• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.1
• /
• pp.138-145
• /
• 2009

High-efficiency and high-quality machining has become a fact of life for numerous machine shops in recent years. And high-efficiency machining is the most significant tool to enhance productivity. In this study, to achieve high-efficiency machining in turning process, a spindle speed optimization method was proposed based on a cutting power model. The cutting force and power were estimated from the cutting parameters such as specific cutting force, feed, depth of cut, and spindle speed. The time delay due to the acceleration or deceleration of spindle was considered to predict a more accurate machining time. Especially, the good agreement between the predicted and measured cutting forces showed the reliability of the proposed optimization method, and the effectiveness of the proposed optimization method was demonstrated through the simulation results associated with the productivity enhancement in turning process

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.3
• /
• pp.1111-1130
• /
• 2016

Cooperative communications can significantly improve the wireless transmission performance with the help of relay nodes. In cooperative communication networks, relay selection and power allocation are two key issues. In this paper, we propose a relay selection and power allocation scheme RS-PA-PSACO (Relay Selection-Power Allocation-Particle Swarm Ant Colony Optimization) based on PSACO (Particle Swarm Ant Colony Optimization) algorithm. This scheme can effectively reduce the computational complexity and select the optimal relay nodes. As one of the swarm intelligence algorithms, PSACO which combined both PSO (Particle Swarm Optimization) and ACO (Ant Colony Optimization) algorithms is effective to solve non-linear optimization problems through a fast global search at a low cost. The proposed RS-PA-PSACO algorithm can simultaneously obtain the optimal solutions of relay selection and power allocation to minimize the SER (Symbol Error Rate) with a fixed total power constraint both in AF (Amplify and Forward) and DF (Decode and Forward) modes. Simulation results show that the proposed scheme improves the system performance significantly both in reliability and power efficiency at a low complexity.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
• /
• 1997.10a
• /
• pp.17-23
• /
• 1997

A methodology for on-line data reconciliation and optimization has been proposed to minimize the energy cost of a utility system. As industrial data tend to be corrupted by noise or gross error, fast and robust data reconciliation technique is essential for the on-line optimization of utility system. Thus, we propose the hierarchical decomposition approach that can be applicable to on-line data reconciliation and optimization. As this approach divides whole system into several subsystems and removes the nonlinearity of constraint systematically, it handles complexity of system easily and shows good performance in accuracy and computation speed. Through case studies, we prove that this methodology is a good candidate for on-line data reconciliation and optimization.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.05a
• /
• pp.352-355
• /
• 2004

The objective of this work is to develop a new design method to find optimal coils, especially the optimal coil configuration of an optical pickup actuator. In designing actuator coils, the developed Lorenz force in the coils along the desired direction should be made as large as possible while forces and torques in other directions should be made as small as possible. The design methodology we are developing is a systematic approach that can generate optimal coil configurations for given permanent magnet configurations. To consider the best coil configuration among all feasible coil configurations, we formulate the design problem as a topology optimization of a coil. The present formulation for coil design is noble in the sense that the existing topology optimization is mainly concerned with the design of yokes and permanent magnets and that the optimization of actuator coils is so far limited within shape or size optimization. Though the present design methodology applies to any problem, the specific design example considered is the design of fine-pattern tracking and focusing coils.

• 한국금형공학회:학술대회논문집
• /
• 2008.06a
• /
• pp.203-208
• /
• 2008

Recently, the modern society in development and industrial growth is investing a lot of time and much effort to improvement and environment of life quality. Thus, the casting tape which uses environmentally friendly and human body friendly water hardening process Polymer is rapidly substituted for the gypsum cast product which has been plentifully used in medical treatment. Until currently, prior researches have a tendency to focusing the analysis about chemical creation expense and reaction quality rather than the issue about optimization of the process for this polymerization. In the polymerization process which has been accomplished with actual same chemical creation expense, there has been a problem which is the possibility of getting a different result. This is because the optimization of respectively control factors is not accomplished which affect at polymerization process. Therefore, this research sees the chemical qualities of casting tape Polymer, consequently selects the polymerization process which is suitable. And, by using a experimental design, this research will evaluate the affects which the respective factors have on remaining NCO and viscosity. futhermore, this research will carry out the process optimization which can get the above results.

