Background¶
In the complex landscape of the manufacturing industry, data has become one of the most valuable assets. Staying ahead of the competition requires leveraging innovative technology to unlock and transform raw data into actionable insights.
This data includes streaming and event-driven data from devices communicating via OPC-UA or MQTT, as well as upstream operational technology systems such as SCADA, MES, and quality systems, alongside business systems such as planning and supply chain management.
Our expertise¶
Aurelius Enterprise specializes in helping manufacturing companies unlock plant data, such as machine and process data, to provide real-time end-to-end insights. We combine our expertise in Data Engineering (Node-RED, Apache Kafka), Time Series Data Storage (InfluxDB), and Data Visualization (Grafana) to ingest, store, and process streaming data for monitoring, analysis, or Machine Learning training purposes.
Client use case¶
Many manufacturing companies aim to build data streaming and IoT data platforms. One of our clients, a machine manufacturing company, aims to become smarter by developing predictive maintenance models to reduce costly unscheduled downtime and integrating various systems to gather and expose data for data-driven decision-making (DDDM).
Path to becoming a Smart Factory¶
Before taking the significant step towards becoming a Smart Factory, companies need to understand the available data, improve its accessibility, and determine how to collect, store, process, transform, share, and utilize it for various use cases. To achieve this, Aurelius Enterprise has been involved in defining the business case and gathering requirements, designing the architecture, selecting appropriate solutions, and overseeing the build and deployment phases.
Accelerating data-driven transformation¶
To accelerate our clients journey toward becoming data-driven, our team of Solution Architects, Data Engineers, and Data Management Consultants developed an IoT Data Platform. Using Node-RED, we collect data from OPC-UA or MQTT, process it, enrich it with metadata, and collect it from an Apache Kafka-based data platform. The large volumes of structured and unstructured data available in Kafka are permanently stored in a time series database – InfluxDB. This data is currently used for monitoring purposes (e.g., utilizing Grafana's real-time dashboarding capabilities) and for training Machine Learning models to predict unscheduled downtime and optimize end-to-end supply chain.
Demo¶
Our demo is a simplified version of such data platforms, designed to showcase our expertise and the capabilities of our IoT Data solutions.