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29th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2024

作者： Shagufta Kleinert, Tobias Rwth Aachen University Information and Automation Systems for Process and Material Technology Aachen Germany

ISBN: (纸本)9798350361230

In a significant move towards enhancing flexibility in industrial automation, the development of adaptable and scalable control components (CCs) as control-related skills in process and manufacturing industry aims at supporting effective management of complex production systems. This research seeks to develop CC architecture design methods. As a basis, a unified library of elementary functions is designed to enable creation of CCs. With a focus on enabling dynamic CC composition and skill generation, we aim to provide a systematic and scalable approach to flexibility in control applications. The primary objective is to establish a proof of concept for the proposed function library, demonstrating its versatility and effectiveness via validating various procedures. Through the combination of a conceptual framework and prac-tical implementations, this paper validates the potential impact of a unified, composable CCs in enhancing adaptability and re-sponsiveness within control applications in industrial production. Furthermore, the machine-readable functionality description of CCs enhances their reusability and adaptability and thus increase the flexibility and efficiency of production processes. This lays the basis for semantic interoperability which is required to integrate the CC framework into capability-based control application configuration, particularly within the Industry 4.0 framework. © 2024 IEEE.

关键词： Reusability

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Flexible Control Configuration in Modular Plants via Control Function Library 29

Flexible Control Configuration in Modular Plants via Control...

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29th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2024

作者： Zhao, Yuanchen Shagufta Kleinert, Tobias Rwth Aachen University Information and Automation Systems for Process and Material Technology Aachen Germany

ISBN: (纸本)9798350361230

This paper presents the design, implementation, and validation of a Control Function Library to support standardized design and deployment of control functions for automated industrial process operation. The Control Function Library establishes a standardized set of control functions for chemical production. Five categories (Time-based, Continuous, Reversible, Stopping, and Ramping control functions) are developed and encapsulated in the first version of the library. The Control Function Library enables scalability by providing a flexible framework for adding or modifying control functions to accommodate specific production requirements. This scalability allows control systems to adapt to changing requirements or environments without significant redevelopment efforts, especially for capability-based operation configuration and execution. Furthermore, the reuse of Control Function Libraries across various projects or applications minimizes development time and resource costs by avoiding the need to re-engineer processes from scratch for each new modular plant. © 2024 IEEE.

关键词： Chemical variables control

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Bridging the Gap: A Python-to-Structured Text Compiler with IEC 61131-3 Compliance 29

Bridging the Gap: A Python-to-Structured Text Compiler with ...

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29th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2024

作者： Zhao, Yuanchen Eve, Alicia Miny, Torben Kleinert, Tobias Rwth Aachen University Information and Automation Systems for Process and Material Technology Aachen Germany

ISBN: (纸本)9798350361230

This paper introduces a high-level language compiler with IEC 61131-3 compliance capable of converting control function code written in Python into structured text. The Python-to-Structured Text Compiler aims to bridge the gap between modern language programming and PLC programming in industrial automation. The proposed Py2ST Compiler workflow includes parsing, transformation, code generation, and code import stages. The implementation of these phases is presented in this paper. And the compilation ability of the Py2ST Compiler is validated by a case study. Utilizing the Py2ST Compiler facilitates the development of PLC control functions within the Python environment. This capability enables the management of both IT and OT functions within a unified environment, enhancing the overall project's maintainability and reducing the development cycle. © 2024 IEEE.

关键词： Program compilers

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Automatic Generation of Submodel-Specific Classes with Predefined Meta-information Based on Submodel Templates 28

Automatic Generation of Submodel-Specific Classes with Prede...

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

作者： Garmaev, Igor Miny, Torben Kleinert, Tobias RWTH Aachen Information and Automation Systems for Process and Material Technology Aachen Germany

ISBN: (纸本)9798350339918

Asset Administration Shells are an essential component of Industry 4.0, and submodels are crucial to their functioning. However, the current method of generating submodels involves writing custom code, which can lead to code duplication and inconsistencies across submodels. To address these challenges, we propose an automatic generation of submodel-specific classes with predefined meta-information based on submodel templates. Our proposed solution aims to reduce code duplication, provide support in integrated development environments, ensure consistency across submodels, and facilitate the immediate publishing of submodel software development kits. This paper discusses the current approaches for instantiating submodels and their problems, the proposed approach, its requirements, advantages, and an outlook. © 2023 IEEE.

关键词： Automatic programming

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Source Component Shift Detection & Classification for Improved Remaining Useful Life Estimation in Alarm-Based Predictive Maintenance 23

Source Component Shift Detection & Classification for Improv...

