• Management Science and Financial Engineering
• /
• 제10권2호
• /
• pp.73-87
• /
• 2004

Automotive and aircraft assembly process rely on fixtures to support and coordinate parts and subassemblies. Fixture layout in multi-station panel assemblies has a direct dimensional effect on final products and thus presents a quality problem. This paper describes a methodology for fixture layout design in multi -station assembly processes. An optimal fixture layout improves the robustness of a fixture system against environmental noises, reduces product variability, and eventually leads to manufacturing cost reduction. One of the difficulties raised by multi-station fixture layout design is the overwhelmingly large number of design alternatives. This makes it difficult to find a global optimality and, if an inefficient algorithm is used, may require prohibitive computing time. In this paper, simulated annealing is adopted and appropriate parameters are selected to find good fixture layouts. A four-station assembly process for a sport utility vehicle (SUV) side frame is used throughout the paper to illustrate the efficiency and effectiveness of this methodology.

• 전기학회논문지
• /
• 제61권3호
• /
• pp.472-478
• /
• 2012

The inspection machine in PCB (printed circuit board) assembly line checks assembly errors by inspecting the images inside of the component inspection region. The component inspection region consists of region of component package and region of soldering. It is necessary to extract the regions automatically for auto-teaching system of the inspection machine. We propose an image segmentation method to extract the component inspection regions automatically from images of PCB. The acquired image is transformed to HSI color model, and then segmented by several regions by clustering method. We develop a modified K-means algorithm to increase the accuracy of extraction. The heuristics generating the initial clusters and merging the final clusters are newly proposed. The vertical and horizontal projection is also developed to distinguish the region of component package and region of soldering. The experimental results are presented to verify the usefulness of the proposed method.

• 한국기계연구소 소보
• /
• 통권18호
• /
• pp.67-74
• /
• 1988

The force sensor is essentially required in controlling robot manipulator in such applications as precise assembly of mechanical parts, deburring and polishing and various kinds of 6-axis force sensors are developed for these application. This paper presents the algorithm of horizontal assembly of circular cross-sectional workpiece using 3-axis force sensor and procedure to develop the sensor. The sensor is calibrated and tested using AID converter and 16 bit micro computer. The result is $\pm$0.03% FS of zero stability, 0.1%FS of linearity and $\pm$0.05% FS of resolution. The sensor will be used in the research of robot application such as assembly and deburring interfaced with micro computer based robot controller which is under development at the robotics lab.

• 산업경영시스템학회지
• /
• 제22권51호
• /
• pp.189-197
• /
• 1999

Assembly line balancing problem is known as one of difficult combinatorial optimization problems. This problem has been solved with linear programming, dynamic programming approaches. but unfortunately these approaches do not lead to efficient algorithms. Recently, genetic algorithm has been recognized as an efficient procedure for solving hard combinatorial optimization problems, but has a defect that requires long-run time and computational complexties to find the solution. For this reason, we adapt a new method called the Critical Node Method that is intuitive, easy to understand, simple for implementation. Fuzzy set theory is frequently used to represent uncertainty of information. In this paper, to treat the data of real world problems we use a fuzzy number to represent the duration and Critical Node Method based heuristic procedure is developed for solving fuzzy assembly line balancing problem.

• 정보처리학회논문지:소프트웨어 및 데이터공학
• /
• 제2권10호
• /
• pp.697-704
• /
• 2013

인간의 한쪽 염색체상에 나타나는 SNP의 서열인 일배체형을 식별해내면 효과적인 유전질병 연관검사를 할 수 있다. 주어진 SNP 단편들로부터 계산적인 방법으로 한 쌍의 일배체형을 조합하기 위해 제시된 모델 중 하나인 최소오류수정 모델은 단편에 손실이 없는 경우조차 NP-hard임이 증명되었다. 기존의 분기한정 알고리즘은 많은 계산시간을 요구함에 따라 실제 응용에 사용하기 어려웠다. 그러나 최근에 개선된 분기한정 알고리즘이 제시되었고, 꿀벌(Apis mellifera)의 유전자형 데이터를 대상으로 성능을 분석해봄으로써 개선된 알고리즘이 기존 분기한정 알고리즘보다 효율적임을 보였다. 본 논문에서는 인간의 유전자형 데이터를 대상으로 개선된 분기한정 알고리즘을 적용해 일배체형 조합문제를 수행한다. 실험을 통한 성능분석 결과, 개선된 분기한정 알고리즘이 인간 유전체에 대해서도 성공적으로 적용됨을 확인함으로써 다양한 생명체의 일배체형 조합문제에 적용 가능함을 보인다.

