• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.69-86
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• 2020

Purpose: This study aims to determine the optimal conditions for the spot welding process that mechanically connects the case of a cylindrical secondary battery and the negative tab. Methods: We use 33 factorial design to derive the optimal conditions for the spot welding process. The pulling strength, the cross-sectional area of nugget, and the shock test life are selected as response variables, which can represent the resistance welding quality. The input variables are selected as the welding time, welding voltage, and pressure, which are the controllable factors in the spot welding process. Results: The main effects of welding time and welding voltage and the interaction effect of welding time and welding voltage are significant. Conclusion: The optimal conditions for the spot welding process to mechanically join the negative electrode tab of the cylindrical secondary battery and the battery case are developed. The result shows that the pulling strength is increased by 44% compared to before improvement under optimal conditions.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.49-58
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• 1997

In process planning for pocket machining, the selection of tool size, tool path, overlap distance, and the calculation of machining time are very important factors to obtain the optimal process planning result. Among those factors, the tool size is the most important one because the others depend on tool size. And also, it is not easy to determine the optimal tool size even though the shape of pocket is simple. Therefore, the optimal selection of tool size is the most essential task in process planning for machining a pocket. This paper presents a method for selecting optimal toos in pocket machining. The branch and bound method is applied to select the optimal tools which minimize the machining time by using the range of feasible tools and the breadth-first search.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2002.11a
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• pp.23-32
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• 2002

The torsional forward extrusion is the process that is executed by punch travel and die rotation. The advantages of having the die rotation on this process are that forming load can be reduced and optimal die angle can be increased. This provides a possibility to extrude cold-worded material where a large extrusion force and die angle are required. Also, this process can improve the material properties owing to the high deformation and uniform strain distribution. The forming load and optimal die angle of this process are determined by the upper bound analysis using stream function and the optimization technique. To verify the theoretical result, we have carried out experiments and FE simulations using DEFORM3D.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.4
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• pp.571-579
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• 1990

A dynamic relocation algorithm for non-deterministic process graph in distributed computer systems is proposed. A method is represented for determining the optimal policy for processing a process tree. A general database query request is modelled by a process tree which represent a set of subprocesses together with their precedence relationship. The process allocation model is based on operating cost which is a function fo selection of site for processing operation, data reduction function and file size. By using expected values of parameters for non-deterministic process tree, the process graph and optimal policy that yield minimum operating cost are determined. As process is relocated according to threshold value and new information of parameters after the execution of low level process for non-deterministic process graph, the assigned state that approximate to optiaml solution is obtained. The proposed algorihtm is heuristic By performing algorithm for sample problems, it is shown that the proposed algorithm is good in obtaining optimal solution.

• Current Photovoltaic Research
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• v.6 no.2
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• pp.49-55
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• 2018

Recently solar cell industry needs the optimal design of Czochralski process for low cost high quality silicon mono crystalline ingot. Because market needs both high efficient solar cell and similar cost with multi-crystalline Si ingot. For cost reduction in Czochralski process, first of all energy reduction should be completed because Czochralski process is high energy consumption process. For this purpose we studied optimal water-cooling tube design and simultaneously we also check the quality of ingot with Von mises stress and V(pull speed of ingot)/G(temperature gradient to the crystallization) values. At this research we used $CG-Sim^{(R)}$ S/W package and finally we got improved water-cooling tube design than normally used process in present industry. The optimal water-cooling tube length should be 200mm. The result will be adopted at real industry.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.2
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• pp.55-63
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• 2014

Fractures and wrinkles are two major defects frequently found in the sheet metal forming process. The process has several noise factors that cannot be ignored when determining the optimal process conditions. Therefore, without any countermeasures against noise, attempts to reduce defects through optimal design methods have often led to failure. In this study, a new and robust design methodology that can reduce the possibility of formation of fractures and wrinkles is presented using decision-making theory. A two-attribute value function is presented to form the design metric for the sheet metal forming process. A modified complex method is adopted to isolate the optimal robust design variables. One of the major limitations of the traditional robust design methodology, which is based on an orthogonal array experiment, is that the values of the optimal design variables have to coincide with one of the experimental levels. As this restriction is eliminated in the complex method, a better solution can be expected. The procedure of the proposed method is illustrated through a robust design of the sheet metal forming process of a side member of an automobile body.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.41-50
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• 1994

Consider a canning process where cans are filled with an expensive ingredient. Cans weighting above the specified limit are sold in a regular market for a fixed price, and underfilled cans are emptied and refilled at the expense of a reprocessing cost. In this paper, the effect of measurement error on the determination of the optimal process mean for a canning process is examined. It is assumed that the quantity X of ingredient in a can is normally distributed with unknown mean and known variance, and the observed value Y of X is also normally distributed with known mean and variance. A profit model is constructed which involves selling price. cost of ingredients, reprocessing cost. and cost from an accepted nonconforming can, and methods of finding the optimal process mean and the cutoff value on Y are presented. It is shown that the optimal process mean increases. and the expected profit decreases when the measurement error is relatively large in comparison to the process variance.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.199-202
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• 2005

In this paper, the six sigma scheme is employed together with the rigid-viscoplastic finite element method to obtain the optimal metal flow lines in hot press forging. In general, the six sigma process is consisted of following five steps : define, measure, analyze, improve and control. Each step Is investigated in detail to meet customer's requirements through improvement of product quality. A forging simulator, AFDEX-2D, is used for analysis of the metal flow lines of a multi-stage hot forging process under various conditions of major factors, determined at each step of the six sigma process. The analyzed results are examined in order to reveal the effects of major factors on the metal flow lines and the formed shapes. The effects are used to find an optimal process and the optimal process with die is devised and tested. The comparison between required metal flow lines and experiments shows that the approach is effective for optimal process in hot forging design considering metal flow lines.

• Electrical & Electronic Materials
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• v.9 no.8
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• pp.799-805
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• 1996

In short channel MOSFET, it is very important to establish optimal process conditions because of variation of device characteristics due to the process parameters. In this paper, we used process simulator and device characteristics caused by process parameter variation. From this simulation, it has been ' derived to the dependence relations between process parameters and device characteristics. The experimental result of fabricated short channel device according to the optimal process parameters demonstrate good device characteristics.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.113-122
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• 1996

As integrity of semiconductor device is increased, accurate and efficient modeling and recipe generation of semiconductor fabrication procsses are necessary. Among the major semiconductor manufacturing processes, dry etc- hing process using gas plasma and accelerated ion is widely used. The process involves a variety of the chemical and physical effects of gas and accelerated ions. Despite the increased popularity, the complex internal characteristics made efficient modeling difficult. Because of difficulty to determine the control input for the desired output, the recipe generation depends largely on experiences of the experts with several trial and error presently. In this paper, the optimal control of the etching is carried out in the following two phases. First, the optimal neural network models for etching process are developed with genetic algorithm utilizing the input and output data obtained by experiments. In the second phase, search for optimal control inputs in performed by means of using the optimal neural network developed together with genetic algorithm. The results of study indicate that the predictive capabilities of the neural network models are superior to that of the statistical models which have been widely utilized in the semiconductor factory lines. Search for optimal control inputs using genetic algorithm is proved to be efficient by experiments. (author). refs., figs., tabs.