Large Language Models (LLMs) have shown promising capabilities in supporting and automating a variety of clearly defined, structured tasks. The engineering of modular plants also follows standardized workflow structures and uses standardized artifacts such as P&IDs, flow diagrams or HAZOPs. Therefore, the engineering of modular plants has the potential to be significantly supported or automated by AI tools. The articles objective is to determine which aspects of the modular plant engineering workflow could be supported or automated by LLMs. This is done by reviewing the current state of the art and combining the modular plant engineering workflow which LLM-based capabilities for engineering support. This leads to two results. First, a mapping of current LLM capabilities to the steps within the modular plant engineering workflow. Second, a theoretical assessment of the general LLM capabilities in terms of their usefulness for the tasks within the modular plant engineering workflow. All in all, the proposed mapping of LLMs to the modular plant engineering workflow provides an overview of the ways in which LLMs can support engineers. In addition, the LLM capability assessment provides insights into the current state of the LLMs abilities and highlights where further research and development is needed.

This work-in-progress paper proposes an approach to quantify process information in the context of sensor selection in chemical plants. The method is based on approximating the global state uncertainty via Monte Carlo simulation. In contrast to most existing approaches for sensor selection, this promises insusceptibility against dependent non-Gaussian uncertainties in steady-state or dynamic processes with the possibility to integrate data-driven models into the set of state equations. First results demonstrate that the approach can find the Pareto optimal sensor configuration for an in-silico continuous stirred tank reactor (CSTR). Additionally, the method's further development for applications in real-world scenarios is discussed.

Modular process plants, built from Process Equipment Assembly (PEA), promise a higher flexibility compared to monolithic plants. Digital documentation is a key requirement for a seamless orchestration of a modular plant using PEAs from different vendors. From a process engineering functional view the Module Type Package (MTP) documents the capabilities realized by a PEA. From a automation perspective the documentation and specification can be optimized by utilizing a standard called System Control Diagrams (SCDs). There is up to now no connection of the individual standards. This connection could enable an integrated engineering approach to raise consistency and reduce engineering effort. This work presents an approach to map SCD based automation planning to the MTP. Therefore, both standards are introduced and a mapping from SCD to MTP is realized. It is shown, that most of the functions from SCD have a representation in the MTP, enabling the linking of basic automation functions to capabilities. This enables engineers which are using SCD as a planning tool to efficiently provide an MTP for PEAs or modular plants.

The increasing need for simulation-based analysis along the life-cycle of modern process plants introduces new requirements and limitations in the development of simulation models. In the context of modular plants, according to VDI 2776, the distributed knowledge arises as a challenge in enabling system simulations. Co-simulation can enable a provider-independent simulation of chemical processes, but the co-simulation interfaces need further standardization to be efficiently integrated in the modular plant life-cycle. This paper works toward the usability of process models for co-simulation to support standardization efforts and make simulation models more usable and re-usable. To increase the usability of co-simulation in the process industry by working towards a common standard, two co-simulation standards, namely the Functional Mock-Up Interface and the CAPE-OPEN standard, are semantically linked. A use-case for a co-simulation-based operability analysis of a heterogeneous electrolysis plant is presented and necessary model requirements and interfaces are defined. Criteria to assess the compatibility of the model interfaces as a first step of a usability analysis are collected and presented. With the available requirements and interface specifications Functional Mock-Up Units can be created and the shown use-case can be carried out. Challenges regarding the potential integration of varying thermophysical properties have been pointed out and methods to overcome these challenges in the context of usability have been outlined.

Waste and recycling material sorting is crucial for reducing environmental impact and promoting resource recovery. However, its complexity poses significant challenges, necessitating the development of effective sorting processes. Manual operation of these plants can be less efficient than automated systems. The first step toward automation is utilizing a Digital Twin, which combines fundamental principles and data-driven insights into the waste sorting process. To achieve this, the equipment involved in waste sorting plants can be analyzed in detail, focusing on operational settings and their impact on overall efficiency. Initially, a steady-state model of the plant is developed, followed by the implementation of advanced strategies like model predictive control. The model can be rigorously tested and refined using a case study on German post-consumer waste. The architecture of the Digital Twin, comprising various building blocks such as the modeling and simulation block, is being developed to transition away from manual operations. This Digital Twin aims to enhance sorting efficiency through offline and online optimization of operational set points, leading to a more sustainable and resource-efficient future. Through simulations and real-time data integration, a Digital Twin for the waste and recycling material process can aid with process design, fine-tuning, and plant automation.

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.

In this paper we compare different operation strategies for alkaline electrolyzis (AEL) systems using numeric simulation. We derived general models for mass and energy balances from literature and composed them into a model for an AEL system. Here we considered a numbered-up plant topology, containing multiple AEL stacks with single electrolyte distribution and gas separation systems. The gas impurities and achievable minimal load distribution were compared for the different operating strategies. The results were discussed and further conclusions for the operation of a homogeneous numbered-up AEL system were derived.

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.

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.

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.

The scale up of hydrogen production to large scale production systems demands a structured approach to control these systems. With suitable control principles, optimization for operation can be achieved whilst maintaining flexibility. In this paper, existing control strategies are analyzed and compared for large scale electrolysis systems. It is argued, how modularization can enable the optimal distribution of set-points and enables the systems for capacity extension. An initial implementation in MATLAB is presented, showing the feasibility of the proposed power distribution concept.

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 module.OBJECTIVE: Simplifying the deployment and reconfiguration of compute-intensive applications for modular plants.METHODS: Reviewing the current state of the art and combining the modular plant concept with a cloud-based Control-as-a-Service (CaaS) approach.RESULTS: 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 FX.CONCLUSION: 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.

