Complex, industry-wide challenges such as sustainable production require collaboration across various industry actors, such as manufacturers, automation system providers and engineering technology suppliers, as well as across their related systems. While the digital twin paradigm offers immense potential through virtual asset representations for advanced predictions and analytics, building digital twins that are shared across organization boundaries and interfacing with the existing systems is not easily achieved. In fact, lack of interoperability of asset digital twins has been recognized as a growth inhibitor as well as limiting reaching the full potential and maturity of digital twins.As a solution, we present a modular, interoperable digital twin architecture named CRADLE, short for Cross-Vendor Asset Digital Twin Architecture to enable collaborations across organizational boundaries and illustrate it via an application to paper manufacturing. The industrial interoperability standards of Asset Administration Shell (AAS), Functional Mock-Up Interface (FMI), OPC UA and AutomationML, are suitably combined for integration with multiple industrial production systems as well as different cloud platforms. Use cases of energy optimization and emissions reduction, operational planning and material flow optimization are enabled through the cross-vendor asset digital twin and illustrated in the context of paper manufacturing.

Asset engineering process in energy industry domain is a complex multi-disciplinary and multi-organizational process including an iterative exchange of a large number of artifacts. Legacy document-centric exchange process of those artifacts is an error-prone semi-manual process negatively impacting overall project duration and quality. We present results of a collaborative study between ABB and Equinor exploring the potential of the digitalization of this process based on Industry 4.0 technologies, especially the Asset Administration Shell. An exemplary engineering workflow including OPC UA and AutomationML models embedded in Asset Administration Shells was implemented along with novel Asset Administration Shell infrastructure. Despite minor flaws in maturing Industry 4.0 technologies, no major roadblocks were identified.

Long life cycles of OT equipment used in process industry pose a burden to the adoption of high-paced Industry 4.0 IT applications. NAMUR Open Architecture (NOA) specifies a reference architecture to securely decouple the life cycle of IT and OT components, allowing both to evolve on the required pace. Verification of Request (VoR) and Security Gateway are two key concepts of NOA to allow controlled information traversal both ways between IT and OT domains. In this work we present a cloud-native software architecture of VoR by using a standardized OPC UA PubSub communication over MQTT. The architecture has been successfully validated on a simulated system using Kubernetes clusters and Virtual Machines hosting product-grade DCS and edge components.

Large language models (LLMs) providing generative AI have become popular to support software engineers in creating, summarizing, optimizing, and documenting source code. It is still unknown how LLMs can support control engineers using typical control programming languages in programming tasks. Researchers have explored GitHub CoPilot or DeepMind AlphaCode for source code generation but did not yet tackle control logic programming. A key contribution of this paper is an exploratory study, for which we created 100 LLM prompts in 10 representative categories to analyze control logic generation for of PLCs and DCS from natural language. We tested the prompts by generating answers with ChatGPT using the GPT-4 LLM. It generated syntactically correct IEC 61131-3 Structured Text code in many cases and demonstrated useful reasoning skills that could boost control engineer productivity. Our prompt collection is the basis for a more formal LLM benchmark to test and compare such models for control logic generation.

Modular automation is a recent concept for industrial automation offering a more flexible production with less engineering effort. Historically, incompatible standards for modular automation exist in different industrial segments, e.g., in process automation (Module Type Package) and discrete automation (PackML). The incompatibility of these standards has a particular negative impact on so called hybrid or mixed-equipment production facilities where process and discrete manufacturing modules co-exist in a physical installation. In this contribution, we propose an integration approach of both standards which is based on Industry 4.0 technologies (e.g., Asset Administration Shell). Our approach is validated on a simulated process plant involving commercial soft-PLCs of multiple vendors for MTP modules and a BPMN-based process orchestrator.

