• Journal of Korean Society for Quality Management
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• v.32 no.3
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• pp.109-125
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• 2004

This paper deals with an optimal process control problem in production of hull structural steel plate with high defective rate. The main quality characteristic(dependent variable) is the internal quality(defect) of plates and is dependent on process parameters(independent variables). The dependent variable(quality characteristics) has three categorical ordinal data and there are 35 independent variables(29 continuous variables and 6 categorical variables). In this paper, we determine the main factors and to develop the mathematical model between internal quality predicted probabilities and the main factors. Secondly, we find out the optimal process condition of main factors through analysis of variance(ANOVA) using simulation. We consider three models to obtain the main factors and the optimal process condition: linear, quadratic, error models.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.368-371
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• 2008

The optimal operation condition of gasifier is one of the most important parameters to increase efficiency and reliability in IGCC plant. Also the prediction of the syngas composition and quantity must be predicted to carry out process design of the gasification plant. However, the gasifier process licensor are protective with information on process design and optimal gasifier design conditions. So, the most of process studies in the engineering company for gasification plant have carried out to look for key parameters and optimal design conditions using several prediction methods. In this paper, we present the estimated preliminary optimal operation condition of the 300MW Demonstration Entrain Flow Gasifier using Aspen Plus. The gasifier operation temperature considering slag flow was predicted by FactSage software and Annen Model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.946-949
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• 2005

It is very a time-consuming and error-prone process to obtain the optimal injection condition, which can produce good injection molding products in some operational variation of facilities, from a seed injection condition. This study proposes a new approach to search the optimal injection molding condition using a neural network and a genetic algorithm. To estimate the defect type of unknown injection conditions, this study forces the neural network into learning iteratively from the injection molding conditions collected. Major two parameters of the injection molding condition - injection pressure and velocity are encoded in a binary value to apply to the genetic algorithm. The optimal injection condition is obtained through the selection, cross-over, and mutation process of the genetic algorithm. Finally, this study compares the optimal injection condition searched using the proposed approach. with the other ones obtained by heuristic algorithms and design of experiment technique. The comparison result shows the usability of the approach proposed.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.71-74
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• 2001

Using the Taguchi method, optimum process condition of lead frame blanking has been determined in the point of view of shape of blanked profile. As the main process parameters, clearance, strip holding pressure and bridge width are selected. According to the orthogonal array table, three levels of experiment have been carried out for each factors. The optimal blanking condition is analyzed with the SN ratio. It has been verified that the optimal process condition can be determined with a combination of basic blanking experiment and experiment design method. Both the effect of each factors and gain can be judged in the quantitative manners from the analysis of SN ratio.

• Transactions of Materials Processing
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• v.11 no.2
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• pp.132-137
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• 2002

Using the Taguchi method, optimum process condition of lead frame blanking has been determined in the point of view of shape of blanked profile. As the main process parameters, clearance, strip holding pressure and bridge width are selected. According to the orthogonal array table, three levels of experiment have been carried out for each factor. The optimal blanking condition is analyzed with the SN ratio. It has been verified that the optimal Process condition can be determined with a combination of basic blanking experiment and experiment design method. Both the effect of each factor and gain can be judged in the quantitative manner from the analysis of SN ratio.

• Transactions of Materials Processing
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• v.26 no.6
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• pp.348-355
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• 2017

In recent years, dissimilar materials such as aluminum, magnesium, titanium, and advanced high strength steel are widely used in automotive body due to environment concerns and fuel consumption. Therefore, joining technology is important for assembling components made of dissimilar materials. In this study, friction stir hole clinching (FSHC) was proposed as a new mechanical joining method to join dissimilar materials. This process stirs and heats the upper sheet, forming mechanical interlocking with the lower sheet. The feasibility of this FSHC process was verified by comparing cross-section of joint in FSHC and hole clinching process under the same processing condition. Taguchi method was also applied to the FSHC process to estimate the effect of process parameters on joint strength and obtain optimal combination of process parameters. Joint strength of FSHC with optimal process condition was compared to that of FSHC with initial process condition as well as that of hole clinching with optimal process condition. Results showed that the FSHC process was useful for joining dissimilar materials, even if the formability of materials was low.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.111-117
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• 2002

In most machining companies, operators decide the cutting condition, a pair of spindle speed (5) and table federate (F) by experience and subjective judgment. As cutting conditions are determined by operators' experience and ability, inconsistent cutting conditions are given in same operating conditions. The objective of this study is to develop the cutting condition decision system which utilizes shop data and predicts tool life by neural network and eventually leads to the optimal cutting condition. The production time per piece is considered for an optimization object. We will discuss the process of an optimal cutting condition decision by neural network. By this process, a series of shop data is stored. And neural network is constructed for prediction of tool life and the optimal cutting condition is recommended from a cutting condition decision system using the stored shop data. The results show that the developed system is rational in searching the optimal cutting conditions on job operations.

• Journal of the Korean Society of Safety
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• v.29 no.4
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• pp.61-72
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• 2014

The aim of this study is to define the condition of optimal pre-treatment for preferable activated carbon fibers (ACFs), which are based on rayon fibers. This paper shows the ideal path of ACFs preparation process; implies that rayon fibers are pre-treated by various solvents with different times before the heating process. The pre-treated rayon fibers finally turned into desirable rayon fiber-based ACFs through optimal pre-treatment condition by heating processes. The thermal analysis method of pre-treated rayon fibers by thermo-gravimetry analyser (TGA) is an idealized tool, which analyzes the best thermal condition of pre-treatment process. Surface morphologies of resulting rayon fibers based ACFs were examined by scanning electron microscope(SEM). The results of TGA and SEM analyses show that the optimal pre-treatment condition for preparing ACFs was clearly defined, in terms of thermal stability and surface morphology.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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• pp.173-177
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• 2013

The purpose of this paper is to investigate the influences on mechanical properties of two-stroke cycle motor pistons manufactured by casting, conventional forging and powder forging, through the comparison of characteristics, merits and disadvantages of each forming technology. For each forming technology, the optimal process parameters were determined through the experiments for several conditions, and microstructure, hardness, tensile strength and elongation of pistons are compared and analyzed. In conventional forging process, material temperature was $460^{\circ}C$ and the die temperature was $210^{\circ}C$ for the Al 4032. The optimal condition was found as solution treatment under $520^{\circ}C$ for 5 hours, quenching with $23^{\circ}C$ water, and aging under $190^{\circ}C$ for 5 hours. In powder forging process, the proper composition of material was determined and optimal sintering conditions were examined. From the experiment, 1.5% of Si contents on the total weight, $580^{\circ}C$ of sintering temperature, and 25 minutes of sintering time were determined as the optimal process condition. For the optimal condition, the pistons had 76.4~78.3 [HRB] of hardness, and 500 [MPa] of tensile strength after T6 heat treatment.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.6
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• pp.590-597
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• 2009

The final quality of the workpiece is affected by the grinding process that has been conducted in final manufacturing stage. However the quality-satisfaction of ground workpiece depends on the skill of an expert in this process. Therefore, the process models of grinding have been developed to predict the states according to grinding process. In this paper, in order to find the optimized grinding condition to reduce the manufacturing expense and to meet requirements of ground workpiece optimization algorithm using E.S.(Evolutionary Strategy) is proposed. The proposed algorithm has been employed to find the optimal grinding and dressing condition using the grinding process models and nonlinear grinding constraints. The optimized results also presents the guide line of grinding process. The effectiveness of the proposed algorithm is verified through the experimental results.