This paper explores a multi-agent reinforcement learning approach for real-time control of HVAC systems during demand response events. The heating, ventilation and air conditioning (HVAC) systems are major energy consumers on cruise ships. At the same time, the large time constants of HVAC systems make them a strong candidate for demand response, as energy consumption can be adjusted with delayed effects on occupant comfort. However, this inherent slowness also makes control a complex and challenging task. Additional factors, such as solar heat load, significantly affect cabin temperature, thus complicating the control strategy. Since actions in chillers and air handling units influence fan coil units, optimization must be done holistically.

The cruise ship industry is under increasing pressure to reduce greenhouse gas emissions, as international regulations define ambitious requirements and goals for modern cruise ships. One of the most significant consumers of energy onboard cruise ships are their Heating Ventilation and Air Conditioning (HVAC) systems. However, the energy optimization of HVAC systems is challenging, as they are impacted by a number of uncontrolled variables, such as changing weather conditions, passenger behavior, and the demands of other significant energy consumers, such as propulsion systems. Reinforcement Learning (RL) is often used to tackle such complex optimization tasks, however concerns over ensuring the safety of RL optimized systems hinders its adoption in industry, especially in the context of safety-critical systems. This paper presents the initial findings of applying a novel approach to ensure safety in RL: a safety shield developed utilizing a novel hazard analysis method, System-Theoretic Process Analysis. In this work the safety shield is used to both train the RL agent as well as block unsafe behavior in operation. Preliminary findings suggest that blocking unsafe behavior during training hinders the ability to learn a safe RL policy, however, when used in testing the approach is capable of significantly reducing the number of safety violations.

Cruise ships are large greenhouse gas emitters. Given the net-zero emission goal by 2050 set by the International Maritime Organization, it is crucial to focus on different strategies for reducing emissions. One promising strategy is to work on reducing energy losses due to non-optimal management of a cruise ship’s complex energy system. Effectively managing a ship’s energy consumption is a difficult task. Modern reinforcement learning approaches have been employed to the task at hand. Results have shown improvements over traditional optimization methods that fail to scale to large stochastic problems such as ship energy optimization. However, reinforcement learning approaches lack a direct focus on ensuring the safety of the system, which is critical for a real-world application.This paper showcases work in progress related to developing a safe reinforcement learning (RL) framework for ship energy optimization. We utilize a formal safety shield to block unsafe control actions and a large language model (LLM) to generate a reward function (RF) that incorporates safety constraints. We construct a white-box physical system of a ship’s energy management system and a faster black-box surrogate model as environments to train and test our RL methods. Preliminary results show that the integration of the safety shield and the LLM-generated reward function is promising in reducing safety violations.

This paper presents an approach to optimizing the energy cost of heating a building during the cold season using geothermal energy. A building model is developed using the IDA-ICE software and calibrated with real building data for accuracy. The optimization problem is addressed with a deep reinforcement learning (DRL) agent, which minimizes overall energy costs by interacting with the building while considering real-time electricity price and weather forecasts. The proposed method adapts to dynamic conditions, ensuring efficient thermal management and occupant comfort. The results demonstrate the effectiveness of the DRL-based controller in reducing energy costs compared to the currently used rule-based control strategy while maintaining optimal comfort levels. This work contributes to the advancement of cost-efficient heating strategies for sustainable building energy management.

The growing need for compliance with sustainability regulations force the adoption of sustainable practices, which consequently establish the need for data sharing for the purpose of Life Cycle Assessment (LCA), a critical method for evaluating environmental impacts. One key area where these data are essential is in calculating Scope 3 emissions, which can account for up to 90% of an organization’s total carbon footprint and require input from its suppliers or service providers. However, the confidential nature of industrial process data poses a hindrance to data sharing throughout the supply chain. To address this issue, this study explores the use of secure multiparty computation (SMPC) to enable privacy-preserving LCA computations. The performance of various SMPC protocols is evaluated in different security models (dishonest and honest majority, malicious, covert, and semi-honest) and computational domains (arithmetic modulo prime and modulo 2k). The evaluation focuses on key performance factors, such as computation time, data exchange, and communication rounds, using a flat supply chain model. The findings highlight the trade-offs between security, performance, and scalability for different SMPC protocols in the context of LCA. The study demonstrates the feasibility of applying arithmetic circuit-based SMPC for LCA over other protocols.