PubSub is a recent introduction to a widely-accepted industrial communication protocol OPC UA. It is driven by OPC Foundation Field eXchange group (ex-FLC, ex-Shapers) to enable real-time OPC UA over TSN for cyclic communication in industrial automation. Furthermore, evolution of Soft Programmable Logic Controllers (PLC) to Virtual PLCs entails a wider use of software stacks and applications expected to provide necessary level of performance, which might be influenced by various configuration options of the application, the OPC UA stack, and the underlying operating system. In this work we address this issue with an experimental setup for benchmarking of cyclic PubSub applications using commercial off-the-shelf (COTS) hardware and a state-of-the-art open-source OPC UA PubSub stack. Experimental results show achievable jitter and cycle times for different message sizes, SDK options, and OS configurations.

Composite asset or systems engineering requires integration and verification of the constituent asset models at the system level. It requires integrating relevant asset data and dynamical models of the individual assets which may be developed using diverse design and simulation tools by multiple vendors. Key integration challenges of lack of interoperability among corresponding data and simulation models, and separated, inflexible application deployments are addressed in this paper via application to a drive-motor-load system. A novel cloud-enabled drive-motor-load simulation platform based on the usage of Asset Administration Shells (AASs) for automatic data exchange and Functional Mockup Units (FMUs) for interoperable simulation is presented, together with an initial application of containerization for securing components. The solution enables higher quality and efficiency of engineering through simulation-based asset dimensioning, what-if scenario simulations, and simulation-based calibration and optimization as well as flexible, user-friendly, and more secure application deployment. An AAS-based model integration for linking various domain models and their parameters across design, configuration, and virtual commissioning, including application-side load FMUs via AAS Simulation Submodels at the composite system level, enables data interoperability while also serving as a building block of the future drive-motor-load system’s digital twin. The solution enables various applications across different product lifecycle phases such as pre-sales (drive) customer engagement, simulation-based calibration and design optimization during engineering, advanced system validations and testing in virtual commissioning, and continuous customer and OEM trainings during commissioning and operations.

In today’s Industrial Internet of Things (IIoT), a broad range of communication protocols are utilized. Built-in security mechanisms enable these protocols to protect communication and defend against network attacks. However, before IIoT devices can utilize these security mechanisms, they need to be securely onboarded in the network. Although several onboarding solutions exist, there is no widely applicable and easy solution for all protocols. Thus, owners of IIoT devices must currently perform multiple processes until they can securely use a device in operation, which requires a high amount of manual effort and onboarding infrastructure.In this work, we present a generic secure onboarding solution for a broad range of network protocols based on OPC UA. OPC UA is particularly suited for this task, as it is one of the most widespread IIoT protocols and one of few protocols whose standard defines a secure onboarding. Our solution leverages the OPC UA onboarding process to equip other IIoT protocols with the initial trust and credentials to establish secure connections. To this end, only minor extensions to the OPC UA implementation on devices are necessary, such that device owners can reuse their OPC UA onboarding infrastructure without any modifications. As a proof of concept for our solution, we demonstrate the secure onboarding of an HTTPS web server. Our implementation fully reuses the reference implementation OPC UA sample server as infrastructure and only needs minor extensions to the IIoT device.

Monitoring and life cycle management of industrial plants and their devices is a crucial task to avoid plant downtimes and safety risks. The emergence of Edge Computing allows monitoring applications to be deployed close to the devices, benefiting from a minimum response time, but also adhering to strong privacy policies. At the same time, life cycle management applications need to involve information from multiple parties, e.g., the device vendor, the operator, and maintenance staff. Thus, information needs to be processed in a standardized format so that it can be exchanged across company borders. The Asset Administration Shell (AAS) serves as such a standardized information modeling and exchange format in Industry 4.0. This paper discusses use cases that benefit from a deployment of an AAS infrastructure on edge computing devices. We collected and analyzed use cases around device monitoring and management from recent sources in the industrial context and discuss how our vision of "AAS on the edge" enables these use cases. Furthermore, we list open challenges that currently hinder the successful implementation of these use cases in practice.

