Concept and Implementation of a Software Architecture for Unifying Data Transfer in Automated Production Systems

The integration of smart devices into the production process results in the emer-gence of cyber-physical production systems (CPPSs) that are a key part of Indus-trie 4.0. Various sensors, actuators, Programmable Logic Controllers (PLCs), Manufacturing Execution Systems (MES) and Enterprise Resource Planning (ERP) systems produce huge amounts of data and meta data that can hardly be handled by conventional analytic methods. The main goal of this work is to de-velop an innovative architecture for handling big data from various heterogeneous sources within an automated production system (aPS) and thus enable gaining otherwise undiscovered knowledge from data analysis to support a better under-standing of the whole process, spotting possible defects in advance and increas-ing the overall equipment effectiveness (OEE). This new architecture vertically connects the production line to the analysts by using a generic data format for dealing with various types of data. The presented model is applied prototypically to a lab-scale production unit. Based on a message broker, the presented proto-type is able to process messages from different sources, using e.g. OPC UA and MQTT protocols, storing them in a database and providing them for live-analysis. Furthermore, data can be anonymized, depending on granted access rights, and can be provided to external analyzers. The prototypical implementation of the architecture is able to operate in a heterogeneous environment supporting many platforms. The prototype is stress tested with different workloads showing hardly any response in the form of longer delivery times. Thus, feasibility of the architecture and its suitability for industrial, near real-time applications can be shown.