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Far vs. Near: A Decision Framework for Cloud and Edge Use in the process Industry 22

Far vs. Near: A Decision Framework for Cloud and Edge Use in...

引用

22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Vogt, Lucas Charania, Zohra Urbas, Leon Process-to-Order Lab TU Dresden Dresden Germany Process Control Systems TU Dresden Dresden Germany

ISBN: (纸本)9798331527471

The technology readiness levels of cloud infrastructure and edge devices have increased significantly in recent years. This means that companies now have a growing number of computing environments at their disposal that could be suitable for the computing and control tasks involved in their production processes. Consequently, the need arises to select the best computing environment based on objective criteria and metrics. In order to create the basis for such a decision-making process, first an overview of the definitions and a comparison between edge and cloud environments is provided. Then a decision-making framework is derived that aims to facilitate this selection process. This is accomplished by providing a set of criteria that can be detailed to analyze a given use case. This analysis is then represented in a custom radar chart, which offers decision-makers a compact but meaningful representation of the decision space. Finally, the limits and future potentials of such a decision-making framework are discussed. © 2024 IEEE.

关键词： Cloud platforms

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Bringing Human Cognition to Machines: Introducing Cognitive Edge Devices for the process Industry 22

Bringing Human Cognition to Machines: Introducing Cognitive ...

引用

22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Charania, Zohra Vogt, Lucas Klose, Anselm Urbas, Leon Process Control Systems TU Dresden Dresden Germany Process-to-Order Lab TU Dresden Dresden Germany

ISBN: (纸本)9798331527471

In the era of Industry 4.0 (I4.0), Cyber Physical Production systems (CPPS) and upcoming industrial transformations, there's a great impulse for smarter, more connected, and adaptable industries. To support this shift, our industrial devices need to be upgraded. They should not only do their usual tasks reliably but also support new technologies like Artificial Intelligence (AI), Machine Learning (ML), Digital Twins (DT), etc. seamlessly. This is where cognition in devices becomes significant. This paper showcases an innovative cognitive system design for edge devices for control, drawing inspiration from the well-established concept of cognitive control. This approach highlights the symphonious existence of conscious (controlled) and unconscious (automatic) processing. The system architecture demonstrates the concurrent processing of real-time tasks, like control loops, field devices, etc., and non-real-time tasks such as AI, ML, Neural Network (NN) models, DT models, etc. within the edge device. This corresponds to the unconscious and conscious cognitive functions in human beings. This paper outlines the characteristics of such cognitive devices. The potential technologies that can help in achieving these characteristics like virtualization, multi-core edge devices, concurrency, etc. have also been explored. Additionally, a proof-of-concept demonstration use case has been presented that exhibits the implementation of the Open Cognitive control systems (OCCS) architecture in edge devices. This work sets a stepping stone towards making industrial devices smarter. © 2024 IEEE.

关键词： artificial intelligence cognition containerization edge device process industry real-time systems

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A Prototype for Navigation in Signed Directed Graphs of Chemical processes 28

A Prototype for Navigation in Signed Directed Graphs of Chem...

引用

28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Hamedi, Nazanin Richter, Julia Schrank, Bernhard Lischinski, Eric Chen, Jiaxin Sun, Xiaoyu Klose, Anselm Urbas, Leon TU Dresden DFG RTG Conducive Design of Cyber Physical Systems Dresden Germany TU Dresden Process Control Systems Dresden Germany TU Dresden Process Control Systems Process-to-Order Lab Dresden Germany TU Dresden Process Control Systems & Process Systems Engineering Dresden Germany

ISBN: (纸本)9798350339918

Signed Directed Graphs (SDGs) are among the very beneficial, and well-known tools for fault diagnosis in chemical process plants. Based on the size of the process plant, their corresponding SDGs can be very large in size;and therefore, significantly difficult to navigate. Besides that, the recent advancement in semantic description of process structures and intelligent process and Instrumentation Diagrams (P&IDs), has led to the development of several computer tools for navigating in a process plant structure and examining the connectivity of different process equipment to each other. In this study a prototype for an intelligent P&ID, in which the SDG is considered to help the user understand the influence of process parameters on each other is developed. Requirements were derived and implemented as a click prototype, using Axure RP. The evaluation results indicate that despite the high understandability of the prototype, the cognitive efforts for linking the information derived from the SDG with the plant's P&ID scheme are still too high for achieving a good overall usability. © 2023 IEEE.

