The manufacturing industry of the future requires innovative approaches to optimize operational efficiency and adaptability. Integrating context-awareness into workflow management systems has emerged ...as a promising avenue to enhance efficiency in modern manufacturing processes. This research presents an innovative context-aware workflow management architecture designed to address industry-related challenges and overcome current limitations in the state-of-the-art. The architecture leverages Industry 4.0 standards for asset representation and workflow notation while incorporating a Context Analyzer component for real-time context interpretation. The effectiveness of the proposed solution is demonstrated in a real-world manufacturing setting, specifically in the scenario of collecting work order materials using the Robot Operating System (ROS) technology for robot navigation. The evaluation showcases improvements in task completion rate, resource utilization, and task completion time. These outcomes exemplify the potential benefits of incorporating context-awareness into manufacturing workflows, providing insights for further improvements. Contributions include advancing the understanding of context-aware workflow management, a review of the challenges that cap its adoption in the manufacturing domain, a qualitative comparison of similar approaches, practical implementation of the proposed architecture, evaluation of the context-aware component, and provision of the source code and datasets to the community for future advancement and reproducibility.
•Advancing standardization of manufacturing processes with BPMN and AAS integration.•Enhancing manufacturing efficiency through context-aware workflow management.•ROS-based robots in a real-world manufacturing case study.•The proposed solution improved task completion rate, time, and energy saving.
Microservice Architectures have increasingly become popular in Industry 4.0 as they allow heterogeneous systems to interact, reduce the complexity in the management of individual components, and ...support distributed deployments. The integration of those distributed services into orchestrated production processes is performed by workflow managers. Next generation workflow managers must overcome a number of challenges when operating in microservice architectures and IoT environments. To overcome these challenges (heterogeneity, high dynamism, edge deployment or scalability), we propose a workflow manager alternative built in Node-RED. Node-RED provides instruments for the development of IoT systems and leverages the edge computing paradigm. This solution is deployable in embedded systems, is able to load and execute business processes by means of BPMN recipes and enables the integration of other frameworks and architectures.
The establishment of collaborative AI pipelines, in which multiple organizations share their data and models, is often complicated by lengthy data governance processes and legal clarifications. Data ...sovereignty solutions, which ensure data is being used under agreed terms and conditions, are promising to overcome these problems. However, there is limited research on their applicability in AI pipelines. In this study, we extended an existing AI pipeline at Mondragon Corporation, in which sensor data is collected and subsequently forwarded to a data quality service provider with a data sovereignty component. By systematically reflecting and generalizing our experiences during the twelve-month action research project, we formulated ten lessons learned, four benefits, and three barriers to data-sovereign AI pipelines that can inform further research and custom implementations. Our results show that a data sovereignty component can help reduce existing barriers and increase the success of collaborative data science initiatives. CCS CONCEPTS * Security and privacy \rightarrow Privacy protections; * Software and its engineering \rightarrow Data flow architectures.
This paper presents an industrial scenario that simulates a Manufacturing as a Service system for the execution of remote production orders built upon the implementation of emerging Asset ...Administration Shell (AAS) capabilities and International Data Space connectors. Static and dynamic information from industrial assets (presses and laser cutting machines) are modelled with new AAS submodels and the result is stored in an AAS manager/registration system. A manufacturing orchestrator discovers assets through the registry and completes production orders. The AAS registry allows the selection of assets with capabilities to perform tasks and also shares the AAS catalogue available in the system. The catalogue is shared with external parties through Data Space Connectors. Third party companies can launch manufacturing orders remotely using the same connectors. The paper validates the implementation of AAS components and IDS connectors in a manufacturing context where remote production orders can be securely activated.
