System Architectures for Cyber-Physical Production Systems enabling Self-X and Autonomy

Stock, Daniel; Bauernhansl, Thomas; Weyrich, Michael; Feurer, Matthias; Wutzke, Rolf

doi:10.1109/etfa46521.2020.9212182

Cited by 9 publications

(3 citation statements)

References 22 publications

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“…The Asset Administration Shell (AAS) [6], [13] can provide such a standardized representation. The use of AAS for service deployment has been investigated before [7], showing that it can successfully negotiate deployment requirements.…”

Section: State Of the Artmentioning

confidence: 99%

“…For devices, without claim to completeness, it can include among others: Total resources, e.g., vCPU, RAM, and storage, as well as communication interfaces; and dynamic information about current resource usage. A selfdescription of the topology [7] describes links between devices (cf. Table I), e.g., latency for communication.…”

Section: Self-description Of the Infrastructurementioning

confidence: 99%

“…To complement the infrastructure's self-description, a selfdescription of the application [7], [8] can also be realized through a collection of AAS:…”

Section: Self-description Of the Applicationmentioning

confidence: 99%

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Self-Adaptive Service Deployment for Resilience of Smart Manufacturing Architectures

Van,

da Silva,

Knissel

et al. 2023

2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)

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Recent advances in the manufacturing sectorincluding edge-to-cloud continuum, machine learning, and digitalization -can enable smart manufacturing solutions, such as control optimization and predictive maintenance. One challenge in new system architectures is the efficient resource management under changing conditions while meeting process requirements, such as latency, when deploying software services. To address this, we propose an approach for self-adaptive service deployment that increases the resilience of smart manufacturing systems. We combine self-adaptation principles with run-time models -that describe the system in the form of the standardized Asset Administration Shell -to enable flexible software architectures for manufacturing. The proposed solution comprises the continuous adaptation of the service deployment in response to system changes, such as resource exhaustion or failure, to ensure an optimized operation. An evaluation of an example manufacturing use case shows that the proposed solution leads to lower execution latency and continuation of production in situations with low resources, e.g., through failures, compared to less flexible deployment approaches.

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Section: State Of the Artmentioning

confidence: 99%

Section: Self-description Of the Infrastructurementioning

confidence: 99%

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Self-Adaptive Service Deployment for Resilience of Smart Manufacturing Architectures

Van,

da Silva,

Knissel

et al. 2023

2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)

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A Digital Twin Platform for Industrie 4.0

et al. 2022

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In an Industrie 4.0 (I4.0), rigid structures and architectures applied in manufacturing and industrial information technologies today will be replaced by highly dynamic and self-organizing networks. Today’s proprietary technical systems lead to strictly defined engineering processes and value chains. Interacting Digital Twins (DTs) are considered an enabling technology that could help increase flexibility based on semantically enriched information. Nevertheless, for interacting DTs to become a reality, their implementation should be based on open standards for information modeling and application programming interfaces like the Asset Administration Shell (AAS). Additionally, DT platforms could accelerate development and deployment of DTs and ensure their resilient operation.This chapter develops a suitable architecture for such a DT platform for I4.0 based on user stories, requirements, and a time series messaging experiment. An architecture based on microservices patterns is identified as the best fit. As an additional result, time series data should not be integrated synchronously and directly into AASs, but rather asynchronously, either via streams or time series databases. The developed DT platform for I4.0 is composed of specialized, independent, loosely coupled microservices interacting use case specifically either syn- or asynchronously. It can be structured into four layers: continuous deployment, shop-floor, data infrastructure, and business services layer. An evaluation is carried out based on the DT controlled manufacturing scenario: AAS-based DTs of products and manufacturing resources organize manufacturing by forming highly dynamic and self-organizing networks.Future work should focus on a final, complete AAS integration into the data infrastructure layer, just like it is already implemented on the shop-floor and business services layers. Since with the standardized AAS only one interface type would then be left in the DT platform for I4.0, DT interaction, adaptability, and autonomy could be improved even further. In order to become part of an I4.0 data space, the DT platform for I4.0 should support global discovery, data sovereignty, compliance, identity, and trust. For this purpose, Gaia-X Federation Services should be implemented, e.g., as cross-company connectors.

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