• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.1
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• pp.25-33
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• 2021

This paper presents the development process for airbag safety devices fitted in motorcyclists' garments. Motorcycle riders often sustain multiple injuries in crashes since rider post-impact kinematics depend on several variables. This study proposes a newly inflatable safety system connected to the motorcycle by a cable. An airbag device with a mechanical triggering system is deployed when the cable detaches from its mounting clip. Airbag filling tests are performed to determine the mixing ratio of compressed gases with the severance of temperature. To estimate the airbag effectiveness to reduce riders' injuries, numerical analysis is performed using the finite element method. A comparative analysis (i.e., with and without the chosen device) was conducted to evaluate its protective efficacy. Prototype garments based on the proposed design have been created and have undergone sled tests. The proposed safety device could also be beneficial in accidents during other sports activities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.79-86
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• 2017

This research focused on deciding optimal manufacturing WIP (Work-In-Process) limit for a small production system. Reducing WIP leads to stable capacity, better manufacturing flow and decrease inventory. WIP is the one of the important issue, since it can affect manufacturing area, like productivity and line efficiency and bottlenecks in manufacturing process. Several approaches implemented in this research. First, two strategies applied to decide WIP limit. One is roulette wheel selection and the other one is elite strategy. Second, for each strategy, JIT (Just In Time), CONWIP (Constant WIP), Gated Max WIP System and CWIPL (Critical WIP Loops) system applied to find a best material flow mechanism. Therefore, pull control system is preferred to control production line efficiently. In the production line, the WIP limit has been decided based on mathematical models or expert's decision. However, due to the complexity of the process or increase of the variables, it is difficult to obtain optimal WIP limit. To obtain an optimal WIP limit, GA applied in each material control system. When evaluating the performance of the result, fitness function is used by reflecting WIP parameter. Elite strategy showed better performance than roulette wheel selection when evaluating fitness value. Elite strategy reach to the optimal WIP limit faster than roulette wheel selection and generation time is short. For this reason, this study proposes a fast and reliable method for determining the WIP level by applying genetic algorithm to pull system based production process. This research showed that this method could be applied to a more complex production system.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.2
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• pp.108-115
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• 1999

This paper proposes the robot inverse calibration method using a neural networks. A highorder networks called Pi-Sigma networks has been used. The Pi-Sigma networks uses linear summing units in the hidden layer and product unit in output layer. The inverse calibration model which compensates the difference of joint variables only between measuring value and analytic value about the desired pose(position orientation) of a robot is proposed. The compensated values are determined by using the weights obtained from the learning process of the neural networks previously. To prove the reasonableness the SCARA type direct drive robot(4-DOF) and anthropomorphic robot(6-DOF) are simulated. It shows that the proposed calibration method can reduce the errors of the joint variables from $\pm$3 to $\pm$0.1.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.89-95
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• 1997

Welding technique is widely applied to general industry such as pressure vessel for chemical plant, pipe system, heavy industry, and automobile. There are some points which must be considered when robot system is used in welding automation process for productivity improvement. Welding quality is governed by heat input, and this quantity can be different according to shape, property, and thick of material . For desired heat input , weld input parameters such as welding voltage, current, and welding velocity must be determined with those consideration. Until now these parameters have been determined mainly by experience of operator. In this study, the size of welding zone was predicted by fuzzy rules were constructed from the relation between welding variables and weld pool size. Inverse model method which welding control input for welder is determined with optimum voltage and current by fuzzy controller is validatied by computer simulation.

• IE interfaces
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• v.23 no.3
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• pp.229-238
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• 2010

Virtual metrology (VM), a critical component of semiconductor manufacturing, is an efficient way of assessing the quality of wafers not actually measured. This is done based on a model between equipment sensor data (obtained for all wafers) and the quality characteristics of wafers actually measured. This paper considers principal component regression (PCR), partial least squares regression (PLSR), kernel PCR (KPCR), and kernel PLSR (KPLSR) as VM models. For each regression model, two cases are considered. One utilizes all explanatory variables in developing a model, and the other selects significant variables using the genetic algorithm (GA). The prediction performances of 8 regression models are compared for the short- and long-term etch process data. It is found among others that the GA-KPLSR model performs best for both types of data. Especially, its prediction ability is within the requirement for the short-term data implying that it can be used to implement VM for real etch processes.

