated product search, order placement, order fulfillment and payment make that manual configuration is no longer feasible. Automated configuration means that all the constraints among components should be checked and confirmed by configuration engine automatically. In addition, technical constraints and customer preferences like price range and a specific function required should be considered. This paper gives an brief overview of configuration problems: characteristics, representation paradigms, and solving algorithms and introduce CRSP(Constraint and Rule Satisfaction Problem) method. CRSP method adopts both constraint and rule for configuration domain knowledge representation. A survey and analysis on web sites adopting configuration functions are provided. Future directions of configuration for EC is discussed in the three aspects: methodology itself, companies adopting configuration function, and electronic commerce industry.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.151-157
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• 1993

In this paper, we investigate the effects of yield randomness for lot-sizing in a multi-stage production system. The practical importance of incorporating yield randomness into production models has been emphasized by many researchers. Yield randomness, especially in semiconductor manufacturing, poses a mojor challenge for production planning and control. The task becomes even more difficult if the demand for final product is uncertain. An attempt to meet the demand with a higher level of confidence forces one to release more input in the fabrication line. This leads to excessive work-in-process (WIP) inventories which cause jobs to spend unpredictably longer time waiting for the machines. The result is that it is more difficult to meet demand with exceptionally long cycle time and puts further pressure to increase the safety stocks. Due to this spiral effect, it is common to find that the capital tied in inventory is the msot significant factor undermining profitability. We propose a policy to determine the quantity to be processed at each stage of a multi-stage production system in which the yield at each stage may be random and may need rework.

• Korean Journal of Computational Design and Engineering
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• v.16 no.5
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• pp.351-360
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• 2011

Product systems are quickly and frequently changed because Product Life Cycle is continuously reduced and adopting new product is steadily fast. Thus, various studies are progressed using simulation which is one of digital manufacturing. The research that is concerning simulation of control verification for shorten the commissioning which has a lot of trial and error is in progress. Also, simulation of control verification has strength that it can catch the errors in advance. However, a control program in simulation needs virtual factory for representation of control information. For this reason, excessive time and energy is put into controlling the virtual factory. So, in this paper, we construct library which is using exist data, in order to overcome limitation of these problems. Furthermore, we suggest methodology which can model and verify the process more speedy using library. Especially, we give body to the BB/BR Line process which has many altering equipment and need high technology effectively using physical and logical modeling. We can set up a control simulation environment very rapidly, as well as cut process time down using our suggestion.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.2
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• pp.8-11
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• 2006

Gas-assisted injection molding (GAIM) process reduces the required injection pressure during mold filling stage as well as the shrinkage and warpage of the part and cycle time. Despite of these advantages, this process needs new parameters and makes the application more difficult because gas and melt interact during the injection molding process. Important GAIM factors involved in this process are gas penetration design, locations of gas injection points, shot size, delay time to inject gas as well as common injection molding parameters. In this study, the experiments are conducted to investigate effects of GAIM process variables on the gas penetration for PP (Polypropylene) and ABS (Acrylonitrile Butadiene Styrene) moldings by changing the gas injection point. Taguchi method is used for the design of the experiments. When the gas is injected at a cavity's center, the most effective factor is the shot size. When the gas is injected at a cavity's end, the most effective factor is the melt temperature. The injection speed is also an effective factor in GAIM process.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.55-67
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• 2022

Sensor data can provide fault diagnosis for equipment. However, the cause analysis for fault results of equipment is not often provided. In this study, we propose an explainable convolutional neural network framework for the sensor-based time series classification model. We used sensor-based time series dataset, acquired from vehicles equipped with sensors, and the Wafer dataset, acquired from manufacturing process. Moreover, we used Cycle Signal dataset, acquired from real world mechanical equipment, and for Data augmentation methods, scaling and jittering were used to train our deep learning models. In addition, our proposed classification models are convolutional neural network based models, FCN, 1D-CNN, and ResNet, to compare evaluations for each model. Our experimental results show that the ResNet provides promising results in the context of time series classification with accuracy and F1 Score reaching 95%, improved by 3% compared to the previous study. Furthermore, we propose XAI methods, Class Activation Map and Layer Visualization, to interpret the experiment result. XAI methods can visualize the time series interval that shows important factors for sensor data classification.

• Clean Technology
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• v.27 no.2
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• pp.107-114
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• 2021

Material Life Cycle Assessment (MLCA) was performed to analyze the environmental impact characteristics of the Mg₂NiH_x-5 wt% CaO hydrogen storage composites' manufacturing process. The MLCA was carried out by Gabi software. It was based on Eco-Indicator 99' (EI99) and CML 2001 methodology. The Mg₂NiH_x-5 wt% CaO composites were synthesized by Hydrogen Induced Mechanical Alloying (HIMA). The metallurgical, thermochemical characteristics of the composites were analyzed by using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), specific surface area analysis (Bruner-Emmett-Teller, BET), and thermogravimetric analysis (TGA). As a result of the CML 2001 methodology, the environmental impact was 78% for Global Warming Potential (GWP) and 22% for Eutrophication Potential (ETP). In addition, as a result of applying the EI 99' methodology, the acidification was the highest at 43%, and the ecotoxicity was 31%. Accordingly, the amount of electricity used in the manufacturing process may have an absolute effect on environmental pollution. Also, it is judged that the leading cause of Mg₂NiH_x-5 wt% CaO is the addition of CaO. Ultimately, it is necessary to research environmental factors by optimizing the process, shortening the manufacturing process time, and exploring eco-friendly alternative materials.