Abstract
Volumetric throughput at the carbonatation filters at Malalane white sugar refinery was identified as a bottleneck. Scheduling filter cleaning was found to be one of the major concerns. The maximisation of the throughput via scheduling was approached by data integration and modelling. Linear regressions of the process parameters were implemented in volume space, which allows for the prediction of the remaining run duration of each filter. These predictions are continually used as an input to an algorithm that creates a schedule. The calculations are conducted in the cloud on real-time data and the predictions reported to a web-based user interface for the plant operator to use.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