Digital twin is a valuable tool for the active training of engineers at both academic and professional levels. This is even more important if learners can experience any safe or unsafe scenarios on the safe environment of an accurate simulator combined with the systematic collaborative applications. This paper introduces a learning platform that is designed in compliance with ISO 10015 to be used following the individual initiatives or organizational competency management programs. The curriculum addresses the needs and expectations of Industry 4.0 engineers who should master not only the specialized subjects relevant to their discipline but also have a good grasp on system thinking, system engineering and complexity management skills. This active learning platform is called ADEPP Skill 4.0 and provides collaborative learning workspaces on a web-based operator training simulator (OTS) which interoperate with the SharePoint application.

Modularization and the Module Type Package (MTP) technology are proven concepts to ensure flexible plants and shorter time-to-market. Since the concepts are generic, they can potentially be applied to other domains. While the MTP approach has so far been used mainly in the specialty chemicals and pharmaceuticals industries, other sectors such as shipbuilding, logistics and hydrogen production show potential for adoption of this approach. In this article, such domains will be briefly examined, and the characteristics of the specific application are assigned to the requirements from modularization. The resulting analysis is transferred to the electrolyzer domain in hydrogen production in order to explain how the MTP technology can be applied there and how the hydrogen industry can benefit from the MTP approach. Furthermore, it motivates to transfer this approach to other industrial sectors that might not be considered in this contribution.

Modular Automation offers promising technologies for the process and chemical industry. It meets the requirements for greater flexibility and a shorter development cycle for production facilities by dividing the process into smaller standardized units. Key element of Modular Automation is the Module Type Package (MTP). It represents a standardized and manufacturer-independent description of the automation interface for self-contained production units, or Process Equipment Assemblies (PEA), and endows the plug-and-produce capability of PEAs. Software solutions to program MTP compatible PEAs are mostly provided by the Programmable Logic Controller (PLC) manufacturers. They are proprietary and bound to certain hardware and even programming languages. Therefore, their suitability for implementation of soft sensors based on data-driven advanced analytics is strongly limited. In this article we present an opensource Python package, MTPPy, designed for rapid prototyping of MTP-capable soft sensors with a focus on AI-based research applications. MTPPy is aimed at the accelerated deployment of soft sensors in the modular plants; thus, closing the gap between the data-driven model development and integration into the production.

Information plays a significant role in modern process industries due to the demand for flexibility and mobility in production. Therefore, it is important to preserve the privacy and security of the information exchanged and shared between partners in value chains, for instance asset chains or supply chains. Since many companies have their own technological solutions and methods for operation and control, this information is regarded as their intellectual property. For the protection of recipes, material flows, or operational and control variables during the manufacturing of products, various methods are available. These techniques include anonymization and encryption solutions. To deal with mathematical models and the computation of formulas, homomorphic encryption schemes can be applied to the data which have to be shared within a value chain. Based on the experience of previous implementations of homomorphic crypto system in different domains, the opportunities for adaptation of encryption methods in process industries are considered. This paper proposes the application of homomorphic encryption in a value chain and defines a specific protocol that enables the Paillier cryptosystem on a time series. A use case is designed for confidential information exchange between a secret owner and a value provider in a value chain. The architecture of confidentiality-preserving information sharing satisfies the zero-knowledge proof requirement and shows low similarity between original and recovered messages.

Hazard & Operability (HAZOP) studies are a common expert-driven brainstorming methodology to analyze the safety of systems. In this paper, we propose an approach to integrate the content of HAZOP studies of (apparatus and process) by extracting and disclosing the causal structures implied in the HAZOPs. Thus, a methodology for data compression and integration of several HAZOP studies is supposed, resulting in a comprehensible summary of the underlying causal relationships withing the current system set-up. The resulting diagrams constitute a summary of the essential HAZOP studies by disclosing and visualizing the internal causal structures and are hence designed to facilitate interpretations and deductions performed by human operators and support machine-readability. The application of the methodology is implemented in the import of HAZOP-tables to Resource Description Framework (RDF). Using this formalized structure, the export to their original format as table is supported as well, so that the transformation can be conducted without the loss of information in both directions.

Discrete manufacturing and process industries move towards flexible production to cope with individualization. Safety systems often counteract these developments. In this paper, a generalized methodology to draft an overall safety concept using different technologies is presented. Motivated by use-cases from both domains, requirements for future safety systems are described and summarized in a structured way. These requirements are then generalized and classified in building blocks to fulfill the needs of flexible functional safety. A methodology to structure safety systems and their general parts is presented. The used building blocks refer to aspects as interfaces, communication, and certification. Within the building blocks different technologies can be applied, to fulfill the part of the safety system accordingly.

Organisation and control of heterogeneous cyber-physical systems are complex tasks, that require robust decision making heuristics based on specific knowledge about the physical environment as well as regarding the capabilities of the system's actuators. Hence, fundamentally different concepts exist. Designs based on a centralised hierarchy on the one hand and completely edge-computing based autonomous systems on the other are well investigated and documented but offer specific disadvantages concerning adaptiveness, control and scalability. This article presents a hybrid approach by suggesting an application-aware optimised compromise. Existing approaches as well as requirements and resulting challenges are outlined. Based on that, an extended middleware is introduced, that does not only act as an abstract communication platform but also organises the cyber-physical system by providing a centralised high-level controller component that issues recommendations that are created based on a global view on the domain-specific conditions. Its architecture makes this component completely independent of the lower system levels. Hence, it can flexibly be integrated into different topologies and ported to various use cases. Although the presented approach does not restrict any task allocation strategy, it is shown that decentralised task distribution provides advantages and can easily be implemented based on our recommendations. A simulation-based evaluation demonstrates that this abstract control strategy is able to support performant and effective behaviour of the cyber-physical system.