As malfunctioning devices may lead to expensive plant downtimes or to severe safety risks, monitoring of industrial plants and their devices is a crucial task. There are many providers for device monitoring solutions on the market. However, integrating third-party monitoring approaches into real industrial systems, especially for time-critical data, is complicated due to mismatching APIs and different parties using different formats for specifying the involved assets and data. This leads to expensive, time-taking, and error-prone manual work. In this paper, we present an edge-computing-based approach to integrate monitoring functionality in an industrial IoT system. It addresses the presented challenges by combining edge computing with an Industry 4.0 information modeling and access format, the Asset Administration Shell.

The digitization of value chains is an ongoing challenge in production. The Asset Administration Shell (AAS) aims to address this issue. Besides standardization activities, there is however little architectural guidance on how to bridge the gap between potential AAS use-cases and realization.In this paper, we describe four AAS related use-cases that we derived from 15 application projects which adopted the AAS into industrial contexts. For each of the four use-cases, we devise an architecture blueprint that documents our experiences when applying the AAS. By utilizing these blueprints, practitioners can benefit from our experiences when implementing the AAS and bridge the gap between use-cases and implementation more easily.

Abstract With the increasing demand for customized systems and rapidly evolving technology, software engineering faces many challenges. A particular challenge is the development and maintenance of systems that are highly variable both in space (concurrent variations of the system at one point in time) and time (sequential variations of the system, due to its evolution). Recent research aims to address this challenge by managing variability in space and time simultaneously. However, this research originates from two different areas, software product line engineering and software configuration management, resulting in non-uniform terminologies and a varying understanding of concepts. These problems hamper the communication and understanding of involved concepts, as well as the development of techniques that unify variability in space and time. To tackle these problems, we performed an iterative, expert-driven analysis of existing tools from both research areas to derive a conceptual model that integrates and unifies concepts of both dimensions of variability. In this article, we first explain the construction process and present the resulting conceptual model. We validate the model and discuss its coverage and granularity with respect to established concepts of variability in space and time. Furthermore, we perform a formal concept analysis to discuss the commonalities and differences among the tools we considered. Finally, we show illustrative applications to explain how the conceptual model can be used in practice to derive conforming tools. The conceptual model unifies concepts and relations used in software product line engineering and software configuration management, provides a unified terminology and common ground for researchers and developers for comparing their works, clarifies communication, and prevents redundant developments.

Modular automation is an upcoming paradigm to improve flexibility and maintainability of industrial production systems. The lack of interoperability between equipment adhering to different modular automation specifications limits module sourcing and hampers coexistence of discrete and process modules in joint hybrid production applications. In this work, we present a reference software architecture for modular automation which is able to cover existing specifications and demonstrate how it can be used to assess alternatives of cross-standard orchestration. Based on this foundation, next steps regarding cross-module and cross-orchestrator communication are outlined.

Many Internet-of-Things (IoT) applications for smart homes, connected factories, or car-to-car communication utilize broker-based publish/subscribe communication protocols, such as the MQTT protocol. Commercial IoT applications have high reliability requirements for messaging, as lost messages due to unstable Internet connections or node failures can harm devices or even human beings. MQTT brokers implement numerous architectural availability tactics, but former analyses of MQTT communication have mainly focused on performance measurements under stable conditions. We have created the MAYHEM resilience testing tool for MQTT brokers and applied it in various resilience experiments on different MQTT brokers (VerneMQ, Mosquitto, HiveMQ, EMQ X). We found that MQTT QoS level 0 is already robust against minor packet loss, that selected broker message persistency solutions can lead to lost messages, and that most clustered MQTT brokers favor availability and performance over communication integrity. The results can support IoT practitioners in architectural decisions and researchers as well as broker vendors in optimizing designs and implementations.

