中国工程院“新一代智能制造”解读

工业4.0创新平台 发布

2018年1月22日

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工业4.0研讨会第78期

研讨会页面链接

http://www.innovation4.cn/event/103

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Intelligent Manufacturing Systems— A Tentative Forecast

J.Hatvany, L.Nemes

Manufacturing systems research and development started by linking extant modules (CAD, NC Programming, DNC, Automated Assembly, Scheduling) to each other. As systems have grown in size and complexity, these methods have become inefficient and research is now concentrated on developing synthesis methods for large-scale hierarchical system design. These methods, however, in the practical use of which the authors have gained some experience, are mostly deterministically based and assume either the predictability of all eventualities, or a reversion to human control when unforeseen (algorithmically unstipulated) situations occur.

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The scale and complexity of large manufacturing systems will grow so rapidly as to render both the above alternatives impracticable. Systems will have to possess an in-built resilience with respect to unforeseen situations, based on the ability to recognize trends and situations in real time from large amounts of data, to use these perceptions to solve the problem of finding an optimal recovery strategy, to carry out the required decision-making processes and finally to implement and check the decisions taken. Such an approach requires the development of novel, heterarchical manufacturing model definition and analysis methods, for which the present tools of Artificial Intelligence research hold promise, but are not yet adequate.

Keywords

Manufacturing processes, artificial intelligence, computer control system, synthesis models, self-adjusting systems

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Designing and implementation of an intelligent manufacturing system

Fernando L.F. Almeida

1Faculty of Engineering of University of Porto (PORTUGAL)

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almd@fe.up.pt

Received June 2011

Accepted September 2011

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The IMS MISSION Architecture For Distributed Manufacturing Simulation

Charles McLean

Frank Riddick

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National Institute of Standards and Technology (NIST)

Gaithersburg, MD (USA)

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Next Generation Manufacturing Systems in the IMS Program

T. Kurihara

Fuji Electric Co., Ltd

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Tokyo 100, Japan

Tel: +81 335368825 Fax: +81 33201 0750

kurihara@fujielectric.coJp

J. Jordan

Consortium for Advanced Manufacturing - International

3301 Airport Freeway, Suite 324

Bedford, TX 76021 USA

Tel: +18178601654 Fax: +18172756450

jajordan@ix.netcom.com

P. Bunce

Consortium for Advanced Manufacturing - International

20 Market Street

Poole, Dorset, BH15 lNF, UK

Tel: +441202670717 Fax: +441202680698

peter@cam-i.demon.co.uk

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Intelligent Manufacturing Systems

DESIGN CONCEPT OF INTELLIGENT MANAGEMENT SYSTEMS

Galina Setlak, Sławomir Pieczonka

INTELLIGENT MANUFACTURING SYSTEM

Vaibhav D. Bhoj1, Shubham S. Abhang2, Gunvant S. Bhangale3 1,2,3Department of Mechanical Engineering, Sandip Foundation’s, Sandip Institute of Technology and Research Centre, SavitribaiPhule Pune University, (India)

An Overview of GNOSIS:

Knowledge Systematization

Masayoshi FUSE

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Sumitomo Electric Ind. Ltd., Shimaya, 1-1-3, Osaka, 554-0024, Japan

Abstract. This paper gives a brief, introductory overview of the GNOSIS project, whose main objective is to develop engineering frameworks and knowledge-based systems to realize the Post Mass-Production Paradigm.

The full introduction of GNOSIS can be found on the World-Wide Web at http://www.modularisation.com/../gnosis/gnosis.htm

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