Concept for a generic modular software architecture for the integration of quality relevant data and sample implementation for a laser sintering system

Abstract

Additive manufacturing (AM) processes, such as laser sintering (LS), are complex in parameter dependencies and process flow. To be able to analyse and potentially predict the quality of the manufactured parts, the monitoring of multiple process parameters along the process chain is necessary. Currently, there are standards defined for data exchange but there is no framework to store and analyse these data or enhance a system with additional sensors. Therefore, a generic software concept is required that allows a consistent process monitoring. In this publication, a generic workflow for AM including pre- and post-processing steps is presented and relevant communication interfaces as e.g. OPC-UA, and relevant data types to be collected are identified. The concept allows the use of different communication protocols, storing and evaluating process data and by its modularity the enhancement of a system with its hardware. The stored values can be analysed by further scripts. The architecture is applicated on LS and partial aspects are prototypically implemented as well as practically validated. Therefore, a generic modular software concept, based on a hardware independent Docker based architecture, is presented. A practical feasibility test shows that machine and image data can be decentralized tapped and recorded, cloud-based analysed and web-based visualized.