For a broader adoption of AI in industrial production, adequate infrastructure capabilities are crucial. This includes easing the integration of AI with industrial devices, support for distributed deployment, monitoring, and consistent system configuration. Existing IIoT platforms still lack required capabilities to flexibly integrate reusable AI services and relevant standards such as Asset Administration Shells or OPC UA in an open, ecosystem-based manner. This is exactly what our next level Intelligent Industrial Production Ecosphere (IIP-Ecosphere) platform addresses, employing a highly configurable low-code based approach. In this paper, we introduce the design of this platform and discuss an early evaluation in terms of a demonstrator for AI-enabled visual quality inspection. This is complemented by insights and lessons learned during this early evaluation activity.
翻译:为了在工业生产中更广泛地采用AI, 充分的基础设施能力至关重要,这包括放宽AI与工业装置的整合,支持分布式部署、监测和一致的系统配置。现有的IIOT平台仍然缺乏以开放、基于生态系统的方式灵活整合可再利用的AI服务和相关标准(如资产管理壳牌或OPCUA)的能力。这正是我们下一个水平的智能工业生产电圈(IIP-Economic)平台地址,采用了高度可配置的低代码方法。我们在本文件中介绍了该平台的设计,并讨论了以一个演示器来进行基于AI的视觉质量检查,这得到了早期评估活动中的深刻见解和经验教训的补充。