关键词： Directed graphs

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Transformation of process functions to the Module Type Package utilizing System control Diagrams 28

Transformation of process functions to the Module Type Packa...

引用

28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Kock, Tobias Klose, Anselm Ingebringsten, Idar Pe Bittorf, Lukas Lorenz, Julius Urbas, Leon TU Dresden Process-to-Order-Lab Dresden Dresden Germany Oslo Norway Semodia GmbH Radebeul Germany TU Dresden Process Control Systems Dresden Germany

ISBN: (纸本)9798350339918

Modular process plants require a new interaction of process engineering and automation engineering. During the engineering of process Equipment Assemblies (PEA) the automation functions are encapsulated in services which represent process operations. In this work an approach is presented, where System control Diagrams (SCD) are utilized to create a transition from process operations to automation functions to services all on the basis of the Piping and Instrumentation Diagram (P&ID). Using this method, a comprehensible graphical and machine-readable link between both sides is created. In combination with existing tools, it is shown that part of the automation could already be prepared during the design of the P&ID. The proposed concept is evaluated using a water deionization PEA. © 2023 IEEE.

关键词： Automation

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Towards cloud-based control-as-a-Service for modular process Plants 28

Towards cloud-based Control-as-a-Service for modular Process...

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Vogt, Lucas Klose, Anselm Khaydarov, Valentin Vockeroth, Christian Endres, Christian Urbas, Leon TU Dresden Process-to-Order Lab Dresden Germany Sartorius Stedim Systems GmbH Guxhagen Germany Sartorius Stedim Biotech GmbH Göttingen Germany TU Dresden Process Control Systems Dresden Germany

ISBN: (纸本)9798350339918

BACKGROUND: Computational and data-intensive technologies such as model predictive control and artificial intelligence have the potential to increase process yields in the process industry. In modular plant designs, the flexible and difficult-to-predict use of a particular module presents the challenge of providing the right amount of data, computing power, and storage capacity to use these technologies in each ***: Simplifying the deployment and reconfiguration of compute-intensive applications for modular ***: Reviewing the current state of the art and combining the modular plant concept with a cloud-based control-as-a-Service (CaaS) ***: A cloud-based, containerized CaaS concept that supports the deployment compute- and data-intensive methods for modular plants. The complementing communication stack consisting of standards such as APL, TSN and OPC UA ***: The proposed architecture simplifies IT/OT integration, eases the deployment of compute-intensive technologies, and allows for GMP compliant pre-qualification of software modules. However, the limiting factors like plant safety, conformity to regulations and widespread architecture adoption are not covered in detail and will be subject of future research. © 2023 IEEE.

关键词： Computing power

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Bringing Human Cognition to Machines: Introducing Cognitive Edge Devices for the process Industry

Bringing Human Cognition to Machines: Introducing Cognitive ...

引用

IEEE International Conference on Industrial Informatics (INDIN)

作者： Zohra Charania Lucas Vogt Anselm Klose Leon Urbas Chair of Process Control Systems TU Dresden Dresden Germany Process-to-Order Lab TU Dresden Dresden Germany

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

关键词： Industries Production systems process control systems architecture Machine learning Cognition Real-time systems Reliability Virtualization Informatics

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Far vs. Near: A Decision Framework for Cloud and Edge Use in the process Industry

Far vs. Near: A Decision Framework for Cloud and Edge Use in...

引用

IEEE International Conference on Industrial Informatics (INDIN)

作者： Lucas Vogt Zohra Charania Leon Urbas Process-to-Order Lab TU Dresden Dresden Germany Chair of Process Control Systems TU Dresden Dresden Germany

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

关键词： Measurement Industries Spaceborne radar Decision making process control Production Companies Aerospace electronics Informatics

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A Prototype for Navigation in Signed Directed Graphs of Chemical processes

A Prototype for Navigation in Signed Directed Graphs of Chem...

