Developing an AI-enabled IIoT platform -- Lessons learned from early use case validation

TL;DR

This paper presents the design and early evaluation of the IIP-Ecosphere platform, an AI-enabled IIoT system that facilitates flexible integration of AI services and standards for industrial production.

Contribution

It introduces a highly configurable low-code platform that addresses integration challenges and demonstrates its use in AI-enabled visual quality inspection.

Findings

Successful demonstration of AI-enabled visual quality inspection

Insights into integration of AI services with industrial standards

Lessons learned from early deployment and evaluation

Abstract

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.