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23rd International Conference on Control, automation and systems, ICCAS 2023

作者： Fathi, Kiavash Sadurski, Marcin Kleinert, Tobias Van De Venn, Hans Wernher Institute of Mechatronic Systems Zurich University of Applied Sciences Winterthur8400 Switzerland Rwth Aachen University Chair of Information and Automation Systems for Process and Material Technology Aachen52064 Germany

ISBN: (纸本)9788993215274

Predicting the remaining useful life (RUL) plays a significant role in reducing the downtime of operational assets and maintenance costs. While various predictive maintenance (PdM) studies have utilized sensor data to calculate RUL, valuable information from system alarms has often been overlooked or marginally used. This paper introduces the first-ever solely alarm-based PdM model for RUL estimation. To demonstrate the effectiveness of the proposed method in real-world production lines, the alarm data from two instances of milling machines, used for producing artificial bone joints, are utilized for PdM model development and testing. Additionally, given the varying operation hours of the machines and also the changes in the size of the produced bone joints, this study demonstrates the importance of pinpointing different subpopulations of the alarm data, called data modality (DM), for improved RUL estimation. As flexible and adaptable manufacturing required in Industry 4.0 results in constant changes in the distribution of the gathered data, this paper presents a systematic and generic approach for identifying different DMs, which results in a significant decrease of up to 25.20% in the mean absolute error (MAE) for RUL predictions on the whole test dataset, and up to 60.50% in the MAE of the RUL predictions for the minority DM in the test dataset. © 2023 ICROS.

关键词： Machine learning

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Detection of Novel Asset Failures in Predictive Maintenance Using Classifier Certainty 32

Detection of Novel Asset Failures in Predictive Maintenance ...

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32nd Mediterranean Conference on Control and automation, MED 2024

作者： Fathi, Kiavash Ristin, Marko Sadurski, Marcin Kleinert, Tobias Van De Venn, Hans Wernher RWTH Aachen University Information and Automation Systems for Process and Material Technology Aachen52064 Germany Institute of Mechatronic Systems Zurich University of Applied Sciences Winterthur8400 Switzerland

ISBN: (纸本)9798350395440

Model reliability is one of the main building blocks of trustworthy AI where models are capable of indicating their prediction certainty given the provided input data. Despite the numerous model calibration techniques available to gauge the reliability of trained models, it has been shown that even well-calibrated classification models cannot properly represent their uncertainty for data points outside the training distribution. Such models, therefore, cannot be used in industrial settings to find previously unidentified failures in an asset, leaving the maintenance crews in the dark. To counter that, we analyze the sequence of the predicted probability values from a condition monitoring classification sub-model of a predictive maintenance solution. We demonstrate that the data points from unknown regions of the asset parameter space can be flagged by simply analyzing such sequences. The flagged failure instances of the asset are consequently sent for thorough inspection to the maintenance crew. Furthermore, we demonstrate on a practical real-world scenario the effectiveness of our proposed method (mean accuracy of 94.35 %) by comparing it with models trained only on pre-processed data (mean accuracy of 27.96 %) or models based on autoencoder reconstruction error (mean accuracy of 51.09%). We finally show how the predicted probability values from different regions of the parameter space exhibit a higher degree of separability between normal working condition, known and unknown failure modes compared to signal readings of the system or reconstruction errors of an anomaly detection model. © 2024 IEEE.

关键词： Industry 4.0

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Bridging the Gap: A Python-to-Structured Text Compiler with IEC 61131-3 Compliance

Bridging the Gap: A Python-to-Structured Text Compiler with ...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Yuanchen Zhao Alicia Eve Torben Miny Tobias Kleinert Chair of Information and Automation Systems for Process and Material Technology RWTH Aachen University Aachen Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

This paper introduces a high-level language compiler with IEC 61131–3 compliance capable of converting control function code written in Python into structured text. The Python-to-Structured Text Compiler aims to bridge the gap between modern language programming and PLC programming in industrial automation. The proposed Py2ST Compiler workflow includes parsing, transformation, code generation, and code import stages. The implementation of these phases is presented in this paper. And the compilation ability of the Py2ST Compiler is validated by a case study. Utilizing the Py2ST Compiler facilitates the development of PLC control functions within the Python environment. This capability enables the management of both IT and OT functions within a unified environment, enhancing the overall project's maintainability and reducing the development cycle.

关键词： Codes Program processors Programming IEC Standards High level languages Manufacturing automation Python

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Development of a Unified Function Library for Composable and Generatable Skills in process and Manufacturing Control

Development of a Unified Function Library for Composable and...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Shagufta Tobias Kleinert Chair of Information and Automation Systems for Process and Material Technology RWTH Aachen University Aachen Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

关键词： Manufacturing industries Production systems Systematics Design methodology Semantics process control Libraries Real-time systems Standards Manufacturing automation

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Flexible Control Configuration in Modular Plants via Control Function Library

Flexible Control Configuration in Modular Plants via Control...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Yuanchen Zhao Shagufta Tobias Kleinert Chair of Information and Automation Systems for Process and Material Technology RWTH Aachen University Aachen Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

关键词： Costs Scalability process control Production Control systems Libraries Chemicals Manufacturing automation

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Semantic models in process monitoring: Semantic models for field device performance monitoring in the process industry in the context of industry 4.0

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VDI Berichte 2023年第2419期2023卷 233-244页

作者： Hana, Ramy Kleinert, Tobias Chair of Information and Automation Systems for Process and Material Technology RWTH Aachen University Aachen Germany

The introduction of numerous semantic models (e.g. Asset administration shells (AAS) and automationML (AML) models) has facilitated the description of different aspects of production in the process industry. Semantic models provide a flexible structure for encapsulating annotated information. The models are integrated with standardized data exchange formats (e.g. XML) which enables a wide range of automated functions. One of these functions would be field device performance assessment where the different semantic models can help in creating an assessment ecosystem for the continuous monitoring of field devices. © 2023 The Authors.

关键词： Flexible structures

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