The design process for manufacturing systems involves different architectural design decisions (ADDs), including deploying software to hardware components, determining shop-floor topology, and planning production tasks for stations. These ADDs exhibit complex interactions, where the synthesis of one ADD impacts other ADDs, highlighting the need to investigate their dynamic interplay. However, current research prioritizes individual ADDs over exploring multiple ADDs together. This work investigates a multi-dimensional design space exploration (DSE) of deployment, shop-floor topology, and production planning ADDs. We introduce mitigation constraints to ensure the compatibility among these ADDs. To evaluate our approach, we apply it to a flexible manufacturing line demonstrator. Furthermore, we assess and compare various DSE workflows, providing preliminary guidance to software architects on mitigatlng conflicts and enhancing the quality of ADDs.

Optimizing evolving manufacturing systems often requires considering the interplay of various architectural design decisions (ADDs), especially at the lower levels of the automation pyramid. Here, decisions about programmable logic controllers, stations, and shop-floor topology directly impact product characteristics. This necessitates a multidimensional design space exploration (DSE) approach that synthesizes diverse ADDs together. However, integrating diverse ADDs within the complex context of industrial automation remains a challenge, and existing DSE solutions from other domains often lack direct applicability. This work introduces a novel multidimensional DSE approach for such systems, leveraging domain-specific input models to automatically generate valid and optimal deployment, shop-floor topology, and production planning ADDs. We evaluate the approach by assessing the quality of derived ADDs against various domain optimization goals. This evaluation compares our approach to both random and manual ADDs, utilizing a prototype implementation and realistic manufacturing architectures.

The complexity of Industry 4.0 systems makes it challenging to manually synthesize and optimize architecture-level decisions, such as service deployment and composition. To address this challenge, we propose an approach that utilizes a satisfiability modulo theories (SMT) solver to (semi-)automate service deployment and composition synthesis. Thereby, we conceptualize, formalize and implement the complete workflow from input service workflows to valid and optimized service deployments and compositions. We demonstrate the practical application of our approach in an Industry 4.0 scenario, specifically the flexible production of new products. We evaluate the effectiveness of the proposed approach by investigating its benefits in terms of engineering effort, complexity of the resulting IEC 61499-based applications, and improvement of communication coupling quality attribute (QA).

Design of manufacturing system involves various architectural design decisions (ADDs), including software and hardware component allocation, production service composition, plant layout determination, and production planning. These ADDs gain significance in Industry 4.0 (I4.0) scenarios due to the frequent need for architecture synthesis to achieve adaptable and flexible production processes. Additionally, synthesizing ADDs in conjunction with each other increases the decisions’ impact on system quality attributes (QAs). The increasing importance of architecture synthesis and optimization (ASO) in I4.0 necessitates an overview of ADDs within this context. This paper expands on the previous work by creating a landscape of I4.0-related ADDs based on insights from the BaSys 4.0 research project series. The landscape describes relevant ADDs and their relationships, and suggests multi-dimensional ASO workflows. Mapping the ADD landscape to BaSys 4.0 research enhances idea generation and the exploration of existing solutions in ASO.

Engineering distributed control systems is a complex task, where the complexity and, thus, costs of the software development are growing rapidly. To keep the software complexity at an acceptable level and save time for development and subsequent maintenance, new solutions are sorely needed. In this paper, we investigate the advantages of using skills - universal control device interfaces - for generating complex logic in distributed control environments. By enriching a skill interface with the information about the dynamic behavior of a component under control, we compose the functionalities of individual control devices. The logic, required for such composition, is automatically derived from the interface description and the production plan, identifying the required skill sequence. The evaluation, executed using two industrial demonstrators, shows that the approach successfully handles different behavioral models and is capable of generating fault-tolerant orchestrators, including error handling scenarios. Overall, for developing a complex logic in a distributed skill-based automation system, the proposed approach shows significant savings in development time allowing to automate the skill composition task.

An asset administration shell (AAS), as a key concept of Industry 4.0 (I4.0), provides a machine-accessible interface to any kind of asset. To enable interoperability and smooth integration of the devices into the I4.0 middleware, an application implementing the device's functionality should be able to interact with different AASs. In this work, we investigate the integration of the Programmable Logic Controller (PLC) runtime systems into the I4.0 middleware. For doing this, we specify the function blocks (FBs) for connecting the PLCs with AASs and other I4.0 components, such as registry and discovery server. We analyze the requirements of such FBs while focusing on REST/HTTP- and OPC UA-based AASs, and provide interface specification for IEC 61499- and IEC 61131-3-based FBs. Furthermore, we implemented an FB library that enables communication with an AAS from the respective control applications. Those FBs allow accessing properties and invoking operations of remote AASs, as well as hosting AASs submodels. Common functionalities, such as registering the runtime system at the registry component, or finding AASs, are also supported. The results obtained in this paper will ease interaction with the complex AAS structure from the low-level devices.

The fourth industrial revolution (Industry 4.0) anticipates unplanned changes of production processes. Production changes may trigger synthesis, and preferably optimization, of architecture-level decisions, such as service deployment and composition. Performing such architecture-level decisions manually is difficult due to the ever-rising complexity of Industry 4.0 systems. In order to (semi-)automate the architecture synthesis and optimization, we propose an approach of service deployment and composition by using existing domain models. Our contribution is threefold: (1) We suggest a workflow with domain models for architecture synthesis in the industrial automation. (2) We display the formalization on a part of the workflow and provide an initial prototype of service deployment synthesis using a satisfiability modulo theories (SMT) solver. (3) We envision a way of service composition and code generation, and prototypically implemented it as conclusion of the suggested workflow. We demonstrate the practical use of the proposed approach in the Industry 4.0 scenario, i.e., flexible production of new products.

Architectural design decisions, such as service deployment and composition, plant layout synthesis, or production planning, are an indispensable and overarching part of an industrial manufacturing system design. In the fourth industrial revolution (Industry 4.0), frequent production changes trigger their synthesis, and preferably optimization. Yet, knowledge on architecture synthesis and optimization has been scattered around other domains, such as generic software engineering. We take a step towards synthesizing current knowledge on architectural design decisions in Industry 4.0. We developed a taxonomy describing architectural models, design decisions, and optimization possibilities. The developed taxonomy serves as a guideline for comparing different possibilities (e.g., application of different optimization algorithms) and selecting appropriate ones for a given context. Furthermore, we reviewed and mapped 30 relevant research works to the taxonomy, identifying research trends and gaps. We discuss interesting, and yet uncovered topics that emerged from our review.

An asset administration shell (AAS), as a key concept of the Industry 4.0, provides a machine-accessible interface to any kind of asset. An application implementing the devices functionality should be able to interact with different AASs.In this work, we specify the function blocks (FBs) for accessing properties and invoking operations of AASs. We analyzed the nature and requirements of such FBs while focusing on REST/HTTP- and OPC UA-based AASs and provided IEC 61499-based implementation.The results obtained in this paper will ease interaction with the complex AAS structure from the low-level devices.

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.

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 fourth industrial revolution introduced additional requirements on the industrial systems' control software in order to cope with current manufacturing systems' flexibility demands. These requirements include, among others, a dynamic reconfigurability, software reusability and an external service orchestration. This work presents the design of an industry 4.0 compliant control software architecture resulting from an iterative design process. The architecture is based on the reconfiguration services of the IEC 61499 standard and the service orchestration via OPC UA. We demonstrate the software architecture's compliance to the industry 4.0 requirements on an aluminum cold rolling mill plant demonstrator.