Problem
The customer has a highly complex and dynamic manufacturing environment, and tracking what assets are being used for what jobs was proving difficult and time consuming. Simultaneously, there was a push for improved dashboards and interfaces for the workers on the lines to be able to see critical information about the equipment assets based on their roles in a more efficient manner. Currently, all the data from equipment assets is gathered manually (if at all), and these overheads were limiting how quickly the lines could be changed between jobs or products.
Solution
Create standardised AAS to improve data organization, interoperability and easier integration and management of assets. Set up a messaging broker, enabling targeted communication between devices and applications, facilitating efficient, scalable and real-time data. Design and implement a robust data model to facilitate seamless integration and management of IoT assets. Real-Time Data Visualisation, Historical Data Analysis, Geospatial Mapping, Alert Monitoring, KPI Monitoring and User-Specific Views.
Benefits
The customer now has a standardised and future-proofed approach to data collection from their equipment assets, storage of the data and presentation of the data to the workers based on roles. The proof-of-concept case study is being handed over to a commercial system integrator, who will carry forward the work into a larger and more complete system building on these principles.