Avril uses Braincube to quickly crunch through their production data to improve their processes.
A contextualized production data model enabled Owens Corning to experiment with variables without wasting resources. As a result, their process engineers and factory workers collaborate better during each phase of their production process.
Smurfit Kappa originally used Braincube to improve production efficiency after installing a new machine. Now they use Breaincube to further improve efficiency at factories that are already highly efficient. As one of Braincube’s longest customers, they’re still finding success a decade later.
Teams were able to focus on optimizing processes, instead of be reactive to problems.
Reductions in cost, energy, and waste were only the start for Oji Paper. With a comprehensive understanding of their most important production variables, Oji Paper’s team makes better on-the-fly decisions to stay compliant.
Cargill wanted to spend less money operating their oil boiler while maintaining steam output. Cargill’s internal analyses had yet to significantly impact the boiler’s efficiency because they couldn’t identify the optimal set points to improve boiler efficiency without decreasing steam output.
With complex product traceability and a long production cycle, Aubert & Duval needed a robust IIoT solution. They had to integrate data from different systems and facilities, monitoring progress from raw material through the final product. Braincube helped them simultaneously improve process control, quality, and sustainability.
Arjowiggins wanted to use their data in a more meaningful way to help them solve process issues. Braincube built a structured digital twin using Arjowiggins’ historical data. Now, Arjowiggins’ teams are empowered to improve processes and resolve problems on a daily basis.