• 한국기계가공학회지
• /
• 제14권6호
• /
• pp.49-56
• /
• 2015

For designing working devices of construction equipment, it is necessary to consider not only sufficient working ability but also available working range. Therefore, it is important to select the appropriate pivot positions of links. This paper presents a study on selection of pivot points of links used in construction equipment. To analyze the effect of each pivot point, a design program for pivot selection is developed. A conventional pivot design method requires a complicated process because it needs to create a certain working position manually to evaluate its performance. However, the developed program includes an automatic link assembly algorithm; thus, the working device can easily be analyzed by using pivot information of links. The developed program also included a kinematic/static analysis module and characteristic analysis algorithms. Therefore, it is possible to easily analyze a working device model created through the automatic assembly algorithm, whereby users can easily analyze the effect of each link pivot point for the actual product design.

• 대한안전경영과학회지
• /
• 제19권1호
• /
• pp.203-210
• /
• 2017

Companies are pursuing the management of small quantity batch production or JIT(Just-in-time) system for improving the delivery response and LOB(Line Balancing) in order to satisfy consumers' increasing demands in the current global economic recession. And in order to improve the growth of production for reducing manufacturing cost, improvements of the Load Balancing have become an important reformation factor. Thus this paper is aimed at warehouse which procures materials on the assembly line in procurement logistics of automotive logistics and proceed with research on heuristic algorithm development which can increase the Load Balancing of workers. As a result of this study, when applied the primary target value, it was verified that the whole workers decreased from 28 to 24. Furthermore, when specified the secondary target value and applied algorithm once more, it was verified that the Load Balance Ratio was improved from 44.96% to 91.7%.

• Journal of Mechanical Science and Technology
• /
• 제16권12호
• /
• pp.1633-1642
• /
• 2002

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system using electro-hydraulic manipulator because hydraulic manipulators have the advantage of electric insulation. Meanwhile it is relatively difficult to realize autonomous assembly tasks particularly in the case of manipulating flexible objects such as electric lines. In this report, a discrete event control system is introduced for automatic assembly task of electric lines into sleeves as one of the typical task of active electric power lines. In the implementation of a discrete event control system, LVQNN (linear vector quantization neural network) is applied to the insertion task of electric lines to sleeves. In order to apply these proposed control system to the unknown environment, virtual learning data for LVQNN is generated by fuzzy inference. By the experimental results of two types of electric lines and sleeves, these proposed discrete event control and neural network learning algorithm are confirmed very effective to the insertion tasks of electric lines to sleeves as a typical task of active electric power maintenance tasks.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2005년도 춘계학술대회 논문집
• /
• pp.2015-2018
• /
• 2005

In this paper, we are willing to prepare the reasonable optimization, Combinatorial Optimization and Genetic Algorithm. Thus we define position status of end-effect (or terminative link module) using promised form, (G, M(G), A(G), and so on.). For this preparing step, the reorganizing procedure of Link and Joint Module is necessary, like as enumerating the kinematically identical assembly group of several links and joints. Thus, we draw a G, directed graph in a first step. Because, directed graph contains the path information between adjacent Link Module and Joint Module. From the directed graph,G, we can incite the Incidence Matrix, M(G). The incidence matrix, M(G), contains the contact information of the Link (Joint) Module and the type of Link (Joint). At the end of this paper, we generalize the modular information as a matrix form, A(G). From this matrix, we can make a population of assembly status. That is the finial output of this paper.

• Nuclear Engineering and Technology
• /
• 제54권10호
• /
• pp.3943-3948
• /
• 2022

Single-photon emission computed tomography is one of the reliable pin-by-pin verification techniques for spent-fuel assemblies. One of the challenges with this technique is to increase the total fuel assembly verification speed while maintaining high verification accuracy. The aim of the present study, therefore, was to develop an artificial intelligence (AI) algorithm-based tomographic image analysis technique for partial-defect verification of fuel assemblies. With the Monte Carlo (MC) simulation technique, a tomographic image dataset consisting of 511 fuel-rod patterns of a 3 × 3 fuel assembly was generated, and with these images, the VGG16, GoogLeNet, and ResNet models were trained. According to an evaluation of these models for different training dataset sizes, the ResNet model showed 100% pattern estimation accuracy. And, based on the different tomographic image qualities, all of the models showed almost 100% pattern estimation accuracy, even for low-quality images with unrecognizable fuel patterns. This study verified that an AI model can be effectively employed for accurate and fast partial-defect verification of fuel assemblies.