• International Journal of Quality Innovation
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• v.1 no.1
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• pp.89-96
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• 2000

Evolutionary operation (EVOP) is a continuous improvement system which explores a region of process operating conditions by deliberately creating some systematic changes to the process variable levels without jeopardizing the product. It is aimed at securing a satisfactory operating condition in full-scale manufacturing processes, which is generally different from that obtained in laboratory or pilot plant experiments. Information on how to improve the process is generated from a simple experimental design. Traditional EVOP procedures are established on the assumption that the variance of the response variable should be small and stable in the region of the process operation. However, it is often the case that process noises have an influence on the stability of the process. This process instability is due to many factors such as raw materials, ambient temperature, and equipment wear. Therefore, process variables should be optimized continuously not only to meet the target value but also to keep the variance of the response variables as low as possible. We propose a scheme to achieve robust process improvement. As a process performance measure, we adopted the mean square error (MSE) of the replicate response values on a specific operating condition, and used the Kruskal-Wallis test to identify significant differences between the process operating conditions.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.268-283
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• 2016

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.100-105
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• 2003

With the recent development of machining technology, high speed machining process is widely used for-the mold and difficult-to -cut-materials machining since it allows achieving high productivity and surface quality. However, during the high speed machining process, high cutting speed and feed rate can cause abrupt tool life decrease due to rapid rising of the cutting tool temperature. Such situation may cause increase of machining cost. Thus, in this study, developed optimization algorithm is applied to determine optimal machining variables for multiple high speed machining. The R-T characteristic curve for machining economics problems with a linear-lorarithmic tool life model is determined by applying sensitivity analysis. finally, a series of high speed machining experiments are performed to determine the desired optimal machining variables, and the results are analyzed.

• Journal of Distribution Science
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• v.15 no.5
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• pp.17-28
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• 2017

Purpose - Considering the environmental issues in corporate management is now a necessity, not an option. In addition, consumers' interest in health and environment has increased rapidly. This study aims to investigate how the management style that pursues environmental protection affects the various outcomes at each management process such as planning, producing and supervising process. Research design, data, and methodology - We surveyed 319 manufacturing companies from April 1 to April 30, 2016. Green purchasing, environmental technology management and management support are selected as independent variables and firm performances as dependent variables. Three analyses including factor, regression and moderating were conducted. Results - Regression analysis was performed to set up hypotheses. Consequently, the total six hypotheses were adopted and then innovative management style showed moderating effect. Conclusions - Companies should consider environmental factors to improve the financial performance in the long term. Especially the cooperative style enhances financial performance by implementing eco-friendly design in cooperation with customers. Also, eco-friendly activities with suppliers could have direct environmental protection effects. Therefore, a manufacturer needs to cooperate with both suppliers and customers to maximize the protection effect. The production of eco-friendly products and implementing eco-friendly design with customers positively affect product quality.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.5
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• pp.81-87
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• 2015

In this paper, the finite element method was used for the flow and strength analysis of aluminum alloy under friction stir welding. The simulations were carried out using Sysweld s/w, and the modeling of the sheet was executed using Unigraphics NX6 s/w. The welding variables for the analysis were the shoulder diameter, rotating speed, and welding speed of the tool. Additionally, a three-way factorial design method was applied to confirm the effect of the welding variables on the flow and strength analysis with variance analysis. From these results, the rotating speed had the greatest influence on the maximum temperature, and the maximum temperature was $578.84{\pm}12.72$ at a confidence interval of 99%. The greater the rotating speed and shoulder diameter, the greater the difference between maximum and minimum temperature. Furthermore, the shoulder diameter had the largest influence on von Mises stress, and the von Mises stress was $184.54{\pm}12.62$ at a confidence interval of 99%. In addition to the increased shoulder diameter, welding speed, and rotating speed of the tool increased the von Mises stress.