• Polymer(Korea)
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• v.35 no.6
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• pp.574-579
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• 2011

3-Roll coating process as a key application technology for manufacturing automotive pre-painted metal-sheets has been studied. The 3-Roll coating system for this study consists of pick-up roll for picking up and distributing coating liquid from the reservoir, metering roll to properly meter coating liquid in metering gap regime, and applicator roll for directly transferring liquid into metal-sheet surface. Flow dynamics and operable coating windows of a polymeric paint (primer) with shear-thinning rheological property have been correlated with processing parameters such as speed ratio and metering gap between pick-up and metering rolls. In the uniform coating regime, dry coating thickness increased with increasing metering gap or decreasing speed ratio. Ribbing and cascade instabilities were observed in low speed and high speed ratio conditions, respectively. It is revealed that lower speed ratio makes severity and wavelength of the ribbing increase, aggravating flow instability in coating systems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.177-183
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• 2015

Incremental sheet metal forming is a manufacturing process to produce thin parts using sheet metals by a series of small incremental deformation. The process rarely needs dedicated dies and molds, thus, preparation time for the process is relatively short as to be compared to conventional metal forming. Spring back in sheet metal working is very common, which causes critical errors in dimensions. Incremental sheet metal forming is not fully investigated yet. Hence, incremental sheet metal forming frequently produces inaccurate parts. This paper proposes a method to minimize dimensional errors to improve shape accuracy of products manufactured by incremental forming. This study conducts experiments using an exclusive incremental forming machine and the material for these experiments are sheets of aluminum AL1015. This research defines a process parameter and selects a few factors for the experiments. The parameters employed in this paper are tool feed rate, tool diameter, step depth, material thickness, forming method, dies applied, and tool path method. In addition, their levels for each factor are determined. The plan of the experiments is designed using orthogonal array $L_8$ ($2^7$) which requires minimum number of experiments. Based on the measurements, dimensional errors are collected both on the tool contacted surfaces and on the non-contacted surfaces. The distances between the formed surfaces and the CAD models are scanned and recorded using a commercial software product. These collected data are statistically analyzed and ANOVAs (analysis of variances) are drawn up. From the ANOVAs, this paper concludes that the process parameters of tool diameter, forming depth, and forming method are the significant factors to reduce the errors on the tool contacted surface. On the other hand, the experimental factors of forming method and dies applied are the significant factors on the non-contacted surface. However, the negative forming method always produces better accuracy than the positive forming method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1144-1151
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• 2021

The pressing process is a compression process in which a product is made by applying force to a heated or unheated material to transform it into the desired shape. Due to the characteristics of press equipment that produces products through continuous compression for a short time, product defects occur continuously, and systems for solving these problems are being developed using various technologies. This paper proposes a real-time defect detection system based on an artificial intelligence algorithm that detects defects. By attaching various sensors to the press device, the relationship between equipment status and defects is defined and collected based on a big data platform. By developing an artificial intelligence algorithm based on the collected data and implementing the developed algorithm using an embedded board, we will show the practicality of the system by applying it to the actual field.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.179-188
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• 2018

Recently, blockchain technology has been recognized as one of the most important issues for the 4th Industrial Revolution which can be represented by Artificial Intelligence and Internet of Things. Cryptocurrency, named Bitcoin, was the first successful implementation of blockchain, and it triggered the emergence of various cryptocurrencies. In addition, blockchain technology has been applied to various applications such as finance, healthcare, manufacturing, logistics as well as public services. Distributed consensus algorithm is an essential component in blockchain, and it enables all nodes belonging to blockchain network to make an agreement, which means all nodes have the same information. For example, Bitcoin uses a consensus algorithm called Proof-of-Work (PoW) that gives possession of block generation based on the computational volume committed by nodes. However, energy consumption for block generation in PoW has drastically increased due to the growth of computational performance to prove the possession of block. Although many other distributed consensus algorithms including Proof-of-Stake are suggested, they have their own advantages and limitations, and new research works should be proposed to overcome these limitations. For doing this, above all things, we need to establish an evaluation method existing distributed consensus algorithms. Based on this motivation, in this work, we suggest and analyze assessment items by classifying them as efficiency and safety perspectives for investigating existing distributed consensus algorithms. Furthermore, we suggest new assessment criteria and their implementation methods, which can be used for a baseline for improving performance of existing distributed consensus algorithms and designing new consensus algorithm in future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• Applied Chemistry for Engineering
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• v.32 no.4
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• pp.379-384
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• 2021

A microneedle is a tool that used for drug delivery and diagnosis. Unlike general injections, the microneedle is short in length, enabling effective drug delivery while minimizing pain and risk of infection. Conventionally, microneedles have been manufactured precisely at a nanometer level based on microelectro mechanical systems (MEMS) technology, requiring expensive equipments & maintenance and complicated processes. To address the issues, 3D printing research has been conducted to fabricate microneedles simply, economically, and rapidly. Since 3D printing facilitates to manufacture prototypes and apply feedbacks, it is advantageous for the development and commercialization of microneedle for pharmaceuticals and cosmetics. Therefore, this review will introduce stereolithography (SLA), two-photon polymerization (2PP), dynamic light processing (DLP), continuous liquid interface production (CLIP), and fused deposition modeling (FDM) 3D printing technologies and also highlight research trends for microneedle production using them. Furthermore, the limitation of the current microneedle technology and the direction to be solved in the future will be discussed.