Plug&Operate shall enable process industry to adapt more quickly to varying production situations. While the definition of process equipment assemblies as units with specific capabilities and uniform automation interface is already under standardization, the process control layer is gaining importance as it realizes a variety of tasks required for plant operation. This paper presents an overview of requirements on the research process control layer Polaris collected from an initial implementation and literature. The results of these findings are used for an assessment of suitable architectures from which the presented concept emerges. Special focus is on microFrontends, as these are considered a suitable solution to support task specific frontends during plant engineering and operation with simultaneous high flexibility due to modular design and loose coupling.

In the process industry, ongoing digitization is leading to a considerable information exchange over the entire life cycle of a process plant. Data models are usually created in the initial planning phases and these change continuously with further progress including the planning phase itself, plant adaptations after commissioning, and maintenance. The various models from the disciplines involved have a considerable semantic overlap, creating dependencies. Changes in one model inevitably lead to changes in another. This paper presents an approach for networking and synchronization between data models based on these overlaps. The resulting synchronization network provides models which are as free of inconsistencies as possible across different disciplines at any point in time. In addition, first approaches for collaborative conflict resolution are presented. Approaches from model-driven software development and web technologies are adapted to the application domain of the process industry. Typical information models created during the planning phase of a process engineering plant serve as an example.

With the advent of the fourth industrial revolution i.e. Industry 4.0, plants and factories are becoming smarter and interconnected. The transitions demand vertical integration and seamless connectivity. For this purpose, there is a need for semantic communication between various devices including the heavily resource-constrained field devices. To address this, a real-time capable hardware-based implementation of a well-established semantic communication protocol, i.e. OPC Unified Architecture was designed and developed. This chip-based implementation is power-efficient and compact, making it suitable for the field level. The chip was analyzed and incorporated in a demonstrator as a proof of concept of its integration at field level in a plant module of the process industry. Various opportunities are also examined where the chip could be utilized to deliver benefits to existing and future technologies.

Industrial plants suffer from a high degree of complexity and incompatibility in their communication infrastructure, caused by a wild mix of proprietary technologies. This prevents transformation toward Industry 4.0 and the Industrial Internet of Things. Open platform communications unified architecture (OPC UA) is a standardized protocol that addresses these problems with uniform and semantic communication across all levels of the hierarchy. However, its adoption in embedded field devices, such as sensors and actuators, is still lacking due to prohibitive memory and power requirements of software implementations. We have developed a dedicated hardware engine that offloads processing of the OPC UA protocol and enables the realization of compact and low-power field devices with OPC UA support. As part of a proof-of-concept embedded system, we have implemented this engine in a 22-nm FDSOI technology, representing the first ASIC implementation of an OPC UA server. We measured performance, power consumption, and memory footprint of our test chip and compared it with a software implementation based on open62541 and a Raspberry Pi 2B. Our OPC UA hardware engine is 50 times more energy efficient and only requires 36 KiB of memory. The complete system consumes only 24 mW under full load, making it suitable for low-power embedded applications.

With the rising amount of networked devices in industrial, edge, fog and IoT applications, gathering, managing and presenting data from a multitude of distributed sources is an increasingly vital task. Computing systems that locate and centralize data from a subordinate network domain - complex gateways and aggregating servers - are frequently employed and described in this capacity. However, when such "aggregating systems" are encountered in research or industrial applications, one quickly realizes that functions and capabilities vary tremendously. The term appears to encompass anything from simple fieldbus gateways to intelligent information processing nodes for harmonizing information models. This article presents a classification scheme for aggregating systems, that is systems with the ability to integrate information from other, distributed devices into their own datastore. A particular focus lies on intelligent systems supporting OPC UA, a standard that is rapidly establishing itself as a key protocol for semantic communications. This article first introduces a general architecture model for aggregating systems and proceeds to detail functionality and cross-cutting concerns that effect these systems. Finally, the applicability of these models is tested on two case studies.

The introduction of AI methods in production or production-related environments meets with resistance from operators due to their lack of relevant experience and their responsibility for plant safety. To overcome these inhibitions one requires prototypical implementations, which offer considerable benefits, meet the highest requirements for reliability, are accepted by the operating personnel, and get support from those in charge. As a result, AI technologies must be embedded into the complex IT/OT infrastructure of the companies. Traceability, maintainability and longevity must also be guaranteed. As a first step towards this, we present a concept of the demonstrator and its first results, which should make AI comprehensible by visualizing challenges and exploring possibilities in the process industry.

Modular process plants enable the process industry to adapt to volatile and fluctuating markets. The preferred process technology concept for these market scenarios is realized through combining pre-engineered process equipment assemblies (PEA) from different manufacturers with standardized interfaces. While the flexibility gain for this type of plants is high, the design of the safety systems of these modular plants in terms of exchangeability and compatibility is challenging. One solution could be the development of a safety-interface for PEAs to create flexible and scalable safety systems. The principles of modular basic process control are analyzed and requirements with respect to safety design are discussed. The authors provide a differentiation of the intramodular safety concept of a single PEA from the intermodular safety concept of a complete modular plant. A concept for safe and modular interaction of PEAs in a modular plant is developed and additionally validated on a basic demonstrator. Finally, from these findings, standardization requirements are provided and aspects for further research are pointed out.

