• 한국공작기계학회논문집
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• 제13권2호
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• pp.81-87
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• 2004

This paper deals with a new approach to tolerance optimization problems. Optimal tolerance allotment problems can be formulated as stochastic optimization problems. Most schemes to solve the stochastic optimization problems have been found to exhibit difficulties in multivariate integration of the probability density function. As a typical example of stochastic optimization the optimal tolerance allotment problem has the same difficulties. In this stochastic model, manufacturing system is represented by Gauss-Markov stochastic process and the manufacturing unit availability is characterized for realistic optimization modeling. The new algorithm performed robustly for a large deviation approximation. A significant reduction in computation time was observed compared to the results obtained in previous studies.

• 한국CDE학회논문집
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• 제19권2호
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• pp.148-156
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• 2014

Generally, over 95% of manufacturing cost is determined in the design and manufacturing preparation step, especially a great part of productivity is determined in the manufacturing preparation step. In order to improve the manufacturing competitiveness, we have to verify the problems that can be occurred in the production step and remove the unnecessary factors in the manufacturing preparation step. Thus, manufacturing industries are adopting digital manufacturing system based on modeling & simulation. In this paper, we introduce e-FEED system (electronic based Front End Engineering and Design) that is the integrated design and analysis system for optimized manufacturing line development based on simulation automation and explain the work process (Design, Analysis and Optimization) about manufacturing line development using e-FEED system. Also, the effect is described through the real implementation cases.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권9호
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• pp.393-402
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• 2015

데이터 시각화 기술은 다양한 데이터와 그 분석 결과를 쉽게 이해할 수 있도록 도와줌으로써 제조현장과 같은 실제 산업현장에서도 그 유용성이 기대되고 있다. 제조현장에서 발생하는 대량의 데이터는 제조 기술의 표준화를 위한 기반 데이터가 될 수 있으며 제조공정의 개선을 위하여 매우 중요한 역할을 수행할 수 있다. 본 논문에서는 실험계획법과 데이터 분석 기반의 제조공정 최적화를 위한 정보 시각화 방법을 제안한다. 데이터 분석 결과의 정보 시각화를 통하여 작업 현장에 이해하기 쉬운 분석 결과를 제공함으로써 다양한 불량원인을 감소시키고 제조공정을 개선시킬 수 있다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.491-495
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• 2002

In the paper, a Visual factory model for a optical-components manufacturing process is built. The optical-components manufacturing process is composed of 3 operation processes; optical sub assembly process, package assembly process, and fiber assembly process. Each process is managed not a batch mode, which is one of most popular manufacturing styles to produce a great deal of industrial output, but though a modular cell. In the processes, a modular cell has to be processed independently of the other cells. Optimization for the composition of assembly cell in the optical-components system is made by the Visual factory model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1362-1366
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• 2003

Workload programming is allocating suitable workloads of production process according to the needs of products, which would minimize the total cost of both work and stock under some constraint conditions. In this paper, a production process flow chart of discrete manufacturing is presented by a Petri net, and the optimization model of workload-stock is established. An approach of the optimal workloads is provided by means of the integer matrix theory. An example is given to verify this method.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.636-639
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• 2002

In the paper, a Visual factory model for a optical-components manufacturing process is built. The optical-components manufacturing process is composed of 3 operation processes; optical sub assembly process, package assembly process, and fiber assembly process. Each process is managed not a batch mode, which is one of most popular manufacturing styles to produce a great deal of industrial output, but though a modular cell. In the processes, a modular cell has to be processed independently of the other cells. Optimization for the composition of assembly cell in the optical-components system is made by the Visual factory model.

• Journal of Computational Design and Engineering
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• 제2권4호
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• pp.248-252
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• 2015

Currently composite manufacturing process, such as linear friction welding plus NC machining, is the main method for the manufacturing and repairing of complex parts with integrated structure. Due to different datum position and inevitable distortion from different processes, it is important to ensure sufficient machining allowance for complex parts during the NC machining process. In this paper, a workpiece localization approach for machining allowance optimization of complex parts based on CMM inspection is developed. This technique concerns an alignment process to ensure sufficient stock allowance for the single parts as well as the whole integrated parts. The mathematical model of the constrained alignment is firstly established, and then the symmetric block solution strategy is proposed to solve the optimization model. Experiment result shows that the approach is appropriate and feasible to distribute the machining allowance for the single and whole parts for adaptive machining of complex parts.

• 한국기계가공학회지
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• 제16권3호
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• pp.119-124
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• 2017

Machining optimization using typical computer-aided manufacturing (CAM) software mainly depends on tool paths, and it is impossible to predict the behavior of material or cutting force. In this paper, cutting force analysis simulation is performed on the Unibody Case of a mobile phone with the aim of optimizing cutting-force-based machining using the Third Wave Systems' AdventEdge Production Module. Machining time after optimization was shortened by 42% for roughing compared to pre-optimization, and actual machining time was reduced by 36.8%. For finishing, machining time was reduced by 92%, and actual machining time was reduced around 90%. A surface roughness analysis found that the post-optimization surface roughness was $1.16{\mu}m$ Ra, compared to a pre-optimization value of $1.75{\mu}m$ Ra.

• 한국공작기계학회논문집
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• 제15권5호
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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.

• 대한기계학회논문집A
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• 제31권9호
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• pp.960-966
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• 2007

High-efficient machining, which means to machine a part in the least amount of time, is the most effective tool to improve productivity. In this study, a new feed optimization method based on virtual manufacturing was proposed to realize the high-efficient machining in turning process through the cutting power regulation. The cutting area was evaluated by using the Boolean intersection operation between the cutting tool and workpiece. And the cutting force and power were predicted from the cutting parameters such as feed, depth of cut, spindle speed, specific cutting force, and so on. Especially, the reliability of the proposed optimization method was validated by comparing the predicted and measured cutting forces. The simulation results showed that the proposed optimization method could effectively enhance the productivity in turning process.