A reference model for common understanding of capabilities and skills in manufacturing

IF 0.7 4区 计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS At-Automatisierungstechnik Pub Date : 2023-02-01 DOI:10.1515/auto-2022-0117
Aljosha Köcher, Alexander Belyaev, Jesko Hermann, Jürgen Bock, Kristof Meixner, Magnus Volkmann, Michael Winter, Patrick Zimmermann, Stephan Grimm, Christian Diedrich
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引用次数: 12

Abstract

Abstract In manufacturing, many use cases of Industrie 4.0 require vendor-neutral and machine-interpretable information models to describe, implement and execute resource functions. Such models have been researched under the terms capabilities and skills . Standardization of such models is required, but currently not available. This paper presents a reference model developed jointly by members of various organizations in a working group of the Plattform Industrie 4.0 . This model covers definitions of most important aspects of capabilities and skills. It can be seen as a basis for further standardization efforts.
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一个通用的制造业能力和技能理解的参考模型
在制造业中,工业4.0的许多用例需要供应商中立和机器可解释的信息模型来描述、实现和执行资源功能。这些模型在能力和技能这两个术语下进行了研究。这些模型的标准化是必需的,但目前还没有。本文提出了一个由工业4.0平台工作组中各组织成员共同开发的参考模型。该模型涵盖了能力和技能的最重要方面的定义。它可以被看作是进一步标准化工作的基础。
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来源期刊
At-Automatisierungstechnik
At-Automatisierungstechnik 工程技术-自动化与控制系统
CiteScore
2.00
自引率
10.00%
发文量
99
审稿时长
6-12 weeks
期刊介绍: Automatisierungstechnik (AUTO) publishes articles covering the entire range of automation technology: development and application of methods, the operating principles, characteristics, and applications of tools and the interrelationships between automation technology and societal developments. The journal includes a tutorial series on "Theory for Users," and a forum for the exchange of viewpoints concerning past, present, and future developments. Automatisierungstechnik is the official organ of GMA (The VDI/VDE Society for Measurement and Automatic Control) and NAMUR (The Process-Industry Interest Group for Automation Technology). Topics control engineering digital measurement systems cybernetics robotics process automation / process engineering control design modelling information processing man-machine interfaces networked control systems complexity management machine learning ambient assisted living automated driving bio-analysis technology building automation factory automation / smart factories flexible manufacturing systems functional safety mechatronic systems.
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