This paper considers an implementation of the predictive maintenance for rotating equipment in a chemical process plant by means of the NAMUR Open Architecture (NOA). Various methods and challenges for monitoring of rotating equipment are described and compared. An approach based on the motor current measurement for the use case at a BASF plant was selected due to construction limitations. The focus is on connectivity aspects as well as details of implementation of the NOA concept. Use of the NOA concept made it possible to deploy the developed monitoring system into a real plant within one day during a planned maintenance window without any permanent alterations to the existing plant. The monitoring system works in parallel and affects neither the process nor the process control directly. Discussion of the first data gathered by the installed monitoring system showed that additional context information about the process are of great importance for the comprehensive analysis. At the end of the paper, improvements with regards to the connectivity and integration of additional sensors as well as further activities such as coupling of context information about the process and development of a decision making system are discussed.

Dynamic-state estimation plays a critical role in achieving real-time wide-area monitoring of power systems. On the other hand, false data injection (FDI) attacks are substantial threats, which can undesirably ruin the state estimation results. To tackle this problem, an effective secure hybrid dynamic-state estimation approach that involves a dynamic model of the attack vector is proposed in this article. In the proposed method, an initial estimation of the system states is first obtained using a designed unknown input observer (UIO). Subsequently, based on the system, UIO models, and the initial estimations of the states, a dynamic model for the attack vector is extracted. Ultimately, the attack model is augmented with the main system model for coestimation of the attack and the system states using a Kalman filter. The onset of the FDI attack is rapidly detected by the accurate estimation of the attack vector. The effectiveness of the proposed approach is demonstrated under different FDI attack scenarios by a thorough theoretical analysis as well as simulations on IEEE 14-bus and 57-bus test systems. In order to show that the proposed method can keep up with typical scan rates of commercial phasor measurement units, a series of software-in-the-loop experiments are also conducted and the real-time feasibility of the proposed approach is guaranteed.

The fast semantics project examines the use of the OPC Unified Architecture (OPC UA) in embedded industrial systems and proposes the design of a customizable, hard real time capable OPC UA Intellectual Property Core (IP Core) for single chip computing plattforms. This allows using OPC UA in both novel energy efficient sensor applications and in state of the art field devices. These single chip OPC UA servers form the semantic data sources for future applications such as cloud based added value services or machine learning applications. This article presents the design alternatives and first synthesis results for the implementation of OPC UA servers in embedded systems.

In recent years, the automation industry is moving towards Industry 4.0 and cyber-physical systems. There is an increasing demand for smarter plants and plant modules. In this paper, we are proposing an architecture for the open cognitive control system. This will provide the benefits of a control strategy based on the data analysis. With the possibility to connect with the cloud, this will enable easy updates and exchange of task modules that would ensure the system to keep up with the technological advancements. This will also improve the accuracy and lifetime of the automation system. To meet the requirements of flexibility, speed and reliability of the system, the architecture has been based on distributed and concurrent systems design. A detailed description of the architecture along with its challenges have been presented in this paper. A comparison of different implementation techniques for certain blocks has also been discussed.

In complex production systems, the diagnosis and correction of faults requires operators to possess a deep understanding of the specific processes and machines as well as general knowledge about the interactions between different system components. However, in actual work environments operator qualification and experience is quite diverse, which leads to an immense variability in the time required for fault diagnosis and in the quality of corrective actions. Both time and quality of fault diagnosis and correction are vital parameters in the functioning of a plant, because downtimes have severe economic consequences and thus should be kept to a minimum. With the introduction of highly complex and flexible cyber-physical production systems, these problems are aggravated as fault sources vary and diagnosis becomes even more challenging. The paper presents a concept for a self-learning assistance system that supports operators in finding and evaluating solution strategies for complex faults. This concept applies a question-answer approach which allows for an incremental, dialogue-based establishment of common ground between operators and the assistance system.

Modularization of process plants is seen as one approach to face the increasing flexibility requirements in the process industry. Therefore, modules are combined to a modular process plant to achieve a higher flexibility of the production. Conventional distributed control systems do not support flexible production systems adequately. Hence, modules should encapsulate process functions as services. The services should be invoked and controlled by state-based control. This contribution presents an approach for the state-based control of services, following a defined state-model. The approach has been tested in two case studies and two different implementations: In a simulation environment based on Matlab Simulink Stateflow, and in an industrial implementation of a pump and a controller. This contribution provides an overview of the developed concepts and their capability for the use in industrial environments.

In this study, a new two-stage learning based reduction approach for fuzzy cognitive maps (FCM) is introduced in order to reduce the number of concepts. FCM is a graphical modeling technique that follows a reasoning approach similar to the human reasoning and the decision-making process. The FCM model incorporates the available knowledge and expertise in the form of concepts and in the direction and strength of the interactions among concepts. One of the modeling problems of FCMs is that oversized FCM models suffer from interpretability problems. An oversized FCM may contain concepts that are semantically similar and affect the other concepts in a similar way. This new study introduces a two-stage model reduction approach, and both static and dynamic analyses are considered without losing essential information. In the first stage, the number of concepts is reduced by merging similar concepts into clusters, whereas in the second stage the transformation function parameters of concepts are optimized. In order to show the benefit of using the proposed reduction approach, two sets of studies are conducted. First, a huge set of synthetic FCMs are generated, and the results of these statistical analyses are presented via various tables and figures. Subsequently, suggestions to the decision makers are given. Second, experimental studies are also presented to show the decision parameters and procedure for the proposed approach. The results show that after using the concept reduction approach presented in this study, the interpretability of FCM increases with an acceptable amount of information loss in the output concepts.

Actual trends, such as highly volatile markets and shorter product lifecycles, in the process industries require new approaches for the control of process plants. These changes are tackled by the approach of modular process plants. Modular process plants promise a shorter time-to-market and a high flexibility regarding the products produced herein. To achieve these advantages, beside the mechanical modularization also the control systems of such plants need to change. Current process control systems are not able to fulfill all requirements of modularization. Therefore, known approaches from information technology are adapted for the automation of modular process plants. Beside service-oriented architectures, the Microservice approach is of current interest in the information technology domain. This approach is presented in this contribution, and the suitability of Microservices as an architecture for modular process automation is analyzed. Furthermore, a Microservice-based approach for the control of modular process plants is presented.

