State-based control of process services within modular process plants

Bloch, Henry; Hensel, Stephan; Hoernicke, Mario; Stärk, Katharina D.C.; Menschner, Anna; Fay, Alexander; Urbas, Leon; Knohl, Torsten; Bernshausen, Jens

doi:10.1016/j.procir.2018.03.037

Cited by 21 publications

(7 citation statements)

References 4 publications

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“…To realize a complex process, PEAs are interconnected on a superior automation layer, called Process Orchestration Layer (POL). The sequencing of Services within the POL is referred to as orchestration and enabled by the MTP [10].…”

Section: Fig 1 Infrastructure Of Modular Process Plants Adapted [1]mentioning

confidence: 99%

Safety in modular process plants: demonstration of safety concepts

Pelzer

Klose

Miesner

et al. 2021

Elektrotech. Inftech.

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The modularization of process plants addresses the need for flexible production options in the process industry. In order to maintain the advantages of the adaptability of modular plants, an adaptation of established engineering methods and procedures to their dynamic context of use is required. This paper describes the development and the features of a demonstrator, which makes it possible to investigate aspects of modular plant topology, the design of modular process units, and the functional safety of modules and plants. During the engineering of the modules, modular planning principles are applied and evaluated with respect to the requirements for functional safety and with a strong focus on the modification of safety systems through the exchange of PEAs and FEAs. For the design and modification of the safety systems, a safety life cycle, which meets the requirements of modular automation and takes the provisions of IEC 61508 and IEC 61511 into account, is applied. Practical insights into the construction and the implementation of the distributed Safety Instrumented System as well as the Basic Process Control System are described. In addition to the validation of safety concepts related to the interconnection of Safety Instrumented Functions, the demonstrator is used to study human working environments in modular plants.

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Section: Fig 1 Infrastructure Of Modular Process Plants Adapted [1]mentioning

confidence: 99%

Safety in modular process plants: demonstration of safety concepts

Pelzer

Klose

Miesner

et al. 2021

Elektrotech. Inftech.

Self Cite

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“…Via a module type package (MTP), see NE148 [47], the column can be run versatile in different modular plants for different purposes. The MTP enables an easy implementation of the PEA into a control system, where each PEA as a part of the whole modular plant can be controlled in a manual or automatic way, e.g., via process recipes) [48]. For the usage of this distillation module in a modular plant, it has to be well described, characterized, and made robust against process changes.…”

Section: Distillation Columnmentioning

confidence: 99%

Equipment and Separation Units for Flow Chemistry Applications and Process Development

et al. 2019

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Process development and small‐scale production gets more and more important in fine chemistry and pharmaceutical production. An equipment toolbox assists process synthesis presented in this contribution. A microfluidic calorimeter can measure kinetic and thermodynamic reaction data with commercial plate reactors. A tubular reactor coiled with 90° bends allows for long residence time with low axial dispersion, also known as coiled flow inverter (CFI). A similar setup is used for continuous‐flow cooling crystallization. Small‐scale columns with rotating internals are employed for distillation and liquid‐liquid extraction. Main emphasis will be put on automation and scale‐up in future steps.

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“…In order to make these data also accessable to software located outside of the field‐level, e.g., a cloud application, it is referred to the NAMUR Open Architecture concept (NOA) 62. A special MTP feature is the service‐oriented architecture that provides the possibility to run recipes with the predefined services each PEA offers to the POL 36. This feature could be used to run the process with many different control variables, study the respective effects of control variables and observe states that are usually undesired.…”

Section: Introductionmentioning

confidence: 99%

Flooding Prevention in Distillation and Extraction Columns with Aid of Machine Learning Approaches

Oeing

Neuendorf

Bittorf

et al. 2021

Chemie Ingenieur Technik

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Flooding of separation columns is a severe limitation in the operation of distillation and liquid‐liquid extraction columns. To observe operation conditions, machine learning algorithms are implemented to recognize the flooding behavior of separation columns on laboratory scale. Besides this, the investigated columns already provided the modular automation interface Module Type Package (MTP), which is used for data access of necessary sensor data. Hence, artificial intelligence (AI) tools with deep learning offer high potential for the process industry and allow to capture operating states that are otherwise difficult to detect or model. However, the advanced methods are only hesitantly applied in practice due to complex combination of operational sensing, data analysis, and active control of the equipment. This article provides an overview on how AI‐based algorithms can be implemented in existing laboratory plants. Process sensor data as well as image data are used to model the flooding behavior of distillation and extraction columns for stable and robust operational conditions.

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State-based control of process services within modular process plants

Cited by 21 publications

References 4 publications

Safety in modular process plants: demonstration of safety concepts

Safety in modular process plants: demonstration of safety concepts

Equipment and Separation Units for Flow Chemistry Applications and Process Development

Flooding Prevention in Distillation and Extraction Columns with Aid of Machine Learning Approaches

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