“HYPPOS is a toolkit for building online decision support tools, with advanced material tracking capabilities, which lead to energy savings and waste reduction, while enabling improved quality and increased profitability of industrial polymer plants”
The Hyperion Predictive Production Online Software (HYPPOS) is based on the digital twin concept with application in the process manufacturing industry. The twin tracks material and quality data from the production equipment and is synchronised using live values from the production process. HYPPOS combines digital twin data with data collected from other systems, i.e., LIMS and ERP, to provide users with a unique view of the state of the production process.
Using the innovative online analytical processing capabilities of HYPPOS, visibility is provided, quality issues can be identified and tracked in real-time. This allows for corrective actions earlier in the process, leading to improved product quality and less waste.
A mathematical material tracking algorithm that uses real-time process values to track continuous movement of liquid, powder, and granular material by segmenting and characterizing material into discrete quantities.
On-demand real-time reporting
HYPPOS comes bundled with several pre-configured, built-in reports. Many more reports can be configured as per the customer’s needs and requirements, and deployed within the HYPPOS framework.
Integration with third party software
As HYPPOS stores all data in a relational DB, it can easily feed this data, in real-time, to other management reporting systems or visualisation platforms, in combination with data from other sources, e.g., financial or sales data from ERP.
Web-based & multi-user roles
HYPPOS boasts a modern web-based graphical user interface, which means that it is secure, platform-independent, and can be accessed 24/7. Users, allocated with appropriate permission rights, can collaborate easily either in one location or across various sites and geographies.
A configurable workflow module reacts to process events and data relating to batch production from initial creation through quality testing and packaging with the capability to interact with plant operators where defined processes require data, approval or other intervention.