OPC UA is one of the most prominent candidates for a middleware in future CPS scenarios. It provides many concepts which makes it very useful to address challenges in the area of flexibility, security and availability. It offers a semantic rich information space with extensible OPC UA information models. They make it possible to develop smart client application with a high degree of flexibility. This paper summarizes experiences made with the use of OPC UA information models. Thus, it presents various projects in which we used OPC UA as base technologies. Then, we describe how information models supported the development. On the other hand, we provide a list of issues which we experienced regarding this information models. There is some potential to improve OPC UA in the area of revision management and distributed applications.

Modular process plants are small or medium scale plants which consist of separately engineered and automated modules. To speed up the start of production, a modular process plant is composed from several of such modules. Nowadays, safety engineering refers to the whole process plant, is very individual, time consuming, and hardly integrated. For safe modular process plants, the safety engineering has to be performed and implemented on module level to keep the engineering processes of the modules and the modular process plant independent. The safety engineering has to be more integrated to keep the advantage of modular process plants. This paper presents the challenges of such a modular safety engineering and our approach to cope with them. We use a case study of an exemplary modular process plant to show the results of a modular HAZOP study with limited information and how to combine the modular HAZOP studies to fill the gaps.

During the life cycle of an industrial processing plant, a variety of domain specific data models are generated. All these models will be changed independently by a group of engineers over time. Maintaining the consistency of these models involves a time consuming and costly manual process. Here we introduce an interactive roundtrip engineering system for processing industry environments. The system use a complementary rule-based transformation language to provide generation and synchronisation processes. For this, an interactive concept is presented with a knowledge-based system and user interaction. The goal is to have a consistent digital twin of the plant through the whole life cycle in a highly automated manner. This leads to a traceable transformation process which ensures more parallel design phases and an efficient maintenance or reconstruction of the digital plant twin.

Most Cyber Physical Production Systems (CPPS) research is devoted to the manufacturing industry, but the need for flexibility is an increasing trend in the process industry, too. Today's process automation systems (PAS) are not well-suited for quick adaptation of the plant, i.e. the addition, removal or change of physical components, such as filters, mixers, or reaction units. The authors have developed a model-based approach, which allows reconfiguring the PAS based on a model, which acts as a representative of the physical component. Thus, the model and the physical component together form a CPPS. In the paper, the requirements, the model structure, and the model content will be described, and a practical example will be presented.

During the planning phases of a chemical plant, a great number of domain-specific data models are created, all of which influence one another. Marking these models consistent with each other in process industry environments usually still involves a large amount of manual work. This article proposes an approach to reach data consistency over the whole plant life cycle automatically, with a prospect of interoperability across engineering environments. This is achieved by adapting the well-known roundtrip engineering concepts from software development to process industry models and use cases. In this way it will be possible to create and synchronise models from heterogeneous areas.

Within the Semantic Web field, Linked Data is an emerging technology offering advantages in terms of flexibility and openness also for industrial environments. It provides a powerful information model with simple extension mechanisms and a cross-domain character, which makes it possible to span flexible information spaces across enterprise boundaries. Thus, it is able to represent all facets of a digital plant, like devices and processes. Although developed with the focus on static data, it is also capable of handling dynamic data if the latter is adapted appropriately. This article describes these requirements and presents a concept for integrating process data into the Linked Data information space. A separation between a semantic description of the access to process data and the service providing exactly this information allows efficient and integration-ready access to data. The necessary vocabulary is described as well as the information model. A prototypical implementation of OPC UA integration into Linked Data is presented. The article further discusses the current status of the approach and provides future research challenges.

Modularization is considered as one enabler for flexible and highly reconfigurable process plants. These characteristics are needed to overcome deficiencies regarding market volatility and shorter product innovation cycles. Current standardization activities aim at the specification of Module Type Package (MTP) files as a semantic description of modules for fast and efficient integration into process control systems. To increase the plug and produce character of the approach, online discovery for modules has to be enabled. OPC UA is considered as a suitable industrial communication technology for the communication between modules and process control systems. Therefore, this paper presents an approach for the representation of MTPs in OPC UA in order to enable the online discovery of process modules.

The design of conventional process plants is guided by the idea of structuring the process in functional units. Because of cost reduction this design is often neglected during the implementation phase. There is a huge potential in the re-modularization looking at the re-usability which directly effects the engineering efficiency when developing new plants. Furthermore, there is the possibility to create modularized KPIs. Those can be aggregated to plant-wide KPIs to evaluate the overall plant performance and status. In this paper the authors are presenting a concept for the detection of virtual modules in existing plant topologies. The plant topology is therefore transformed into a searchable graph. With the help of extended search algorithms and the definition of functional patterns it is now possible to identify all possible virtual module within a plant topology. Through a prototypical implementation, visualizing the identified modules in the graph, a proof of concept is shown.

Engineering projects are driven by cost and time constraints. Furthermore, the increasing complexity of these projects makes it necessary to expose specification, implementation and conceptual errors as early as possible. Therefore, a well-established method is to carry out simulation experiments. This paper presents a concept for coupling already existing (domain-specific) simulation models that allow the integration of individual models in a co-simulation environment. A complete system simulation can take place in this environment. Therefore, the contribution of OPC UA as a generic middleware technology - a candidate for Industrie 4.0 scenarios that is being intensively discussed - is analysed. Through a prototypical implementation based on open62541, we can show a proof of concept by coupling different simulations (SIMIT and FMI instances). It also shows that our concept can be easily extended regarding the integration of new simulators.

