• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.333-336
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• 1991

In this paper, Hopfield & Tank model-like artificial neural network structure is proposed, which can be used for the optimal path planning problems such as the unit commitment problems or the maintenance scheduling problems which have been solved by the dynamic programming method or the branch and bound method. To construct the structure of the neural network, an energy function is defined, of which the global minimum means the optimal path of the problem. To avoid falling into one of the local minima during the optimization process, the simulated annealing method is applied via making the slope of the sigmoid transfer functions steeper gradually while the process progresses. As a result, computer(IBM 386-AT 34MHz) simulations can finish the optimal unit commitment problem with 10 power units and 24 hour periods (1 hour factor) in 5 minites. Furthermore, if the full parallel neural network hardware is contructed, the optimization time will be reduced remarkably.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.6
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• pp.84-92
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• 2013

This study improves the formability in fine-blanking the lock plate of car seat belts using a low carbon steel(SM35C) plate. The optimal die design for the forming process is proposed using rules for process planning based on theories and field experiences. The optimal design is analyzed using commercial finite element software in order to solve the fracture problems in the extrusion process. Through the improved layout based on the FEM results, the fracture of the extruded part and the roll over problem are solved. Furthermore, it is demonstrated through the shown from experiments that the extruded part does not break in the modified die.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.209-219
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• 2000

A method is developed to evaluate machining process and to determine the optimal machining conditions considering the environmental effects. The method Is based on the evaluation attributes from the general LCA programs and the analysis technique of AHP from HHS. To assist the analysis. the mass models of cutting energy, tools, and fluids are developed. The models may be used for both quantitative prediction of the uses and disposed masses of materials and optimization of the machining conditions. The algorithm with the mass models is applied to the milling process planning. The process to survey the environmental data, calculate the used mass, and evaluate the alternatives is demonstrated. This demonstration illustrates the of the change of process conditions of the decision making.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.15
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• pp.33-38
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• 1987

In establishing Multi-Stage Machining process inspection procedures, however, where costs of inspection md defective products are often directly measurable, a better method for formulating inspection plans is available. If one of the primary interest of a manufacturing concern is to maximize profits, then optimal inspection plans ought to be selected so as to minimize costs. This paper is aimed to find a methodology of optimal inspection planning in Multi-stage Machining process and to develope a proper algorithm.

• ETRI Journal
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• v.44 no.4
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• pp.641-653
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• 2022

In the process of autonomous vehicle motion planning and to create comfort for vehicle occupants, factors that must be considered are the vehicle's safety features and the road's slipperiness and smoothness. In this paper, we build a mathematical model based on the combination of a genetic algorithm and a neural network to offer lane-change solutions of autonomous vehicles, focusing on human vehicle control skills. Traditional moving planning methods often use vehicle kinematic and dynamic constraints when creating lane-change trajectories for autonomous vehicles. When comparing this generated trajectory with a man-generated moving trajectory, however, there is in fact a significant difference. Therefore, to draw the optimal factors from the actual driver's lane-change operations, the solution in this paper builds the training data set for the moving planning process with lane change operation by humans with optimal elements. The simulation results are performed in a MATLAB simulation environment to demonstrate that the proposed solution operates effectively with optimal points such as operator maneuvers and improved comfort for passengers as well as creating a smooth and slippery lane-change trajectory.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.495-497
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• 2000

The KEPCO is developing the load forecasting sysetm using land use simulation method and distribution planning system. Distribution planning needs the data of presents loads, forecasted loads sub-statin, and distribution lines. Using the data, determine the sub-station and feeder lines according to the load forecasting data. This paper presents the method of formulation processfor the long term load forecasting and optimal distribution planning and optimal distribution planning. And describes the case study of long term distribution planning of Kwangju city accord to the newly applied method.

• Journal of the Korean Society for Precision Engineering
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• v.5 no.3
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• pp.31-42
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• 1988

This paper describes a computer aided process planning system called "Deep-Drawing", "Deep-Drawing" is designed for the drawing sequence of cylindrical and rectangular cups with or without taper and flange. The computer program has written in BASIC language with personal computer. Design Rules for process planning are formulated from process limitation, plasticity theory and experimental results including the know-how of many manufacturing factories. "Deep-Drawing" Capabilities include the analysis of drawing sequence by the determination of optimal drawing ratio, the determination of intermediate shape, dimensions, punch and die radius etc., the calculation of drawing loads and blank holder force to perform each drawing step, and the graphic outputs for the operation sheet.tputs for the operation sheet.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.323-341
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• 1997

Traditionally, the Process Planning problems and the Scheduling problems have been considered as independent ones. However, we can take much advantages by solving the two problems simultaneously. In this paper, we deal with the enlarged problem that takes into account both the process planning and the scheduling problems. And we present a solution algorithm for the problem assuming that the given process plan data is represented by AND/OR graph. A mathematical model(mixed ILP model) whose objective is the minimization of the makespan, is formulated. We found that we can get the optimal solutions of the small-size problems within reasonable time limits, but not the large-size problems. So we devised an algorithm based on the decomposition strategy to solve the large-scale problems (realistic problems) within practical time limits.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.1
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• pp.42-50
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• 2005

In order to increase competitiveness and to gain economic benefit, companies ask more and more how to recycle their products in an efficient way. So far, to answer this question, companies are not sufficiently supported by suitable methods specially in the area of disassembly process planning. For this reason, we develop in collaboration with an industrial partner a new method for generating an optimal disassembly sequence. In this paper this method will be described in detail by considering the exiting assembly information, disassembly method and disassembly depth. PLM(Profit-Loss Margin) curve that is used to determine disassembly depth consists of profit value, disassembly cost and disassembly effect. Using assessment parameters, generated alternative disassembly sequences are evaluated and an optimal disassembly sequence is proposed. This method is applied to generate the optimal disassembly sequence of Door Trim as an example.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.9
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• pp.101-110
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• 1998

In process planning for 3D pocket machining, the critical issues for the optimal process planning are the generation of cutting layers and the tool selection for each cutting layers as well as the other factors such as the determination of machining types, tool path, etc. This paper describes the optimal tool selection on a single cutting layer for 2D pocket machining, the generation of cutting layers for 3D pocket machining, the determination of the thickness of each cutting layers, the determination of the tool combinations for each cutting layers and also the development of an algorithm for determining the machining sequence which reduces the number of tool exchanges, which are based on the backward approach. The branch and bound method is applied to select the optimal tools for each cutting layer, and an algorithmic procedure is developed to determine the machining sequence consisting of the pairs of the cutting layers and cutting tools to be used in the same operation.