Towards Visualization of Manufacturing System Data Models to Support Agile Implementation

Abstract

Usage of Industry 4.0 practices or data models enabling Industry 4.0 is limited in Manufacturing Small and Medium Enterprises (SMEs). One significant obstacle hindering the uptake of such data models is the fact that they remain abstract. The current case study aims to answer two research questions a) how to develop new visualization methods for hierarchical data models for improved understanding of their use in manufacturing applications and b) how to use open access Industrial Internet of Things platform (i.e., FIWARE) to access data from manufacturing devices. Industry 4.0, RAMI4.0 and literature survey are used as research methodologies. The first section of the paper presents a framework to use FIWARE open-source platform to collect manufacturing data. At the core of this section is the implementation of FIWARE data models so that they match the machinery of an Industry 4.0 test bed. The second section focuses on visualization of the data models. For this purpose, data will be collected via mobile robot equipped with sensors for environmental condition monitoring. The results consist of verification of a practical demo case of the visualisation FIWARE data models. Further, the first guidelines for the visualization of the data models are presented. Then, the hierarchy between data models used in a manner that it will be possible to visualize the connections between the machines connected to the platform is highlighted and visualization of the metadata will be described for the functionality of the user interface.