The implementation of software based OPC UA servers on computing platforms in actuators and sensors of the field layer remains a challenge due to the protocols high memory and bandwidth prerequisites. This paper discusses encoding aspects of OPC UA binary data representations for devices with limited random access memory and low fieldbus throughput, especially focusing on single-chip microcomputing platforms. Efficient and machine-friendly binary representations of OPC UA data models are derived by examining the structure of OPC UA data and optimizing their representation in regard to 8 bit serial, non-volatile memory components. Transport compression mechanisms, aiming to reduce bandwidth requirements in crowded or low bandwidth networks, are also introduced. While the memory usage of information models could be significantly reduced to (116 kB for Namespace 0), it was shown transport compression cannot yield bandwidth improvements unless data is compressed as a service.

OPCUA is a promising candidate for achieving a vertical semantic integration of field devices in the next generation of industrial automation topologies. Microprocessing platforms embedded in sensors and actor do however not provide the memory and computing resources required to integrate OPC UA communication stacks. To enable the usage of OPC UA on limited platforms, this article introduces a dedicated, highly scalable hardware server stack, synthesizable on 75.800 μm2using 28 nm CMOS technology as well as FPGAs, that can process OPC UA as a peripheral component.

The reduction of the effort required for integration of a module into a production plant is the fundamental aim of modular plant architectures. Effective module integration can be achieved, for instance, by shifting engineering efforts from the classical site-engineering to the engineering of plant modules. The basis of this approach is the formal description of various aspects of a module in a module type package (MTP). The core elements of this MTP are presented in this paper and discussed in terms of use in a standard module description. In addition, this paper presents a transformation of this concept to the standardized format AutomationML.

Modern process plants are becoming more and more complex with high demands placed on design, engineering and operation. Throughout the life-cycle of process plants there is always the typical conflict involving costs, time and quality. One way of resolving this conflict is to employ simulation technology as it can be used to answer questions relating to engineering and operation earlier and with lower risks. In 2014, the authors conducted a global online survey investigating the current and future role of simulation within the life-cycle of a process plant. Based on the responses of more than 200 participants, fields of action and requirements have been drawn up to help reach the goal of continuously using simulation in the future. A first prototypical implementation towards concurrently using simulation within the life-cycle of a process plant is presented in this paper. This prototype uses tools for simulation, plant design and process automation that are available today and focuses on the engineering and operational phase of the life-cycle.

As a standardized communication protocol, OPC UA is the main focal point with regard to information exchange in the ongoing initiative Industrie 4.0. But there are also considerations to use it within the Internet of Things. The fact that currently no open reference implementation can be used in research for free represents a major problem in this context. The authors have the opinion that open source software can stabilize the ongoing theoretical work. Recent efforts to develop an open implementation for OPC UA were not able to meet the requirements of practical and industrial automation technology. This issue is addressed by the open62541 project which is presented in this article including an overview of its application fields and main research issues.

As Smart Manufacturing, Industrial Internet, Industrie 4.0, and Cyber-Physical Production System (CPPS) are becoming reality, the way process and manufacturing plants are operated has to change. Additionally, these developments - constituting the pervasive digitalisation of industry - have a profound effect on the way human workers and machines interact. This paper contrasts the current state of the art in plant control with a vision for the future. The scenario is illustrated by a realistic problem-solving process in a chemical plant. It describes an integrated industrial information and interaction space that leverages emerging technologies to enable plant operators to remain in control of future flexible modularised process plants. Our approach shows the advantages of an integrated information space which feeds interaction and collaboration using Virtual Reality (VR), novel display technologies and mobile devices.

This paper presents a study on the potential of today's smartwatches as a complementary user interface to mobile support systems for industrial maintenance tasks. Starting from challenges, usage scenarios and use cases for the valuable use of smartwatches in an industrial context, the various possibilities of information delivery, task support and process control using smartwatches are evaluated and checked against basic ergonomic requirements on data pre-processing, user interface design and the hardware equipment. A prototypical implementation of a support system for industrial maintenance tasks illustrates the applicability of the derived interaction concepts and design guidelines for smartwatch-equipped mobile support systems.

In this paper, learning of the FCMs represented using triangular fuzzy numbers (TFNs) in their weight matrices is studied. For this aim a population based novel learning approach is proposed. In the proposed algorithm, BB-BC optimization method is preferred because of its fast convergence capability. Moreover, this proposed approach involves concept by concept (CbC) learning to increase the accuracy of the learning of FCMs. Two different tests are realized as case studies for investigating the performance of the learning approach. For the first test, the learning capability of the algorithm is examined and for the second test the performance of generalization capability is investigated. The tests, which are presented via tables and figures, show that learning approach is successful for learning of FCMs with TFNs. Furthermore, from the case study it can be seen that the uncertain information can be represented and interpreted by the proposed FCM design methodology in a more efficient way.

Modern process plants are becoming more and more complex with high demands placed on design, engineering and operation. Throughout the life cycle of process plants, there is always the typical conflict involving costs, time and quality. One way of resolving this conflict is to employ simulation technology as it can be used to answer questions relating to engineering and operation earlier and with lower risks. To investigate the current and future role of simulation over the life cycle of a process plant, the authors conducted a global survey from July to October 2014. More than 200 persons participated in the survey. The results of the survey are described in this paper, and an initial technological roadmap derived showing a possible course for the future and creating a basis for discussion. The roadmap in this paper is based on action fields that need to be developed to enable a concurrent use of simulation over the complete life cycle of a process plant.

