• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.4
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• pp.114-122
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• 2013

This study introduces an optimization methodology for the determination of gate location that ensures the melt flow balance within a part cavity of injection mold. A new sequential direct-search scheme based on the recursive reduction of the designer-specified gate design area is developed, and it is integrated with a commercial flow simulation tool for optimization. To quantify the level of melt flow balance, we employ the maximum difference among the fill times for the melt fronts to reach the boundary elements of part cavity as objective function. The proposed methodology is successfully applied in the case study of melt flow balancing in molding of a bar code scanner model. The result shows that the melt flow balance at the optimized gate positions is significantly improved from that for the initial gate position.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.9
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• pp.210-221
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• 2000

Plastic mold designers and frequently faced with optimizing multi-quality issues in injection molded parts. These issues are usually in conflict with each other and thus tradeoff needs to be made to reach a final compromised solution. in this study an automated injection molding design methodology has been developed to optimize multi-quality characteristics of injection molded parts. The features of the proposed methodology are as follows : first utility theory is applied to transform the original multi-objective problem into single-objective problem. Second is an implementation of a direct search-based injection molding optimization procedure with automated consideration of robustness against process variation. The modified complex method is used as a general optimization tool in this study. The developed methodology was applied to an actual mold design and the results showed that the methodology was useful through the CAE simulation using a commercial injection molding software package. Applied to production this study will be of immense value to companies in reducing the product development time and enhancing the product quality.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.123-130
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• 2006

In manufacturing, process automation and parameter optimization are required in order to improve productivity. Especially in welding process, productivity and weldablity should be considered to determine the process parameter. In this paper, optimization methodology was proposed to determine the welding conditions using the objective function in terms of productivity and weldablity. In order to conduct this, welding experiments were carried out. Tensile test was performed to evaluate the weldability. Neural network model to estimate tensile strength using the laser power, welding speed, and wire feed rate was developed. Objective function was defined using the normalized tensile strength which represented the weldablilty and welding speed and wire feed rate which represented the productivity. The optimal welding parameters which maximized the objective function were determined.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.10
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• pp.494-500
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• 2001

This paper presents the shape optimization to minimize the BEMF(Back Electro-Motive Force) harmonics of PM type synchronous generators. RSM(Response Surface Methodology) is well adapted to make analytical model for a complex problem considering a lot of interaction of design variables. In this paper, RSM is used to find the optimal solution. The 2D-Finite Element Method is used to obtain the observer data of the BEMF and SQP(Sequential Quadratic Problem method) is used to solve the constrained nonlinear optimization problem.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.84-89
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• 2003

The finite element method (FEM) is typically used in the process of motor design. However, the FEM requires computation time, Therefore, decreasing the number of FEM simulations may also decrease the simulation cost. Several optimal design methods overcoming this problem have been recently studied. This paper investigates the optimal design of the magnet pole of a BLDC motor through reducing simulation cost. The optimization minimizes the magnet volume and limits the average and cogging torques to certain values. In this paper, the response surface methodology and Taguchi's table for reducing the number of FEM simulations are used to approximate two constraints. The optimization result shows that the presented strategy is satisfactorily performed.

• Transactions of Materials Processing
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• v.9 no.5
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• pp.512-525
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• 2000

Designers are frequently faced with multiple quality issues in injection molded parts. These issues are usually In conflict with each other, and thus tradeoff needs to be made to reach a final compromised solutions. The objective of this study is to develop an automated injection molding design methodology, whereby part defects such as warpage and weld line are optimized. The features of the proposed methodology are as follows: first, Utility Function approach is applied to transform the original multiple objective problem into single objective problem. Second is an implementation of a direct search-based Injection molding optimization procedure with automated consideration of process variation. The Space Reduction Method based on Taguchi's DOE(Design Of Experiment) is used as a general optimization tool in this study. The computational experimental verification of the methodology was partially carried out for a can model of Cavallero Plastics Incorporation, U. S. A. Applied to production, this study will be of immense value to companies in reducing the product development time and enhancing the product quality.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.597-602
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• 2011

