• Title/Summary/Keyword: Intelligent Manufacturing Systems

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A Study on the Internet Control and Monitoring System using an Embedded System (임베디드 시스템을 이용한 인터넷 제어감시 시스템에 관한 연구)

  • Haeng-Choon Chun
    • Journal of Advanced Marine Engineering and Technology
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    • v.28 no.5
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    • pp.811-817
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    • 2004
  • Recently embedded systems are widely used in various industrial fields as supervisory controller because they have many merits. One of merits seems to be that operating environment of embedded system is the same as development environment using PC. That makes developing and manufacturing period shorten and also proper time to market Most of all machinery have sequential control system for their maneuvering which is composed of relays. contacts. timers. etc. In this paper. software sequential control system is proposed to be able to replace hardware sequential control system by using embedded system A lot of merits by the software sequential control system can be expected in the respect of economic reproduction, intelligent technologies and utilities, And porting of LINUX operating system to embedded system is carried out and device drivers and interface boards for LINUX 05 are designed for controlling air compressor by software Internet remote control and monitoring system of air compressor is implemented with Java script and CGI for these purposes. The experiment for operating air compressor system is taken through internet networks. The results show that developed system can be used for real plant.

Design of Real-Time Newral-Network Controller Based-on DSPs of a Assembling Robot (DSP를 이용한 조립용 로봇의 실시간 신경회로망 제어기 설계)

  • 차보남
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1999.10a
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    • pp.113-118
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    • 1999
  • This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important n the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

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Study on the Guided Tabu Search for the Vehicle Routing Problem (차량경로 문제에 대한 Guided Tabu 검색)

  • Lee, Seung-Woo;Lee, Hwa-Ki
    • Journal of the Korea Safety Management & Science
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    • v.10 no.1
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    • pp.145-153
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    • 2008
  • The vehicle routing problem determines each vehicle routes to find the transportation costs, subject to meeting the customer demands of all delivery points in geography. Vehicle routing problem is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study aims to develop a heuristic method which combines guided local search with a tabu search in order to minimize the transportation costs for the vehicle routing assignment and uses ILOG programming library to solve. The computational tests were performed using the benchmark problems. And computational experiments on these instances show that the proposed heuristic yields better results than the simple tabu search does.

Acquisition and Refinement of State Dependent FMS Scheduling Knowledge Using Neural Network and Inductive Learning (인공신경망과 귀납학습을 이용한 상태 의존적 유연생산시스템 스케쥴링 지식의 획득과 정제)

  • 김창욱;민형식;이영해
    • Journal of Intelligence and Information Systems
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    • v.2 no.2
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    • pp.69-83
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    • 1996
  • The objective of this research is to develop a knowledge acquisition and refinement method for a multi-objective and multi-decision FMS scheduling problem. A competitive neural network and an inductive learning algorithm are integrated to extract and refine necessary scheduling knowledge from simulation outputs. The obtained scheduling knowledge can assist the FMS operator in real-time to decide multiple decisions simultaneously, while maximally meeting multiple objective desired by the FMS operator. The acquired scheduling knowledge for an FMS scheduling problem is tested by comparing the desired and the simulated values of the multiple objectives. The result show that the knowledge acquisition and refinement method is effective for the multi-objective and multi-decision FMS scheduling problems.

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Study on Pressure System for Curved Glass Fabrication of a Smart Phone (스마트폰 곡면유리 성형을 위한 가압시스템 연구)

  • Jang, Chae Eun;Kim, Kihyun;Park, Jaehyun
    • Journal of the Semiconductor & Display Technology
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    • v.20 no.2
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    • pp.51-55
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    • 2021
  • With the recent development of various smartphone designs in the smartphone market, the use of curved cover glass has been required, and interest in curved glass production has increased. In this paper, we designed a pressurization system that simplified the size of the system using a wedge amplification mechanism for smartphone curved glass molding systems. The pressurization system consisted of a linear motor, a wedge, and a force sensor. The wedge was used to amplify the force, and the piezoelectric sensor was used to measure the force. In addition, the proposed amplification mechanism was confirmed to have an error of 1.27% through an experiment compared to the simulation, and the pressurization error of 0.76% for the pressurization profile 3,500N was verified through an experiment.