• Journal of the Korean Society of Systems Engineering
• /
• v.1 no.1
• /
• pp.14-19
• /
• 2005

High temperature vacuum furnaces or high standard electric furnaces demand high technology level and high production cost. Therefore, an iterative design process and the optimization approach under integrated computing environment are required to reduce the development risk. Moreover, it also required to develop an integrated design software that can manage the centralized database system between factory and design department, and the automated furnace design and analysis. The developed software is dedicated to the development of the vacuum (electric) furnaces. Based on the distribute middleware system, the GUI module, the CAD module, the thermal analysis module and the optimization module are integrated. For the DBMS, Microsoft Access is employed, the GUI is developed using Visual Basic language, and AutoCAD is utilized for the configuration design. By investigating the analysis code interface, the analysis and optimization process, and the data communication method, the overall system architecture, the method to integrate the optimizer and ana lysis codes, and the method to manage the data flow are proposed and verified through the optimal furnace design.

• Advances in aircraft and spacecraft science
• /
• v.3 no.2
• /
• pp.149-170
• /
• 2016

Multi-Disciplinary Optimization (MDO) is widely used to handle the advanced design in several engineering applications. Such applications are commonly simulation-based, in order to capture the physics of the phenomena under study. This framework demands fast optimization algorithms as well as trustworthy numerical analyses, and a synergic integration between the two is required to obtain an efficient design process. In order to meet these needs, an adaptive Computational Fluid Dynamics (CFD) solver and a fast optimization algorithm have been developed and combined by the authors. The CFD solver is based on a high-order discontinuous Galerkin discretization while the optimization algorithm is a high-performance version of the Artificial Bee Colony method. In this work, they are used to address a typical aero-mechanical problem encountered in turbomachinery design. Interesting achievements in the considered test case are illustrated, highlighting the potential applicability of the proposed approach to other engineering problems.

• Structural Engineering and Mechanics
• /
• v.68 no.5
• /
• pp.633-638
• /
• 2018

One of the important problems in the vehicle design is vehicle handling and stability. Effective parameters which should be considered in the vehicle handling and stability are roll angle, camber angle and scrub radius. In this paper, a planar vehicle model is considered that two right and left suspensions are double wishbone suspension system. For a better analysis of the suspension geometry, a kinestatic model of vehicle is considered which instantaneous kinematic and statics relations are analyzed simultaneously. In this model, suspension geometry is considered completely. In order to optimum design of double wishbones suspension system, a multi-objective genetic algorithm is applied. Three important parameters of suspension including roll angle, camber angle and scrub radius are taken into account as objective functions. Coordinates of suspension hard points are design variables of optimization which optimum values of them, corresponding to each optimum point, are obtained in the optimization process. Pareto solutions for three objective functions are derived. There are important optimum points in these Pareto solutions which each point represents an optimum status in the model. In other words, corresponding to any optimal point, a specific geometric position is determined for the suspension hard points. Each of the obtained points in the Pareto optimization can be selected for a special design purpose by designer to create an optimum condition in the vehicle handling and stability.

• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.225-234
• /
• 2020

Reliability-based structural optimization usually requires designers or engineers model different designs manually, which is considered very time consuming and all possibilities cannot be fully explored. Otherwise, a lot of time are needed for designers or engineers to learn mathematical modeling and programming skills. Therefore, a framework that integrates generative design, structural simulation and reliability theory is proposed. With the proposed framework, various designs are generated based on a set of rules and parameters defined based on visual programming, and their structural performance are simulated by OpenSees. Then, reliability of each design is evaluated based on the simulation results, and an optimal design can be found. The proposed framework and prototype are tested in the optimization of a steel frame structure, and results illustrate that generative design based on visual programming is user friendly and different design possibilities can be explored in an efficient way. It is also reported that structural reliability can be assessed in an automatic way by integrating Dynamo and OpenSees. This research contributes to the body of knowledge by providing a novel framework for automatic reliability evaluation and structural optimization.

• Journal of Drive and Control
• /
• v.21 no.1
• /
• pp.46-52
• /
• 2024

The advancement of autonomous driving technology has heightened the importance of Autonomous Mobile Robotics (AMR) within smart factories. Notably, in tasks involving the transportation of heavy objects, the consideration of weight in route optimization and path planning has become crucial. There is ongoing research on local path planning, such as Dijkstra, A^*, and RRT^*, focusing on minimizing travel time and distance within smart factory warehouses. Additionally, there are ongoing simultaneous studies on route optimization, including TSP algorithms for various path explorations and on minimizing energy consumption in mobile robotics operations. However, previous studies have often overlooked the weight of the objects being transported, emphasizing only minimal travel time or distance. Therefore, this research proposes route planning that accounts for the maximum payload capacity of mobile robotics and offers load-optimized path planning for multi-destination transportation. Considering the load, a genetic algorithm with the objectives of minimizing both travel time and distance, as well as energy consumption is employed. This approach is expected to enhance the efficiency of mobility within smart factories.