With the growing adoption of the IEC 61499 standard, heterogeneous distributed automation systems have become increasingly feasible in modern industry. Compared to traditional automation systems based on Programmable Logic Controllers (PLC), IEC 61499 open automation systems could be deployed to various platforms, such as low-cost ARM-based controllers, edge computing nodes, and even cloud servers. This trend raises a critical challenge in distribution optimization of automation software components. In particular, unlike IEC 61131, IEC 61499 supports event-based execution and software-hardware decoupling. It is easier to implement resource-demanding tasks in IEC 61499, such as artificial intelligence and embedded IT software, which makes computing-intensive control software distribution optimization more needed today.This work proposes a framework that optimizes the distribution of various resource-demanding control components in distributed automation systems. By leveraging a script-based auto-benchmarking system, a comprehensive computing performance knowledge base is established. Experimental results demonstrate that the proposed method outperforms other distribution combinations, significantly reducing the overall execution time of the system.

In this paper, we propose a cloud-based virtual commissioning Web platform for IEC 61499 compliant distributed automation systems that support Create-Read-Update-Delete operations for SoftPLC containers from various versions and provide a remote engineering workstation with an embedded web Integrated Development Environment (IDE), Human Machine Interface (HMI), and 3D simulation models. A water tank use case demonstrates the platform's flexibility, enabling control software testing entirely via a Web browser without local installations.

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.

With Industry 5.0, prioritizing worker well-being, the integration of human-related data into production processes poses challenges related to data privacy and compliance with regulations such as GDPR. This paper presents a comprehensive approach to anonymizing sensitive data collected from wearable devices. We propose a methodology that combines real-time processing and complex anonymization algorithms, ensuring end-to-end protection. We employ techniques such as normalization, hashing, and feature dropping. Our findings contribute to advancing privacy-preserving techniques in Industry 5.0 and underscore the importance of safeguarding user privacy in the era of advanced manufacturing.

The manufacturing domain relies on Digital Twins (DTs) to mirror physical systems digitally, facilitating simulation, monitoring, and optimization. However, existing DTs may fail to capture the rich contextual knowledge essential for decision-making in complex manufacturing processes. The evolution to knowledge-enhanced DTs is essential, as it integrates domain-specific knowledge models, enabling a profound understanding of processes. To address this gap, this research introduces a knowledge-enhanced DT framework for the production process. This framework utilizes the ontology-based approach to aid the knowledge integration with the manufacturing DTs. The designed framework consists of three essential layers: The source layer, the Streaming data and knowledge coupling layer, and the Service layer. The proposed framework was further implemented in a lab-scale manufacturing setting and validated through several tests. The results demonstrated the seamless integration of knowledge and streaming data in the production process.

This paper presents a methodology for increasing human-centric production systems flexibility using human factors-enabled digital twins. The paper includes an analysis of the relevant projects that incorporate human-related data collection and processing. The proposed system is capable of collecting human factors-related data from various sources and then use a decision-making algorithm to schedule the tasks according to assessed human operator conditions in real-time. The formed Digital Twin is able to depict the condition of the labourer and production system status in real-time using Visual Components simulation environment. Shown results prove that existing production systems are capable of adapting to the changing condition of the worker flexibly, optimising workflow, distributing tasks with AGVs and cobots, and applying changes in workplace ergonomics to achieve better safety and performance of the worker.

This paper presents the development progress of a methodology to enhance the dynamic visualization of remote Automated Guided Vehicles (AGVs) using open source frameworks as Gazebo and ROS. The approach is based on a deterministic path pre-calculated by edge computing, accessible for a 3D web visualization cloud platform. The trajectory displayed is verified by a live position streaming from the AGV and a predicted communication delay value. By succeeding on the methodology proposed, it is expected to enhance the fidelity of the 3D live representation for every trajectory executed dynamically and autonomously by AGVs in the shop floor, leaving behind an initial scenario with low visualization fidelity due non-deterministic behavior of long-distance communication channels (including wireless networks essential for AGVs). This work aims to have an impact on improving the user experience of remote web-based interfacing tools to visualize the behavior of cyber-physical systems in agile manufacturing.

