• Title/Summary/Keyword: paper machine

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Analysis of Assembly Relationship for Digital Micro Milling Machine (디지털 마이크로 밀링머신의 조립성 분석)

  • Choi, Sung-Il;Subramaniyam, Murali;Park, Sang-Ho
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.16 no.5
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    • pp.101-107
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    • 2007
  • Assembly is mentioned as important process saving time and cost where we produce the machine with many parts relationships. In this study, parts assembly relationship is analysed for assembly information of micro milling machine which have been developing for research. Liaison diagram, datum flow chain and assembly tree are applied to discuss assembly characteristics of micro milling machine model. We can find out the characteristics of micro machine assembly and discuss about facility of assembly. Some analysis in this paper about micro milling machine will give a useful tools for assembly. We knew that the predicted results from analysis in this study are alignment and clearance among the parts. The 3D model of micro machine which is studied in this paper is not a complete model. Main parts of a micro milling machine are used and presented.

A Summary of Recent Pilot Machine and Commercial Machine Trials Comparing a New Microparticle Retention System with Existing Microparticle Technologies

  • Johnson, Gray;Gerli, Alessandra
    • Journal of Korea Technical Association of The Pulp and Paper Industry
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    • v.34 no.5
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    • pp.86-92
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    • 2002
  • The benefits of high performance retention systems have been long recognized by the paper maker. The inter-relation between chemical retention and drainage and their effect on paper production efficiency and paper quality is significant. The subject of this paper is a summary of recent studies comparing three microparticle programs made under highly controlled pilot and commercial paper machine conditions. The results presented in this paper suggest that, in addition to improvements in machine operation, the retention, drainage and formation program can have a marked influence on the paper quality. Improvement of the topographical characteristics of the base paper was observed when the microparticle was a colloidal borosilicate inorganic oxide.

Development of the paper bagging machine for grapes (휴대용 포도자동결속기 개발연구)

  • Park, K.H.;Lee, Y.C.;Moon, B.W.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.11 no.1
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    • pp.79-94
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    • 2009
  • The research project was conducted to develop a paper bagging machine for grape. This technology was aimed to highly reduce a labor for paper bagging in grape and bakery. In agriculture labor and farm population has rapidly decreased since 1980 in Korea so there was so limit in labor. In particular there is highly population in women and old age at rural area and thus labor cost is so high. Therefore a labor saving technology in agricultural sector might be needed to be replaced these old age with mechanical and labor saving tool in agriculture. The following was summarized of the research results for development of a paper bagging machine for grape. 1. Development of a new paper bagging machine for grape - This machine was designed by CATIA VI2/AUTO CAD2000 programme. - A paper bagging machine was mechanically binded a paper bag of grape which should be light and small size. This machine would be designed for women and old age with convenience during bagging work at the field site. - This machine was manufactured with total weight of less than 350g. - An overage bagging operation was more than 99% at the actual field process. - A paper bagging machine was designed with cartridge type which would be easily operated between rows and grape branches under field condition. - The type of cartridge pin was designed as a C-ring type with the length of 500mm which was good for bagging both grape and bakery. - In particular this machine was developed to easily operated among vines of the grape trees. 2. Field trials of a paper bagging machine in grape - There was high in grape quality as compared to the untreated control at the application of paper bagging machine. - The efficiency of paper bagging machine was 102% which was alternative tool for the conventional. - The roll pin of paper bagging machine was good with 5.3cm in terms of bagging precision. - There was no in grape quality between the paper bagging machine and the conventional method. - Disease infection and grape break was not in difference both treatments.

Vxworks Base Java Virtual Machine Development (VxWorks Base Java Virtual Machine 개발)

  • 박상현;고재진;민수영
    • Proceedings of the IEEK Conference
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    • 2002.06c
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    • pp.193-196
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    • 2002
  • Nowadays, many users use internet and many set-top box needs browser for Internet. so we need to develop a Java Virtual Machine to improve browser's performance. This paper has been studied a Java Virtual Machine based on Real-Time 05 Vxwroks. Java Virtual Machine handles Java byte-code quickly in Browser So, this paper has designed module and interfaces for Embedded Browser and Implemented them.