The integration of package units in a SCADA or DCS involves considerable manual effort. Various aspects of automation such as faceplates, states of sequences or interlocks have to be reproduced for the visualization and management of the package unit in the master control system. The integration effort can be reduced using existing technologies, which could also be extended to a modular plug-and-produce methodology. An essential precondition for this is a uniform formal quantitative description of various aspects of the package unit and tool chains based on the formal descriptions. This paper will present an approach using the description language EDDL, which is established in the field of field device integration.

Today simulation is playing an important role at multiple steps within the life-cycle of a process plant. For the future it is expected that simulation will be integrated in the plant life-cycle and the backbone of an integrated engineering process. To simulate the different aspects of a plant multiple domains are necessary. Usually each domain requires specific simulation capabilities, thus multiple specialized tools are used along the life-cycle. Reusing simulation models throughout the life-cycle would be very beneficial. This paper investigates existing approaches for model reuse and co-simulation and motivates the creation of a standard for co-simulation from a process industry perspective.

This paper presents a study of the potential of integrated services for app-based system diagnosis using mobile information systems. First, a task and context analysis is provided for the application of integrated system diagnosis in the context of plant asset management (PAM). Second, exemplary scenarios are presented which demonstrate IT services for system analysis based on self-organizing maps, system diagnosis with a graph-based approach and support for therapeutic measures on defective assets. Third, a mobile information system is presented that allows users to list, describe, filter, and select assets, to browse through available diagnoses, and to follow step-by-step instructions for recommended therapeutic measures. The mobile information system provides a graphical representation, description, and selection of assets by using a P&I diagram as well as a chart visualization of process values. The system further provides access to both static and transient data sources such as engineering data of the plant, process data of the technical process and the results of complex analysis services. This mobile information system demonstrates the suitability of the proposed app-based approach. Finally, the results of a focus group workshop are summarized, showing the potential of mobile information systems in an industrial setting, barriers that still remain.

In this paper, the conventional Fuzzy Cognitive Maps (FCMs), which has already achieved success in many fields, are extended by using triangular fuzzy numbers (TFNs). The advantage of FCMs is that they are relatively easy to construct and parameterize and are capable of handling the full range of system feedback structure, including density-dependent effects. However, it is a well-known fact that there are some limitations inherent in FCM, such as lack of adequate capability to handle uncertain information and lack of enough ability to aggregate the information from different sources. Triangular fuzzy numbers which are represented by a triplet has the capacity to represent the uncertain relations between the concepts. In this context, the weight matrix representing the causal relations are enhanced to a fuzzy weight matrix that has TFNs as element. As a result of this improvement, the dynamic reasoning algorithm of the conventional FCM is improved for the use of the proposed novel FCM. The proposed FCM is presented via four simulations and the results are discussed. The results of the simulation study shows how easily the uncertain information can be represented and interpreted by the proposed FCM design methodology.

Production plants within manufacturing and process industries are becoming more and more complex systems. For a safe and demand sufficient production the automation system of a production plant is mission critical. Therefore the correct functioning and engineering of the automation system is essential. Nowadays the use of a virtual commissioning step before deploying the automation software on the real production plant is used more often. Within the virtual commissioning the automation software is tested against a virtual plant model, sufficient to check out the correct functioning of the automation system. Usually virtual commissioning is used as a step at the end of the automation engineering, as proposed by VDI 4499. Within this paper an integrated virtual commissioning is proposed, where the automation software is continuously tested against a virtual plant model during the overall engineering phase. The virtual plant is growing together with the automation software and thus enables simulation supported automation engineering. Benefits of the proposed workflow are that errors can be detected immediately after the implementation and the use of the virtual plant model could be extended to various stages of the engineering workflow.

Linked Data offers easy extensibility and interoperability of information spaces. This provides a great potential for industrial companies allowing to share information with partners in a virtual enterprise. Hence, together they can become faster and more flexible which results in an advantage in the market. However, there is still the barrier to protect own information with a fine grain. Access control graphs are an approach for this issue. Information is put into different views by executing infer mechanisms on role-based policy rules. Afterwards queries are automatically rewritten at runtime in order to match the generated views and provide only data from views that should be accessible by the authenticated role. This paper demonstrates the balance between flexibility and security using this approach. The amount and complexity of the policy rules are highly dependent on the information model used. However, a moderate restriction of the huge flexibility in the information modelling allows for few rules but those are powerful ones. Additionally, the approach allows can also be leveraged for consistency checking of Linked Data data structures. Thus, clients can rely on these information invariants and the information provider can rely on the fact that fine grained access is granted.

Nowadays, apps provide support for various simple tasks. They are easy to use and highly usable. However, future apps should support more complex workflows especially when trying to enter the professional business world. They need to provide higher reusability and composability in order to make them suitable for complex and alterable workflows that are common in industry. The concept of App Orchestration allows supporting complex tasks with aid of an ensemble of adapted and managed apps. Therefore, the apps raise several demands on the underlying information backend. This article describes these requirements and presents the Linked Data approach, which is a possible methodology for an integrated, semantically described information space for this purpose. It describes possible uses and benefits for the concept of App Orchestration and shows them in a use case of mobile maintenance. It further discusses the current status of the approach and provides future research challenges.

Package units are used to supply production plants with components and auxiliary materials or to assemble final products. They usually come with an automation system that has predefined functions and behavior. The integration of package units in a SCADA or DCS involves considerable manual effort. Various aspects of automation - such as faceplates, states of sequencers, or interlocks - are reproduced manually in the control system for the visualization and management of the package unit. We present potentials and limitations of current and prospective technologies (for example, FDI technology [4]) for the simplified integration of package units in a process control system. This paper also proposes and discusses a concept for simplified integration of package units in control systems.