The need of manufacturing industries to adapt to the demand from customers and the volatile market drives the need for digitalization to realize the so-called smart factory. Smart factory, Compared to traditional factories, smart factory needs to possess high flexibility and stability and often has to employ digital twin. Compared to IEC 61131-3 standard used in traditional industrial production, IEC 61499 standard can bring more advantages to meet the realization of Smart Factory, such as flexibility, distribution and event-driven execution. In this paper, we propose a new Virtual Commissioning (VC) architecture for IEC 61499-based control applications. We build an online collaborative VC platform with the help of cloud computing and containerization technologies. Furthermore, we discuss and propose the utilization of soft-PLC containers from different vendors to meet users’ commissioning requirements for different hardware configurations. Compared with the traditional offline single-person debugging method, our proposed architecture can improve the flexibility, collaboration and efficiency of control software debugging in a more interactive and collaborative style via the online platform we implemented.

The COVID19 pandemic has created tremendous challenges in the learning and education sector. Schools and universities are forced to close and most teaching activities have to be organized with very limited physical and social interaction between the teachers and students, and also among students. This is particularly difficult for certain learning activity, such as laboratory work where it usually involve the student’s direct interaction with equipments in the school and sometimes the need to work together with the their peers in the same space while interacting with the equipments. This paper presents an experience in shifting the delivery method of a process automation laboratory course at Aalto University from face to face teaching into hybrid due to the restrictionc caused by the pandemic. This paper describes the rework process of the course to realize this shift, and after the course, feedbacks are gathered from the student to see if the approach taken is welcomed by the students. The feedback appears promising, indicating 66% of the respondents agree that they like the hybrid method approach considered.

Quality control of products plays an important role in various stages of the manufacturing process. In particular the final control of the quality of a product before being shipped to a customer is crucial for maintaining customer satisfaction and avoiding costly recalls. Automating quality inspection and integrating it into a seamless Industry 4.0 setting is therefore an important topic in factory automation.We present early work towards an automated product inspection station. Our inspection station features a 3D scanner as well as a Virtual Reality headset for remote human inspection. In addition, our concept provides for automated analysis of scans in the cloud. We present an architectural concept as well as an early prototype.

This paper presents integration of software services of smart-sensors into distributed process automation systems using the IEC 61499 architecture. This solution enhances interoperability of IIoT devices and reduces system integration effort. Benefits of IEC 61499 for implementing systems with smart sensors mixing both change and time-based signals have been proven. This also promises reduced power requirements of the field devices.

Dynamic reconfigurability and adaptability are crucial features of the future manufacturing systems that must be supported by adequate software technologies. Currently, they are typically achieved as add-ons to existing software tools and run-time systems, which are not based on any formal foundation such as formal model of computation (MoC). This paper presents the new programming paradigm of service oriented SystemJ (SOSJ), which targets dynamic distributed software systems suited for future manufacturing applications. SOSJ is built on a merger and the synergies of two programming concepts of service oriented architecture, to support dynamic software system composition, and SystemJ programming language based on a formal MoC, which targets correct by construction design of static distributed software systems. The resulting programming paradigm allows the design and implementation of dynamic distributed software systems.

This paper presents a software design pattern for systems composed from distributed intelligent mechatronic modules which communicate with each other via wireless interface. The design pattern is formed by integrating the reliable communication mechanism called channel, which comes from a system-level programming language SystemJ. The paper demonstrates how the design pattern can be applied in an industrial automation example.

This paper proposes Service Oriented SystemJ - OPC UA (SOSJ - OPC UA), a service-oriented programming approach which targets dynamic industrial manufacturing systems. An extension of SOSJ, SOSJ - OPC UA utilizes OPC UA standard to introduce service orientation, enable interoperability with different actors in the systems, and compliance with Reference Architecture Model for Industrie 4.0 (RAMI 4.0) which defines OPC UA as the communication standard. The paper begins by describing new concept on the synergy of SOSJ and OPC UA. Then, SOA information exchange mechanisms which utilize OPC UA are defined that enable parties to find each other. SOSJ - OPC UA is then demonstrated in a simple manufacturing example to demonstrate its capability.

In product-centric manufacturing paradigm, a digital counterpart of a product will request manufacturing services to assemble itself. A modelling & assembly planning framework for product-centric design is considered and extended in this paper. Furthermore, we present a case-study on a product-centric digital twin controlling the assembly of its physical counterpart using a collaborative robot.

OPC UA is considered as an important communication technology for Industry 4.0 components. On the other hand, IEC 61499 is one of the technologies available for developing applications to the same components. In this paper, a proposal for an OPC UA information model for IEC 61499 systems is developed in order to enhance communication with IEC 61499 applications through OPC UA. Already existing related information models, particularly OPC UA for Devices and IEC 61131-3, are utilized as models and parts of the design. An OPC UA wrapper for IEC 61499 runtimes is presented as one possible way to implement the information model. Both the information model and the wrapper are then tested through a case study.

