• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.537-544
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• 2004

An effective methodology is reported for determining the optimal lot size of batch processing and storage networks which include uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, infernally consumed, transported to or from other sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sires while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of the global supply chain.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.5
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• pp.474-481
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• 2023

This paper is an experimental study on the optimal operating conditions of direct charging type electrospray for particulate matter collection. To perform the research, a direct charging type electrospray visualization system was configured to photograph the spray shape of microdroplets, and experiments were performed with varying electrode distance, flow rate, and applied voltage, which are the main factors affecting the particulate matter collection efficacy. Through image processing, the total number of microdroplets according to each condition was analyzed, and the number of microdroplets with a diameter of 1.5 mm or less was confirmed. In addition, by calculating the number of microdroplets per power consumption according to the applied voltage, the optimal operating conditions were derived in terms of energy consumption efficacy, and the microdroplet size distribution was analyzed under the optimal operating conditions. As a result of the experiment, it was confirmed that the optimal operating condition was at a flow rate of 10 mL/min and a voltage of -20 kV in case of 5 mm electrode distance, and at a flow rate of 15 mL/min and a voltage of -30 kV in case of 100 mm electrode distance.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.499-509
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• 2018

Recently, hybrid transactional memory (HyTM) has gained much interest from researchers because it combines the advantages of hardware transactional memory (HTM) and software transactional memory (STM). To provide the concurrency control of transactions, the existing HyTM-based studies use a bloom filter. However, they fail to overcome the typical false positive errors of a bloom filter. Though the existing studies use a global lock, the efficiency of global lock-based memory allocation is significantly low in multi-core environment. In this paper, we propose an efficient hybrid transactional memory scheme using near-optimal retry computation and sophisticated memory management in order to efficiently process transactions in multi-core environment. First, we propose a near-optimal retry computation algorithm that provides an efficient HTM configuration using machine learning algorithms, according to the characteristic of a given workload. Second, we provide an efficient concurrency control for transactions in different environments by using a sophisticated bloom filter. Third, we propose a memory management scheme being optimized for the CPU cache line, in order to provide a fast transaction processing. Finally, it is shown from our performance evaluation that our HyTM scheme achieves up to 2.5 times better performance by using the Stanford transactional applications for multi-processing (STAMP) benchmarks than the state-of-the-art algorithms.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.2
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• pp.123-129
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• 2022

Quartz (SiO2) has high abrasion and heat resistances and excellent chemical and mechanical properties; therefore, it is used in various industries, such as machinery, chemistry, optics, and medicine. Quartz is a high-hardness and brittle material and is classified as the topmost difficult-to-cut material, which is because of the cracking or chipping at the edge during processing. Corner wear, such as cracks and chippings that occur during cutting, is a major cause for the deterioration in the machining quality. Therefore, many researchers are investigating various techniques to process quartz effectively. However, owing to the mechanical properties of quartz, most studies have been conducted on grinding, micromachining, and microdrilling. Few studies have been conducted on quartz processing. The purpose of this study was to analyze the machining characteristics according to the machining factors during the slot machining of quartz using a cubic boron nitride (CBN) tool and to select the optimal machining conditions using the Taguchi method. The machining experiment was performed considering three process variables: the spindle speed, feed rate, and depth of cut. The cutting force and surface roughness were analyzed according to the processing conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.403-410
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• 1999

In this study, a parallel algorithm has been developed that can quickly solve the optiaml control problem of large-scale dynamic systems. The algorithm adopts the sequential quadratic programming methods and achieves domain decomposition-type parallelism in computing sensitivities for search direction computation. A silicon wafer thermal process problem has been solved using the algorithm, and a parallel efficiency of 45% has been achieved with 16 processors. Practical methods have also been investigated in this study as a way to further speed up the computation time.

• Smart Structures and Systems
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• v.3 no.1
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• pp.69-88
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• 2007

In this study, Field-Programmable Gate Arrays (FPGAs) are investigated as a practical solution to the challenge of designing an optimal platform for implementing algorithms in a wireless sensing unit for structuralhealth monitoring. Inherent advantages, such as tremendous processing power, coupled with reconfigurable and flexible architecture render FPGAs a prime candidate for the processing core in an optimal wireless sensor unit, especially when handling Digital Signal Processing (DSP) and system identification algorithms. This paper presents an effort to create a proof-of-concept unit, wherein an off-the-shelf FPGA development board, available at a price comparable to a microprocessor development board, was adopted. Data processing functions, including windowing, Fast Fourier Transform (FFT), and peak detection, were implemented in the FPGA using a Matlab Simulink-based high-level abstraction tool rather than hardware descriptive language. Simulations and laboratory tests were carried out to validate the design.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.397-412
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• 2011

Granular Computing has emerged as a unified and coherent framework of designing, processing, and interpretation of information granules. Information granules are formalized within various frameworks such as sets (interval mathematics), fuzzy sets, rough sets, shadowed sets, probabilities (probability density functions), to name several the most visible approaches. In spite of the apparent diversity of the existing formalisms, there are some underlying commonalities articulated in terms of the fundamentals, algorithmic developments and ensuing application domains. In this study, we introduce two pivotal concepts: a principle of justifiable granularity and a method of an optimal information allocation where information granularity is regarded as an important design asset. We show that these two concepts are relevant to various formal setups of information granularity and offer constructs supporting the design of information granules and their processing. A suite of applied studies is focused on knowledge management in which case we identify several key categories of schemes present there.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.211-212
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• 2011

스트림 프로세싱 시스템은 실시간 데이터 수집 장치와 대규모 분산 컴퓨팅 환경이 결합되어 데이터 생성과 가공을 통하여 다수의 결과를 병렬적으로 도출하는 분산 프로그래밍 모델이다. 본 논문에서는 프로세스간에 필수적으로 요구되는 유입데이터 버퍼 관리에 초점을 두고 있다. 데이터의 유입률에 따라 동적으로 분석 프로세스를 확장시킴으로서 프로세스간 버퍼의 크기를 제어하는 기법을 제안하며 시뮬레이션을 통하여 성능 분석을 하였다.

• Transactions of Materials Processing
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• v.9 no.3
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• pp.226-232
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• 2000

The optimal blank design method by sensitivity analysis has been applied to the formings of oil-pan, tailored blank and front panel as the examples. Die geometry is prepared by a commercial CAD system. Excellent results has been obtained between the numerical results and the target contour shapes. Through the investigation, the proposed systematic method of optimal blank design is found to be effective in the practical forming processes.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.77-89
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• 2004

A computer model is developed to assess optimal ground water pumping rates and optimal locations of wells in a coastal region. A sharp interface model is used to simulate the freshwater and salt water flows. Drawdown, upconing, saltwater intrusion and the contamination of well are considered in this model. A genetic algorithm with parallel processing is used to identify the optimal solution.