Eclipse Arrowhead continues to drive innovation in industrial automation

A lack of resources and high costs for software development have become bottlenecks that could impede industrial development, and substantial amounts of new resources will be needed to adjust to market necessities. In this impending scenario, improvements in software engineering methods and tools to obtain more efficient work processes are key to matching and maintaining the current industrial demand levels. In particular, automating current manual operations and allowing interoperability between engineering phases are critical to reduce engineering effort and time.  

Two features have been introduced to be added to Eclipse arrowhead to achieve this main goal.

Model-Based System Engineering (MBSE) represents the first feature that will automate the transition between the model design and the implementation phase. The proposed solution is implemented in the form of Eclipse IDE plugins and is based on model transformation techniques to reduce engineering time and decrease the entry barrier for new technologies. There are three main sets of plugins, (1) the Arrowhead local cloud generation including the installation of core systems, the generation of application system skeletons, and the generation of database rules; (2) the database setup; and (3) the backward validation and comparison. The validation is done in comparison with the running services available in the database and the changes in the generated code, updating the model in runtime.  Contact: Cristina Paniagua, Cristina.paniagua@ltu.se

Secondly, Eclipse Arrowhead has integrated Artificial Intelligence and Machine Learning (AI/ML) models as services within its framework, significantly advancing industrial automation. These AI/ML models are seamlessly integrated as application systems, allowing for easy management, deployment, and utilization akin to traditional components. This integration simplifies the deployment of AI/ML models, making advanced AI technologies more accessible and practical for industrial applications. Furthermore, it enables continual learning and adaptation, allowing these models to evolve and improve over time by leveraging operational data to enhance performance and accuracy. The integrated AI/ML services maintain the highest standards of security and trust, operating within the secure environment of the Arrowhead local cloud and ensuring the integrity and trustworthiness of industrial processes. Contact: Pal Varga, pvarga@tmit.bme.hu

YouTube link: https://www.youtube.com/watch?v=4nCgQ8xF1nQ&t=2012s