Illumination correction via improved grey wolf optimizer for regularized random vector functional link network

  • Xiaochun Zhang;Zhiyu Zhou
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.3
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    • pp.816-839
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    • 2023
  • In a random vector functional link (RVFL) network, shortcomings such as local optimal stagnation and decreased convergence performance cause a reduction in the accuracy of illumination correction by only inputting the weights and biases of hidden neurons. In this study, we proposed an improved regularized random vector functional link (RRVFL) network algorithm with an optimized grey wolf optimizer (GWO). Herein, we first proposed the moth-flame optimization (MFO) algorithm to provide a set of excellent initial populations to improve the convergence rate of GWO. Thereafter, the MFO-GWO algorithm simultaneously optimized the input feature, input weight, hidden node and bias of RRVFL, thereby avoiding local optimal stagnation. Finally, the MFO-GWO-RRVFL algorithm was applied to ameliorate the performance of illumination correction of various test images. The experimental results revealed that the MFO-GWO-RRVFL algorithm was stable, compatible, and exhibited a fast convergence rate.

Image Enhancement Algorithm and its Application in Image Defogging

  • Jun Cao
    • Journal of Information Processing Systems
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    • v.19 no.4
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    • pp.465-473
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    • 2023
  • An image enhancement algorithm and image defogging method are studied in this paper. The formation of fog and the characteristics of fog image are analyzed, and the fog image is preprocessed by histogram equalization method; then the additive white noise is removed by foggy image attenuation model, the atmospheric scattering physical model is constructed, the image detail characteristics are enhanced by image enhancement method, and the visual effect of defogging image is enhanced by guided filtering method. The proposed method has a good defogging effect on the image. When the number of training iterations is 3,000, the peak signal-to-noise ratio of the proposed method is 43.29 dB and the image structure similarity is 0.9616, indicating excellent image defogging effect.

Storing and Retrieving Motion Capture Data based on Motion Capture Markup Language and Fuzzy Search (MCML 기반 모션캡처 데이터 저장 및 퍼지 기반 모션 검색 기법)

  • Lee, Sung-Joo;Chung, Hyun-Sook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.2
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    • pp.270-275
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    • 2007
  • Motion capture technology is widely used for manufacturing animation since it produces high quality character motion similar to the actual motion of the human body. However, motion capture has a significant weakness due to the lack of an industry wide standard for archiving and retrieving motion capture data. In this paper, we propose a framework to integrate, store and retrieve heterogeneous motion capture data files effectively. We define a standard format for integrating different motion capture file formats. Our standard format is called MCML (Motion Capture Markup Language). It is a markup language based on XML (eXtensible Markup Language). The purpose of MCML is not only to facilitate the conversion or integration of different formats, but also to allow for greater reusability of motion capture data, through the construction of a motion database storing the MCML documents. We propose a fuzzy string searching method to retrieve certain MCML documents including strings approximately matched with keywords. The method can be used to retrieve desired series of frames included in MCML documents not entire MCML documents.

A Study on the Node Split in Decision Tree with Multivariate Target Variables (다변량 목표변수를 갖는 의사결정나무의 노드분리에 관한 연구)

  • Kim, Seong-Jun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.4
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    • pp.386-390
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    • 2003
  • Data mining is a process of discovering useful patterns for decision making from an amount of data. It has recently received much attention in a wide range of business and engineering fields. Classifying a group into subgroups is one of the most important subjects in data mining. Tree-based methods, known as decision trees, provide an efficient way to finding the classification model. The primary concern in tree learning is to minimize a node impurity, which is evaluated using a target variable in the data set. However, there are situations where multiple target variable should be taken into account, for example, such as manufacturing process monitoring, marketing science, and clinical and health analysis. The purpose of this article is to present some methods for measuring the node impurity, which are applicable to data sets with multivariate target variables. For illustration, a numerical cxample is given with discussion.

Methodology for Automate Negotiation for Order Transaction of Injection Mold Manufacturer (사출금형제조업체의 주문처리를 위한 자동협상방법론)

  • 박영재;최형림
    • Journal of Intelligence and Information Systems
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    • v.10 no.1
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    • pp.47-63
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    • 2004
  • Today, there are several markets in cyber space where companies trade electronically due to the development of Information Technology. On the other hand, the most important thing in trades is negotiation. So, in order to support current business practices as well as new ones on the Internet, electronic commerce systems need an ability to negotiate. In this paper, proposed is a method by which a seller can be supported by an agent which plays a role in negotiation process among small and medium companies especially injection mold manufacturer. If the manufacturing capacity cannot afford to produce all orders, the manufacturer may want to extend due dates and the buyers may want to discount prices. The negotiation agent discussed in this paper cooperates with the schedule agent to get due-date information, and performs a role in one (seller)-to-many (buyer) negotiation processes.

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