• Journal of Powder Materials
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• v.28 no.6
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• pp.470-477
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• 2021

Energy storage systems should address issues such as power fluctuations and rapid charge-discharge; to meet this requirement, CoFe₂O₄ (CFO) spinel nanoparticles with a suitable electrical conductivity and various redox states are synthesized and used as electrode materials for supercapacitors. In particular, CFO electrodes combined with carbon nanofibers (CNFs) can provide long-term cycling stability by fabricating binder-free three-dimensional electrodes. In this study, CFO-decorated CNFs are prepared by electrospinning and a low-cost hydrothermal method. The effects of heat treatment, such as the activation of CNFs (ACNFs) and calcination of CFO-decorated CNFs (C-CFO/ACNFs), are investigated. The C-CFO/ACNF electrode exhibits a high specific capacitance of 142.9 F/g at a scan rate of 5 mV/s and superior rate capability of 77.6% capacitance retention at a high scan rate of 500 mV/s. This electrode also achieves the lowest charge transfer resistance of 0.0063 Ω and excellent cycling stability (93.5% retention after 5,000 cycles) because of the improved ion conductivity by pathway formation and structural stability. The results of our work are expected to open a new route for manufacturing hybrid capacitor electrodes containing the C-CFO/ACNF electrode that can be easily prepared with a low-cost and simple process with enhanced electrochemical performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.128-135
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• 2021

WDM(Wavelength Division Multiplexing) is called a wavelength division multiplexing optical transmission method and is a next-generation optical transmission technology. Case company F has recently developed and sold PLC(Planar Lightwave Circuit), a key element necessary for WDM system production. Although Chinese processing companies are being used as a global outsourcing strategy to increase price competitiveness by lowering manufacturing unit prices, the average defect rate of products manufactured by Chinese processing companies is more than 50%, causing many problems. However, Chinese processing companies are trying to avoid responsibility, saying that the cause of the defect is the defective PLC Wafer provided by Company F. Therefore, in this study, the responsibility of the PLC defect is clearly identified through estimating the defect rate of PLC using the sampling inspection method, and the improvement plan for each cause of the PLC defect for PLC yeild improvement is proposed. The result of this research will greatly contribute to eliminating the controversy over providing the cause of defects between global outsourcing companies and the head office. In addition, it is expected to form a partnership with Company F and a Chinese processing company, which will serve as a cornerstone for successful global outsourcing. In the future, it is necessary to increase the reliability of the PLC yield calculation by extracting more precisely the number of defects.

• Steel and Composite Structures
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• v.44 no.1
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• pp.33-47
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• 2022

This paper presents a finite element model for predicting the monotonic behaviour of bolted endplate joints connecting steel-concrete composite walls and steel beams. The demountable Hollo-bolts are utilised to facilitate the quick installation and dismantling for replacement and reuse. In the developed model, material and geometric nonlinearities were included. The accuracy of the developed model was assessed by comparing the numerical results with previous experimental tests on hollow/composite column-to-steel beam joints that incorporated endplates and Hollo-bolts. In particular, the Hollo-bolts were modelled with the expanded sleeves involved, and different material properties of the Hollo-bolt shank and sleeves were considered based on the information provided by the manufacture. The developed models, therefore, can be applied in the present study to simulate the wall-to-beam joints with similar structural components and characteristics. Based on the validated model, the authors herein compared the behaviour of wall-to-beam joints of two commonly utilised composite walling systems (Case 1: flat steel plates with headed studs; Case 2: lipped channel section with partition plates). Considering the ease of manufacturing, onsite erection and the pertinent costs, composite walling system with flat steel plates and conventional headed studs (Case 1) was the focus of present study. Specifically, additional headed studs were pre-welded inside the front wall plates to enhance the joint performance. On this basis, a series of parametric studies were conducted to assess the influences of five design parameters on the behaviour of bolted endplate wall-to-beam joints. The initial stiffness, plastic moment capacity, as well as the rotational capacity of the composite wall-to-beam joints based on the numerical analysis were further compared with the current design provision.

• Journal of the Korean Institute of Gas
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• v.28 no.2
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• pp.76-83
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• 2024

In the semiconductor manufacturing process, the Diffusion process generates various reactive by-products. These by-products are deposited inside the pipes of post-processing and exhaust treatment systems, posing a potential risk of substantial dust explosions. In this study, three methods material verification, selection of analysis samples, and risk analysis were employed to address the substances produced during the Diffusion process. Among the materials handled in the Diffusion process, ZrO₂, TEOD, and E-DEOS were identified as raw material capable of generating by-product dust. Test for Minimum Ignition Energy and dust explosion were conducted on the by-products collected from each processing facility. The results indicated that, in the case of MIE, none of the by-products ignited. However, the dust explosion test revealed that ZrO₂ exhibited a maximum pressure of 7.6 bar and K_st value of 73.3 bar·m/s, its explosive hazard. Consequently, to mitigate such risks in semiconductor processes, it is excessive buildup.