引用

International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Nazanin Hamedi Julia Richter Bernhard Schrank Eric Lischinski Jiaxin Chen Xiaoyu Sun Anselm Klose Leon Urbas DFG RTG Conducive Design of Cyber Physical Systems TU Dresden Dresden Germany Chair of Process Control Systems TU Dresden Dresden Germany Chair of Process Control Systems Process-to-Order Lab TU Dresden Dresden Germany Process Control Systems & Process Systems Engineering TU Dresden Dresden Germany

Signed Directed Graphs (SDGs) are among the very beneficial, and well-known tools for fault diagnosis in chemical process plants. Based on the size of the process plant, their corresponding SDGs can be very large in size; and therefore, significantly difficult to navigate. Besides that, the recent advancement in semantic description of process structures and intelligent process and Instrumentation Diagrams (P&IDs), has led to the development of several computer tools for navigating in a process plant structure and examining the connectivity of different process equipment to each other. In this study a prototype for an intelligent P&ID, in which the SDG is considered to help the user understand the influence of process parameters on each other is developed. Requirements were derived and implemented as a click prototype, using Axure RP. The evaluation results indicate that despite the high understandability of the prototype, the cognitive efforts for linking the information derived from the SDG with the plant’s P&ID scheme are still too high for achieving a good overall usability.

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Demonstrating Containerization of Model Predictive control for Modular Plants

Demonstrating Containerization of Model Predictive Control f...

引用

Industrial Cyber-Physical systems (ICPS)

作者： Lucas Vogt Zohra Charania Jonathan Mädler Julius Lorenz Helaleh Badrnoebashar Amy Koch Leon Urbas Process-to-Order Lab TU Dresden Dresden Germany Chair of Process Control Systems TU Dresden Dresden Germany Process Systems Engineering Group TU Dresden Dresden Germany

ISBN: (数字)9798350363012

ISBN: (纸本)9798350363029

Model predictive control has the potential to increase yields in the process industry, but its deployment is limited by high computational cost. In multi-purpose, modular plant concepts, it is particularly difficult to predict the whole variety of products for which a specific module will be used throughout its lifespan. During module manufacturing, this results in the challenge of allocating the correct computing, memory, and communication capacities to a module so that a model-predictive control application with currently unknown hardware requirements can be used later. The difficulty of this task often prevents the desirable deployment of model predictive control in production environments. The aim of this publication is therefore to demonstrate a simplified deployment and reconfiguration of model predictive control applications for modular plants through containerization. After an overview of the current state of the art, we present the underlying automation architecture based on modular plant concepts combined with a cloud-like automation approach enabled by containerization of the control applications. The feasibility of the chosen approach is demonstrated by implementing a proof-of-concept demonstrator. Subsequently, lessons learned from the demonstrator are discussed and future improvement potentials are identified, which will be the subject of future research.

关键词： Industries Automation Memory management Production Software Hardware Manufacturing

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Standards for Information Models Considering Knowledge Distribution in Modular Plants

Standards for Information Models Considering Knowledge Distr...

引用

IEEE International Conference on Industrial Informatics (INDIN)

作者： Amy Koch Nazanin Hamedi Lukas Furtner Tobias Kock Anselm Klose Jonathan Mädler Process Systems Engineering Group TU Dresden Dresden Germany Research Training Group 2323 TU Dresden Dresden Germany Chair of Process Control Systems Process-to-Order Lab TU Dresden Dresden Germany

For various applications, information models described in standards are available to enable a digital data exchange. For modular process plants, where different domains are interacting in different phases of the plant lifecycle, single, existing standards are not *** this work, we analyze the most relevant standards for process engineering, namely OntoCAPE, DEXPI, and IEC 61512, in regards to their application to support the lifecycle of modular process plants, which are described in the VDI 2776 and VDI/VDE/NAMUR 2658 standards. By challenging the standards with competency questions derived from a specific use case, we discuss which information models are most suitable for all individual domains in each lifecycle phase. The result is the specification of parts of these standards which are needed to create a fully digital support for modular process plants on the example of the introduced use case.

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