A robust asset management methodology is essential for effective decision-making of maintenance, repair and rehabilitation of a bridge network. It can be achieved by a computer-based bridge management system (BMS). Successful BMS development requires a reliable bridge deterioration model, which is the most crucial component in a BMS, and an optimal management philosophy. The maintenance optimization methodology proposed in this paper is developed for a small bridge network with limited structural condition rating records. . The methodology is organized in three major components: (1) bridge health index (BHI); (2) maintenance and budget optimization; and (3) reliable Artificial Intelligence (AI) based bridge deterioration model. The outcomes of the paper will help to identify BMS implementation problems and to provide appropriate solutions for managing small bridge networks.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.579-584
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• 2003

Solenoid type magnetic actuator is the device, which could translate the electromagnetic energy to mechanical force. The force generated by magnetic flux, could be calculated by Maxwell stress tensor method. Maxwell stress tensor method is influenced by the magnetic flux path. Thus, magnetic force could be improved by modification of the iron case, which is the route of the magnetic flux. Modified design is obtained by parameter optimization using by Response surface methodology.

• Journal of Distribution Science
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• v.13 no.11
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• pp.123-130
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• 2015

Purpose - Due to highly elevated levels of competition, many companies today have to face the problem of decreasing profits even when their actual sales volume is increasing. This is a common phenomenon that is seen occurring among companies that focus heavily on quantitative growth rather than qualitative growth. These two aspects of growth should be well balanced for a company to create a sustainable business model. For supply chain management (SCM) planners, the optimized, quantified flow of resources used to be of major interest for decades. However, this trend is rapidly changing so that managers can put the appropriate balance between sales volume and sales quality, which can be evaluated from the profit margin. Profit optimization is a methodology for companies to use to achieve solutions focused more on profitability than sales volume. In this study, we attempt to provide executional insight for companies considering implementation of the profit optimization system to enhance their business profitability. Research design, data, and methodology - In this study, we present a comprehensive explanation of the subject of profit optimization, including the fundamental concepts, the most common profit optimization logic algorithm -linear programming -the business functional scope of the profit optimization system, major key success factors for implementing the profit optimization system at a business organization, and weekly level detailed business processes to actively manage effective system performance in achieving the goals of the system. Additionally, for the purpose of providing more realistic and practical information, we carefully investigate a profit optimization system implementation case study project fulfilled for company S. The project duration was about eight months, with four full-time system development consultants deployed for the period. To guarantee the project's success, the organization adopted a proven system implementation methodology, supply chain management (SCM) six-sigma. SCM six-sigma was originally developed by a group of talented consultants within Samsung SDS through focused efforts and investment in synthesizing SCM and six-sigma to improve and innovate their SCM operations across the entire Samsung Organization. Results - Profit optimization can enable a company to create sales and production plans focused on more profitable products and customers, resulting in sustainable growth. In this study, we explain the concept of profit optimization and prerequisites for successful implementation of the system. Furthermore, the efficient way of system security administration, one of the hottest topics today, is also addressed. Conclusion - This case study can benefit numerous companies that are eagerly searching for ways to break-through current profitability levels. We cannot guarantee that the decision to deploy the profit optimization system will bring success, but we can guarantee that with the help of our study, companies trying to implement profit optimization systems can minimize various possible risks across various system implementation phases. The actual system implementation case of the profit optimization project at company S introduced here can provide valuable lessons for both business organizations and research communities.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.2
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• pp.27-38
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• 2018

Environmental planning includes resource allocation and spatial planning process for the conservation and management of environment. Because the spatialization of the environmental planning is not specifically addressed in the relevant statutes, it actually depends on the qualitative methodology such as expert judgement. The results of the qualitative methodology have the advantage that the accumulated knowledge and intuition of the experts can be utilized. However, it is difficult to objectively judge whether it is enough to solve the original problem or whether it is the best of the possible scenarios. Therefore, this study proposed a methodology to quantitatively and objectively spatialize various environmental planning. At first, we suggested a quantitative spatial planning model based on an optimization algorithm. Secondly, we applied this model to two kinds of environmental planning and discussed about the model performance to present the applicability. Since the models were developed based on conceptual study site, there was a limitation in showing possibility of practical use. However, we expected that this study can contribute to the fields related to environmental planning by suggesting flexible and novel methodology.