The desired flexibility of industrial automation systems foresees among others flexible deployment and execution of control applications on distributed control nodes. This task can be performed more efficiently by an automated deployment algorithm yielding a valid deployment and optimizing non-functional objectives.Although extensively investigated, automated deployment approaches for the automotive domain cannot be translated to industrial control applications, due to a different execution semantics. Thus, in this paper, we present a method of satisfiability modulo theories (SMT)-based automated deployment of the industrial automation systems. We formalize and implement domain-relevant constraints and objectives. Our contribution is threefold: 1) we formalize the functional coupling and end-to-end deadline constraints and objectives while considering the semantics of control applications, 2) we encode the deployment problem into an SMT form, and 3) we validate the approach on an abstract example and a domain-relevant use case.The results obtained in this paper will allow application engineers to fulfill functional and real-time requirements by automatically solving the deployment problem.

Transforming a clone-and-own (i.e., new product variants are created by copying and modifying existing artifacts) code structure and development process to a Software Product Line Engineering (PLE) approach is a tedious and error-prone task. Holistic tool support for such a process is highly desirable, especially to lower efforts and to speed up the transformation. Unfortunately, such a holistic toolchain for reverse engineering of variability, supporting variant-centric and platform-centric extraction approaches is not available. In this paper, we present a toolchain covering the first steps for moving a clone-and-own product development to a PLE approach. We validate the first prototype of the toolchain on a case study consisting of industrial firmware for smart motor controllers and we show that even this early prototype reduces time and effort for moving to a configurable platform approach in the sense of PLE.

One of the main challenges of future industrial systems is to flexibly (re)deploy control applications on hardware controllers - a feature that is missing in most state of the art automation systems. Due to the heterogeneous structure of control systems, e.g. different standards and hardware, a silver bullet architecture for flexible deployment seems to be infeasible. Instead we propose an abstract architecture covering different concrete reconfiguration system architectures along with a taxonomy for design decisions for the realization of such a system. The capability of the abstract architecture is demonstrated by mapping three fundamentally different concrete reconfiguration system architectures and is verified on an industrial use case of a logistic system of an aluminum cold rolling plant.

The overall manufacturing process for a product can be composed of different phases and tasks. Each task can be seen having its own recipe or set of steps to follow and parameters to apply. The ways to represent these phases and tasks can be different depending on the level within the automation pyramid (shop floor / manufacturing execution / enterprise resource planning). This article proposes an approach to unify representations and therefore interconnections of various components of the manufacturing plants. PackML is used as a representation language of state machines for different components. The article describes a tool chain needed for developing and deploying the components to automate manufacturing sites. The use of the approach makes it possible to holistically represent production sites revealing interdependencies between different phases and tasks at the shop floor.

Feature identification and localization is a complicated and error-prone task. Nowadays it is mainly done manually by lead software developer or domain experts. Sometimes these experts are no longer available or cannot support in the feature identification and localization process. Due to that we propose a tool which supports this process with an iterative semi-automatic workflow for identifying, localizing and documenting features. Our tool calculates a feature cluster based on an defined entry point that is found by using information retrieval techniques. This feature cluster will be iteratively refined by the user. This iterative feedback-driven workflow enables developer which are not deeply involved in the development of the software to identify and extract features properly. We evaluated our tool on an industrial smart control system for electric motors with first promising results.

Industry 4.0 has come up with an impressive number of additional terms and definitions e.g. Asset Administration Shell or Digital Twin. Those terms stand for Industry 4.0 coreparadigms, but their meaning is not harmonized even among experts. This is a source of misunderstanding and confusion. In this paper, the mentioned terms are discussed along the life cycle of a plant. A plant's life cycle comprises the whole process from its idea to its destruction. During the discussion of the terms not only the concepts, but also the visions of Industry 4.0 are clarified. Goal of this paper is not to define additional terms, but to explain and substantiate existing ones and to solve apparent contradictions. Additional outcome of the discussion are architectural recommendations for an upcoming Industry 4.0 architecture. Moreover, suggestions for device manufacturers, system integrators, plant owners and Industry 4.0 architects are given.