The engineering phases of process plants present complex tasks with regard of mass data, interfaces and continuous changes. Many engineering challenges are well supported by CAE tools. But there are no integrated and computer-based support systems for the design of complex fieldbus structures. The approach presented in this paper is a research demonstrator that makes it possible to empirically evaluate mathematical algorithms and automated workflows. It integrates the necessary data for communication planning of different departments, handles the structuring requirements of the planners and automatically generates the bill of materials for the required communication equipments. This paper presents the architecture of the prototype, based on the proposal for the engineering steps presented in NA 114 and shows first applied results.

Nowadays the design of industrial communications networks is based on heuristics which are well known by engineers experienced in this design process. Unexperienced engineers have difficulties to design networks because of their complexitiy. The approach of NetGen:X closes this gap by automating the design using the known heuristics. Additional requirements like the reliability of safety relevant process control functions require a function-oriented consideration of the network. Therefore we provide an approach to automatically evaluate the network using a network graph analysis. The analysis is based on the safety functions and their reliability requirements which are projected in the piping and instrumentation diagram (P&ID) of the computer aided engineering system (CAE system) for process plants. In this article we analyze P&IDs which are conform to the standard EN IEC 62424 and identify additional constraints that need to be considered to enable an automated extraction of the information for the network graph analysis. We show that a slightly extended computer aided engineering eXchange model (CAEX model) is capable to provide all the necessary information.

This paper proposes a concept to extend Field Device Integration (FDI) to address equipment which has no dedicated communication interfaces. An FDI equipment package knows the relevant field devices and algorithms that are necessary for diagnosis, condition monitoring and other plant asset management activities. FDI Equipment packages do not need any specific distributed control system support; given the current FDI draft however an additional software component is necessary which uses the standard interfaces of the FDI server. The proposed concept enables equipment vendors and process specialists to deliver FDI Equipment packages that run in every automation architecture that supports FDI. The run-time concept is complemented by engineering workflows and algorithms that automate the assignment of field devices and parameterization of the FDI equipment packages from formal plant engineering data.

Mobile apps are a success story for mobile devices, particularly in the consumer sector. Tailored to a specific task, they offer optimal usability for a defined class of devices. However, today's apps are neither designed to collaborate with complex workflows nor to support these. To overcome this limitation, we developed the concept of Mobile App Orchestration. This pragmatic model driven software generation approach makes it possible to use mobile apps even in complex industrial workflows. We demonstrate the entire development process in a use case and explain solutions and challenges of our approach. An experimental evaluation of a manually conducted orchestration with 11 participants supports our design hypothesis that the proposed approach can deliver usable mobile support systems for Virtual Factories.

Middleware in automation serves the connection of hardware and software components of applications in automation-like control or human-machine interfaces. To cope with today's flexibility requirements, there is an urgent demand to not only communicate data but to describe the semantics of the distinct elements of the distributed information space. Therefore, middleware in automation needs to provide some means for information modeling. To derive general concepts and recommendations on how to implement information models on middleware in automation, we discuss several relevant standards that provide partial information models. We then identify the fundamental information modeling constructs of these partial models and derive general requirements for the information modeling capabilities of middleware in automation.

The trend towards the integration of application domains and technologies in the field of industrial automation and information technology leads to an increasing complexity of systems and applications. Even though integration has always been one of the major goals of automation, it is still challenging. Both, multi-agent systems and middleware technologies have been successfully used in a number of industrial applications. Each of these technologies have significant advantages in the application domains they are used. The aim of our work is to develop an approach which focuses on the optimal distribution of functionalities between multi-agent systems and middleware. In this paper we discuss the technologies characteristics and identify open questions towards a solution of the function allocation problem.

Mobile information systems (MIS) are finding their way into private and business every-day activities. There are also increased attempts to establish MIS for on-site activities in industrial facilities. Industrial environments, however, place significantly higher demands on mobile user interfaces than office or home environments. Common interaction styles are often unsuitable for this domain. MIS comprising specialized configurations like wearable systems might overcome current limitations. Wearable systems make it possible to arrange system components in the immediate environment of the user's body in order to create an ergonomic and intuitive user interface. However, the use of distributed, body-worn user interfaces, and in particular separation of input and output devices, might increase the workload for the user. This study examines the extent to which the separation of input and output devices affects the workload for wearable MIS. Three interaction styles in two different configurations are investigated with four different measures to determine the workload covering both objective and subjective indicators. This investigation shows that there is no significant increase of workload in general. However, the measurement of the heart rate variability revealed subtle but significant differences between the two configurations, particularly for one interaction style. These findings indicate that physiological measures can provide more detailed and subtle information about additional workload and its source than other measures.

This paper presents a mobile assistance system for service and maintenance personnel in industrial facilities. It provides an innovative interaction metaphor designed to fit domain specific working conditions. As a result of a strictly user-centered design process, the presented system follows the principles of Embodied Interaction. The system is evaluated using a sophisticated scenario in a typical industrial environment. The evaluation also includes a comparison with the conventional paper & pencil-based maintenance workflow. A detailed discussion addresses problems of mobile usability evaluation in industrial environments and provides appropriate solutions. The results presented in this paper demonstrate that the proposed system allows for effective and satisfactory service and maintenance. It contributes further insights for utilization and evaluation of embodied systems in industrial applications. Potential applications of this research include design guidelines for future interface configurations using embodied interactive devices.

In the poster, the European Network for E-learning in Process and Chemical Engineering (EuPaCE.net) is introduced. EuPaCE.net is a special interest group that has been set up by seven European Universities to exploit synergies in the field of e-learning for Process and Chemical Engineering (PaCE) education. The poster includes the results of an international survey about trends and challenges of e-learning in academic PaCE education, which was conducted with students and faculty members at the EuPaCE.net partners. Results show that the use of information and communication technologies in PaCE education is still evolving.