Advances in Automation and Artificial Intelligence continue to enhance the autonomy of process plants in handling various operational scenarios. However, certain tasks, such as fault handling, remain challenging, as they rely heavily on human expertise. This highlights the need for systematic, knowledge-based methods. To address this gap, we propose a methodological framework that integrates Large Language Model (LLM) agents with a Digital Twin environment. The LLM agents continuously interpret system states and initiate control actions, including responses to unexpected faults, with the goal of returning the system to normal operation. In this context, the Digital Twin acts both as a structured repository of plant-specific engineering knowledge for agent prompting and as a simulation platform for the systematic validation and verification of the generated corrective control actions. The evaluation using a mixing module of a process plant demonstrates that the proposed framework is capable not only of autonomously controlling the mixing module, but also of generating effective corrective actions to mitigate a pipe clogging with only a few reprompts.

Process plants are becoming increasingly autonomous to compensate for the lack of experienced plant operators. However, certain activities still need to be carried out by humans. To move from a low to a high level of autonomy, an evaluation of operator and plant behavior is necessary. This provides insights into suitable automation measures. Our contribution presents two methods for the creation, integration and evaluation of operator behavior in plant simulations. This will enable the identification and learning of suitable control actions for different levels of plant autonomy at an early stage in plant engineering.

At present, Process Orchestration Layers lack necessary functionalities to control individual modules in modular electrolysis plants based on electricity supply and hydrogen demand. This paper addresses the domain-specific refinement of Process Orchestration Layers to operate a modular electrolysis plant in an economical manner. The refinement, consisting of the Demand Side Management and PEA-Scheduling, allows the integration of forecasts from electricity sources and hydrogen sinks to determine the operating points of individual electrolysis modules. First, the requirements for such a refinement concept are established and then the developed concept is illustrated by the use case of a hydrogen refueling station.

While modular plants and their modular automation have received increasing attention in the wake of the development of a standardized interface, the Module Type Package (MTP), suitable approaches for systematic support in early phases of their engineering are still missing. Particularly in early engineering phases, a continuous collaboration between multiple engineering disciplines is essential to define what is required in terms of services and modular automation using MTP. In this contribution, the authors propose an approach for an automated generation of MTP skeletons based on ontologies in the early engineering phases. The approach uses intention-based engineering, wherein the first steps intentions and required functionalities of the modular plant are defined and, subsequently, MTP services are modeled inside an ontology. In a further step, this ontology is automatically transformed into an MTP skeleton representing an MTP without instance-specific implementation of the services. The approach has been evaluated using the Tennessee Eastman Process (TEP), a widely known reference process for control systems design and analysis.

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.

While there exist approaches to integrate heterogeneous data using semantic models, such semantic models can typically not be used by existing software tools. Many software tools — especially in engineering — only have options to import and export data in more established data interchange formats such as XML or JSON. Thus, if an information which is included in a semantic model needs to be used in a such a software tool, automatic approaches for mapping semantic information into an interchange format are needed. We aim to develop a generic mapping approach that allows users to create transformations of semantic information into a data interchange format with an arbitrary structure which can be defined by a user. This mapping approach is currently being elaborated. In this contribution, we report our initial steps targeted to transformations from RDF into XML. At first, a mapping language is introduced which allows to define automated mappings from ontologies to XML. Furthermore, a mapping algorithm capable of executing mappings defined in this language is presented. An evaluation is done with a use case in which engineering information needs to be used in a 3D modeling tool.

The modularization of process plants and their modular automation are innovative concepts to meet increasing demands for flexibility in plant operation. However, previous approaches to support the engineering of such modular plants do not focus on the early phases of requirements elicitation and concept design, although these early phases are crucial for the economic efficiency of the later plant. This paper presents a method for the formalized description of intentions in the early engineering phases of modular process plants. According to this method, plant operators create a formalized model of their intentions and provide it to the module manufacturers in a modularized form. This allows a reduction of effort in the planning and development of the plant. The approach is demonstrated using an oil, gas and water separation process performed by a modular process plant.

The modularization of process plants represents an innovative approach to meet the increasing requirements regarding flexibility. The current research focuses on 100%modular process plants, which are characterized by high flexibility of the plant, but unlike monolithic process plants, they are not designed for a specific and optimized operating point. In addition, the flexibility provided by the modularity is not needed everywhere in the plant. Therefore, hybrid process plants, i.e. a combination of a monolithic plant and several modules, are expected to overcome this issue. This paper presents the key terms in the context of hybrid process plants as well as the requirements for the engineering and automation of such plants. Furthermore, a generic workflow model for the engineering of hybrid process plants is derived, with focus on the conceptual design.

The upcoming challenges in the process industry demand a high flexibility, shorter product development cycles as well as energy and resource efficient production. Especially, energy efficiency of process plants is of substantial importance with regard to the high energy consumption in the process industry. With the introduction of modules and modular plants, the industry tries to overcome these challenges. However, an energy efficient production requires the identification, analysis and utilization of energy potentials. In order to be able to identify energy efficiency potentials in production, the introduction of an energy management system according to ISO 50001 plays a significant role. This paper investigates the extent to which energy management is practiced in the context of modular production and whether there is a need for research. Additionally, a concept is presented how energy management could be implemented in the engineering and operation phases of modular plants.