In the last few years, resources sharing has been one of the main focal points of the German initiative “Industrie 4.0”. Resources sharing can be properly guided by load distribution algorithms. With the availability of many load distribution algorithms, it can be an intricate decision to match the use case with the correspondent most fitting algorithm. For an easier matching process, a benchmark is introduced along with the most important quantitative and qualitative key performance indicators that cover the pivot factors that affect the performance factors in the field of engineering automation.

Integrating control development phases requires a consolidated communication architecture. Currently, different communication protocols are used at the different development stages preventing a fully integrated solution to exist. We propose an approach using a unified communication protocol to jointly integrate the control development stages. MATLAB and Simulink were connected to a programmable logic controller successfully resulting in a fully integrated control development chain and opening the doors for further development in other potential areas.

OPC UA and DDS are communication protocols for the Industrial Internet. However, they make use of contrasting communication patterns and represent different architectural styles. We discuss these differences and their impact in an Industrial Internet and Internet of Things context. Further, we show up the possibilities for hybrid implementations leveraging the features of both OPC UA and DDS. For this, we provide a) a mapping of the OPC UA data types into DDS and b) a set of DDS quality of service policies that match the guarantees made by the standard OPC UA binary protocol.

Representational state transfer (REST) is a wide-spread architecture style for decentralized applications. REST proposes the use of a fixed set of service interfaces to transfer heterogeneous resource representations instead of defining custom interfaces for individual applications. This paper explores the advantages of RESTful architectures, i.e., service-oriented software architectures comprised RESTful services, in industrial settings. These include communication advantages such as reduced communication overhead and the possibility to introduce caching layers, and system design advantages including stable service interfaces across applications and the use of resource-oriented information models in cyber-physical systems. Additionally, a RESTful extension to the open platform communications (OPC) unified architecture (OPC UA) binary protocol is proposed in order to leverage these advantages. It requires only minimal modifications to the existing OPC UA stacks and is fully backward compatible with the standard protocol. Performance benchmarks on industrial hardware show a throughput increase up to a factor of eight for short-lived interactions. This reduction of overhead is especially relevant for the use of OPC UA in the emerging Industrial Internet of Things.

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.

RESTful interfaces are a wide-spread architecture style for webservice implementations and are built upon the resource-oriented approach to decentralized architectures (ROA). REST postulates a set of requirements that are not covered by the OPC Unified Architecture (OPC UA) communication protocol per se. We propose a set of simple extensions to the OPC UA binary protocol that enable RESTful communication. The evaluation shows an order of magnitude improvement in the use of communication resources for sporadic service requests. Additionally, RESTful OPC UA allows applications to profit from the advantages of the resource-oriented architecture style, such as caching and loose application coupling.

Many tasks in factory automation can be solved with the bare knowledge of used and possible product flow paths in a plant. Unfortunately, the information about these is usually not available explicitly, but is distributed among different models and tools. We present a model that describes discrete product flow paths and aims to play a similarly important role as piping and instrumentation diagrams in process industry. The model's extensibility and its CAEX representation allow a seamless integration into the established model and tool landscapes.

Automation of tedious engineering tasks allows for more efficient plant commissioning and reconfiguration. Usage of knowledge-based systems is one possibility to solve this challenge. We present a rule-based system that is based on declarative graph database queries which have the advantage of being comprehensible by both computer scientists and engineering domain experts. The applicability of the system is verified in two engineering use-cases: the creation of function blocks for basic control and flow path monitoring. Promising results from the first use-case reveal further application fields of the system.

Describing procedures is essential for modeling and controlling technical processes. Although various procedure description methods are available from computer science, system theory and industrial automation, they are only partially suitable as a generic method for engineering automation procedures. In order to close this gap, we propose a procedure description formalism together with a concept of its integration into existing automation systems. By utilizing of the proposed means we obtain an engineerable, generic and user accepted procedure description method.