Integrating different information types within AutomationML

Lüder, Arndt; Schmidt, Nicole; Rosendahl, Ronald; John, Michael

doi:10.1109/etfa.2014.7005275

Cited by 21 publications

(5 citation statements)

References 10 publications

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“…The main aim of AutomationML is to join engineering tools of different domains such as; process control engineering, mechanical plant engineering, electrical design, process engineering, robot programming, PLC programming, HMI development etc. The modelling features of various data formats was analyzed by [22]. Table 2 is an aggregated representation of [22]'s detailed study.…”

Section: Literature Reviewmentioning

confidence: 99%

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An AutomationML model for plug-and-produce assembly systems

Danny

Ferreira

Lohse

et al. 2017

2017 IEEE 15th International Conference on Industrial Informatics (INDIN)

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Section: Literature Reviewmentioning

confidence: 99%

“…The modelling features of various data formats was analyzed by [22]. Table 2 is an aggregated representation of [22]'s detailed study. AML provides a common language for different engineering tools and links for detailed engineering information, which is easily exchangeable between multi-engineering disciplines and projects.…”

Section: Literature Reviewmentioning

confidence: 99%

An AutomationML model for plug-and-produce assembly systems

Danny

Ferreira

Lohse

et al. 2017

2017 IEEE 15th International Conference on Industrial Informatics (INDIN)

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“…This gives the defined hierarchy higher priority than any other object relations that can be represented by using separate link-objects called CAEX-InternalLinks [20]. Lüder et al [21] have shown how additional information (not specified in the standard) can be appended to an existing AutomationML model, allowing all engineering data to be contained in one consistent data set.…”

Section: A Process Engineering State Of the Artmentioning

confidence: 99%

Organizing IoT Systems-of-Systems from standardized engineering data

Carlsson¹,

Hegedűs

Delsing

et al. 2016

IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society

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Abstract-Tackling current challenges in production automation requires the involvement of new concepts like Internet of Things, System-of-Systems and local automation clouds. The objective of this paper is to address the actual process of defining a cloud based automation system. More specifically the design, engineering, operation and maintenance of an automation system must be captured and managed between all stakeholders involved. This is critical to create the expected benefits from the local automation cloud approach.This paper addresses the capability of capturing plant designs and coordinating information exchange based on the captured architecture. For this purpose an architectural componentPlant Description -is proposed to be used in the Arrowhead Framework, based on already existing plant automation standards. An overview of methodologies on how it can interact with the Arrowhead Framework's Orchestration process describes the usefulness in managing large-scale automation systems. A qualitative evaluation for one of the proposed approaches is also described in a water control use case that can be found both in process and building automation.

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“…We propose to solve this problem by implementing a neutral data format based on AutomationML standardized in IEC 62714 [7], allowing to exchange data between different tools used in both offline and online stages. The DED process data (AM paths and process parameters) are generated and stored on an AutomationML file.…”

Section: Introductionmentioning

confidence: 99%

AutomationML for Data Exchange in the Robotic Process of Metal Additive Manufacturing

Babcinschi

Freire

Neto

et al. 2019

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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Flexibility, adaptability and standardization of multidisciplinary production processes are key issues for today's industry. The digitalization of industry partially helps to overcome these challenges, leading to the need for efficient management of data. AutomationML has been pointed as a solution to solve the problem of data exchange between heterogeneous engineering tools landscape. This paper introduces a practical approach for data exchange on a production-engineering environment linked to Metal Additive Manufacturing (MAM). The proposed approach allows the exchange of data/information between different engineering tools using AutomationML Engine. For example, the MAM paths can be edited and enriched with information along the different stages of the process (design, simulation, robotics) using a neutral format. In the sphere of Direct Energy Deposition (DED) technologies it is proposed a practical use case for data exchange and editing, from computer aided design (CAD), to path planning, to process parameters definition, to robot programming. Results demonstrated the effectiveness of the proposed AutomationML-based solution.

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Integrating different information types within AutomationML

Cited by 21 publications

References 10 publications

An AutomationML model for plug-and-produce assembly systems

An AutomationML model for plug-and-produce assembly systems

Organizing IoT Systems-of-Systems from standardized engineering data

AutomationML for Data Exchange in the Robotic Process of Metal Additive Manufacturing

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