This article proposes a method for the automatic generation of a plant model and monitoring using process mining algorithms based on recorded event logs. The behavioral traces of the system are captured by recording event logs during plant operation in either manual control mode or with an automatic controller. Process discovery algorithms are then applied to extract the logic of the process behavior properties from the recorded event logs. The result is represented as a Petri net, which is used to construct the state machine of the plant model and monitor and is in accordance with the IEC 61499 Standard. The monitor is implemented as a function block and can be deployed in real time to trigger an error signal whenever there is a deviation from the actual process scenario. The plant model and controller are connected in a closed loop and are used for the formal verification of the system with the help of the “fb2smv” converter and symbolic model checking tool NuSMV.

Industrialized insect-based bioconversion is a technologically promising and economical viable approach for solving global crisis of food security and waste management. The successful implementation of such a multi-disciplinary system requires comprehensive expertise and skills from biotechnology, automation, information, and circular economy domains. This is rather difficult for existing practitioners. To simplify their jobs, by leveraging recent advances in industrial informatics, this work proposed and developed a low-code development platform for engineering the automation logic of industrial insect rearing and processing. For feasibility demonstration, a pilot facility has been designed, deployed, and benchmarked in this work. When compared with the conventional pro-code practice, the proposed low-code approach can significantly reduce development costs, shorten delivery times, and improve communication efficiency.

Modernization of currently operational nuclear power plants is becoming increasingly important to maintain their performance and safety. Ensuring the safety of newer Instrumentation and Control (I&C) systems used in modernization efforts requires hazard analysis techniques suitable for the analysis of complex and software-heavy systems. System-Theoretic Process Analysis (STPA) has proven to be a suitable hazard analysis method for these complex I&C systems, however, its practical use is still often limited by its labor-intensive and time-consuming nature, partially due to the limitations of the tools used to perform the analysis: common Office tools such as Microsoft Excel or Visio. Conducting an STPA analysis could be simpler and more attractive with software tools specific to the method. This work introduces the requirements for these software tools and lays the foundation for further work, in which software tools will be evaluated against these requirements.

The pulp and paper industry faces significant en-vironmental challenges, such as air pollution, greenhouse gas emissions, and wastewater discharge, requiring smarter and more sustainable operations. Regulatory bodies are imposing stringent measures to mitigate these impacts, prompting the industry to adopt sustainable practices and technologies. Life Cycle Assessment (LCA) models are crucial in this effort, pro-viding a comprehensive evaluation of environmental impacts and aiding decision making for sustainable manufacturing. However, organisations prioritise the confidentiality of their sensitive data, which can hinder collaborative efforts and LCA calculations. This paper addresses organisational requirements for improving confidentiality, tamper-proof data transfer, and ensuring data sovereignty. The ongoing proof-of-concept introduces a novel approach in LCA, employing Secure Multiparty Computation (SMPC) and data spaces to enable confidentiality-preserving LCA. Our solution ensures data sovereignty and accurate LCA calculations, promoting sustainable practices across the value chain. This paper lays the foundation for a collaborative data platform that meets the critical needs of confidentiality, security, and sustainability in the process manufacturing industry.

This paper proposes a framework designed to optimise energy consumption in vertical farming. It aims to maximise cost efficiency by balancing between minimising system operations during the electricity price peaks and the ability to trade capacity on the FCR market while also fulfilling constraints on the internal growing process. We consider that the vertical farming system has distributed control with a series of actuators controlled by various spatially distributed PLCs that we refer to as agents, to underline their independence. The paper conducts two experiments for a lO-agent system with a Pareto controller and a lOO-agent system with a Lagrangian approach and shows the balance between more cost-efficient momentary energy consumption control.

This paper presents a novel approach for tracking products and processes within industrial multi-agent control systems by leveraging blockchain technology. The suggested solution facilitates the recording and validation of every step involved in creating a tailored product through the utilization of Ethereum-based smart contracts. The OWL ontology is used to describe agents and their capabilities and these software agents interact with IEC 61499 function blocks for process execution. The software agents record process events at each stage on the blockchain and the latter smart contract helps to trace and verify these process sequences of the customised product.

Formal verification methods like model checking can provide mathematical proofs of design correctness, so their use is justified in applications where safety or reliability requirements are high. A key challenge for the wider adoption of model checking is the effort and expertise needed in formalizing functional requirements into verifiable properties. A particular challenge in specifying formal properties for industrial instrumentation and control (I&C) logics is accounting for the sequencing and timing issues that arise from, e.g., the dynamic behavior of the plant being controlled. In this paper, we evaluate different visual property specification languages that are aimed at making formal methods more accessible. We have collected 3923 formal properties from practical model checking projects in the nuclear and rail traffic industries and identified the most commonly occurring types of properties. Based on the sample data, a real-world example logic, and our practical experience, we identify requirements for a user-friendly property specification language most suited for our specific domain of industrial I&C.

The design of safety-critical cyber-physical systems requires a rigorous check of their operation logic, as well as an analysis of their overall instrumentation and control (I&C) architectures. In this article, we focus on the latter and use formal verification methods to reason about the correctness of an I&C architecture represented with an ontology, using the example of a nuclear power plant design. A safe nuclear power plant must comply with the defense-in-depth principle, which introduces constraints on the physical and functional components of the I&C systems it consists of. This work presents a method for designing nonfunctional requirements using function block diagrams, its definition using logical programming, and demonstrates its implementation in a graphical tool, FBQL. The tool takes as input an ontology representing the I&C architecture to be checked and allows visual design of complex nonfunctional requirements as well as explanation of the results of the checks.

This work develops a concept of a natural language co-pilot for the creation of IEC 61499 applications to accelerate initial testing and development. The co-pilot addresses the challenge of generating the correct function blocks that can be opened in popular IEC 61499 IDEs. In our case study, we focus on the generation of the centralised controller that operates particular equipment to perform a defined process. In addition, we have developed a scheme for how the co-pilot will be integrated into the FBME IDE as an AI assistant in the next steps. In the discussion, we provide valuable information for future co-pilot developers on the possible problems they might face in this area and how to overcome them.