The heterogeneity of execution platforms and operating software in manufacturing machines and robots, as well as various sensors and actuators, creates challenges for integration into larger systems. Existing approaches make use of different types of middleware to mitigate the challenges of designing interoperable systems. However, middleware can significantly impede modular design and composition of software systems that are dynamic in nature. This paper elaborates upon those challenges and proposes using an approach called service-oriented SystemJ (SOSJ), based on the system-level programming language SystemJ enhanced with service oriented features. This approach allows developers to design dynamic software systems while adopting and incorporating legacy solutions. The approach is demonstrated on the integration of an industrial automation system, incorporating the use of multiple modular mechatronics stations and service robotics systems, represented by robot operating system-enabled Baxter robots. The proposed approach offers a simple service interface based on abstract objects for integrating robots and automation machines in the SOSJ world, without the need to modify the underlying mechatronics or robotics systems.

This paper proposes a novel extension for communication in the lEC 61499 standard. Inspired by the features found in the formal programming language SystemJ, the extension supports reliable and guaranteed communication in distributed execution of function block application(s)/program(s). The extension utilizes mechanisms agnostic on underlying network protocols and are based on formal semantics that guarantee data delivery. The use of proposed extension, called channel, is demonstrated in an industrial automation-type example.

Industrial automation and control systems are going through a big change, adopting the modern computing and Internet technologies to give completely new agility and adaptability properties to production plants, transport and energy systems and infrastructures, often referred to as Industrial Cyber Physical Systems (ICPS). In manufacturing, they are expected to cope with product customizations, changes in the market or supply chain, or failures. However, the wide adoption of ICPS requires rethinking approaches to their design and programming. This article reviews the state of the art of programming approaches for ICPS and analyses their capabilities, in the hope that it will help researchers to identify potential opportunities of future development of software solutions for ICPS.

One of the key challenges in modern manufacturing systems is how to dynamically reconfigure software behaviors that govern machines to reflect changes in physical manufacturing process without completely resetting the entire manufacturing operation. The existing software solutions used to describe software behaviors in manufacturing systems are typically not based on formal semantics and model of computation and have limited capabilities in handling dynamic adaptation/reconfiguration. This paper presents the Service-Oriented SystemJ (SOSJ) framework that supports a new programming paradigm for designing dynamic distributed manufacturing systems. SOSJ combines the system-level language SystemJ and service-oriented architecture (SOA) paradigm to take advantages of both SystemJ's correct-by-construction formal semantics and SOA's dynamic features, respectively. The paper describes the concepts and functionalities of SOSJ, which enable dynamic reconfiguration of a typical manufacturing system. Performance benchmarks are run to compare the capabilities of SOSJ to a multiagent system framework JADE.

In this paper, we propose using an approach based on the system-level programming language SystemJ extended with service oriented features, called SOSJ, to design dynamic interoperable software systems. The approach abstracts and integrates the worlds of automation and robotics systems by using a simple service interface based on abstract objects within SOSJ. We demonstrate our approach in a real-life automated bottling system scenario that uses multiple FESTO modular stations operating in SOSJ and integrating them with two Baxter robots operating in ROS without the need for any modification of the underlying mechatronics or robotics systems.

This paper presents new changes and improvements in the architecture of a programming paradigm Service Oriented SystemJ (SOSJ) to tackle large distributed systems. The programming paradigm makes use of the synergy of two programming concepts of Service Oriented Architecture (SOA) suitable for dynamic system composition and formal GALS (Globally Asynchronous Locally Synchronous) language SystemJ amenable for designing safe static concurrent distributed systems. The use of SOSJ framework based on the new architecture is demonstrated in an industrial manufacturing example and initial benchmarks that evaluate the framework's performance in large distributed systems are shown.

This paper presents the Service Oriented SystemJ (SOSJ) framework, which combines correct-by-construction language features of GALS (Globally Asynchronous Locally Synchronous) system-level language SystemJ with dynamic reconfiguration features of Service Oriented Architecture (SOA), creating a new programming paradigm suitable for designing dynamic distributed manufacturing systems. The paper demonstrates new concepts introduced by SOSJ which enable dynamic online reconfiguration of typical distributed manufacturing systems. Some performance benchmarks are used to showcase the capability of the SOSJ framework.