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Predictive maintenance architecture development for nuclear infrastructure using machine learning

  • Gohel, Hardik A.;Upadhyay, Himanshu;Lagos, Leonel;Cooper, Kevin;Sanzetenea, Andrew
    • Nuclear Engineering and Technology
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    • v.52 no.7
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    • pp.1436-1442
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    • 2020
  • Nuclear infrastructure systems play an important role in national security. The functions and missions of nuclear infrastructure systems are vital to government, businesses, society and citizen's lives. It is crucial to design nuclear infrastructure for scalability, reliability and robustness. To do this, we can use machine learning, which is a state of the art technology used in various fields ranging from voice recognition, Internet of Things (IoT) device management and autonomous vehicles. In this paper, we propose to design and develop a machine learning algorithm to perform predictive maintenance of nuclear infrastructure. Support vector machine and logistic regression algorithms will be used to perform the prediction. These machine learning techniques have been used to explore and compare rare events that could occur in nuclear infrastructure. As per our literature review, support vector machines provide better performance metrics. In this paper, we have performed parameter optimization for both algorithms mentioned. Existing research has been done in conditions with a great volume of data, but this paper presents a novel approach to correlate nuclear infrastructure data samples where the density of probability is very low. This paper also identifies the respective motivations and distinguishes between benefits and drawbacks of the selected machine learning algorithms.

A Special Case of Three Machine Flow Shop Scheduling

  • Yang, Jaehwan
    • Industrial Engineering and Management Systems
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    • v.15 no.1
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    • pp.32-40
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    • 2016
  • This paper considers a special case of a three machine flow shop scheduling problem in which operation processing time of each job is ordered such that machine 1 has the longest processing time, whereas machine 3, the shortest processing time. The objective of the problem is the minimization of the total completion time. Although the problem is simple, its complexity is yet to be established to our best knowledge. This paper first introduces the problem and presents some optimal properties of the problem. Then, it establishes several special cases in which a polynomial-time optimal solution procedure can be found. In addition, the paper proves that the recognition version of the problem is at least binary NP-complete. The complexity of the problem has been open despite its simple structure and this paper finally establishes its complexity. Finally, a simple and intuitive heuristic is developed and the tight worst case bound on relative error of 6/5 is established.

An Error Control for Media Multi-channel running on Machine to Machine Environment (사물 지능 통신 환경에서 미디어 다중 채널을 위한 오류 제어)

  • Ko, Eung-Nam
    • Journal of Advanced Navigation Technology
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    • v.18 no.1
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    • pp.74-77
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    • 2014
  • This paper suggested an error control for multi-channel running on machine to machine environment. This system is suitable for recovering software fault for multimedia CSCW(Computer Supported Cooperative Works) based on machine to machine environment. It is necessary for the system to be protected by reactivity of media service instance instead of breaking process of session. This paper explains a performance analysis of an error recovery system of M2M based computing collaboration environment using rule-based DEVS modeling and simulation techniques.

A Study on Structural Design and Evaluation of the High Precision Cam Profile CNC Grinding Machine (고 정밀 캠 프로파일 CNC 연삭기의 구조설계 및 평가에 관한 연구)

  • Lim, Sang-Heon;Shin, Sang-Hun;Lee, Choon-Man
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.10
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    • pp.113-120
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    • 2006
  • A cam profile CNC grinding machine is developed for manufacture of high precision contoured cams. The developed machine is composed of the high precision spindle using boll bearings, the high stiffness box layer type bed and the three axis CNC controller with the high resolution AC servo motor. In this paper, structural and modal analysis for the developed machine is carried out to check the design criteria of the machine. The analysis is carried out by FEM simulation using the commercial software, CATIA V5. The machine is modeled by placing proper shell and solid finite elements. And also, this paper presents the measurement system and experimental investigation on the modal analysis of a grinding machine. The weak part of the machine is found by the experimental evaluation. The results provide structure modification data for good dynamic behaviors. And safety of the machine was confirmed by the modal analysis of modified machine design. Finally, the cam profile grinding machine was successfully developed.

Analysis of Automatic Machine Learning Solution Trends of Startups

  • Lee, Yo-Seob
    • International Journal of Advanced Culture Technology
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    • v.8 no.2
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    • pp.297-304
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    • 2020
  • Recently, open source automatic machine learning solutions have been applied in many fields. To apply open source automated machine learning to real world problems, you need to write code with expertise in machine learning. Writing code without machine learning knowledge is challenging. To solve this problem, the automatic machine learning solutions provided by startups are made easy to use with a clean user interface. In this paper, we review automatic machine learning solutions of startups.

Using Machine Learning Technique for Analytical Customer Loyalty

  • Mohamed M. Abbassy
    • International Journal of Computer Science & Network Security
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    • v.23 no.8
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    • pp.190-198
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    • 2023
  • To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.