Process Booster - AI-powered Process Control

Which key parameters need to be closely monitored? What ranges should the parameters stay within? How do I adjust my settings if they deviate? Effective process control holds the answers to all of these questions. It is the key to maintaining process health and achieving peak performance.

But conventional process control like SPC (statistical process control) can only take you so far. Because it is mostly limited to static rules for a pre-defined set of key parameters, it is often too generic and imprecise to do justice to the intricacies and dynamics of complex processes. The result is inefficient production processes that run well below their potential.

To leave the competition behind for good, you need to go a decisive step further and take your process control to the next level!

Take that step now with Process Booster: The solution utilizes raw, unlabeled process data to autonomously perform root cause analyses on any production goal or problem. The resulting insights are precisely tailored to the internal process dynamics and the needs of the targeted line. They not only expand your understanding of the process, they enable you to actively pursue the goal and eliminate the problem with real-time warnings and recommended corrective actions.

This way, Process Booster helps you to eliminate recurring disruptions, stabilize key process parameters, and improve critical KPIs. The result is a more transparent and streamlined process that simply delivers more compliant output from the same input, giving you a decisive competitive advantage.

Act now and take your process control to the next level with Process Booster!

BENEFITS

• Higher operating margin Streamlined processes, fewer disruptions, less waste and defects, more reliable quality, improved yield and performance - all these factors significantly improve OEE and operating margin.

• Extended problem-solving Autonomous root cause analysis uncovers even hard-to-find trends and relationships, helping engineers tackle and solve the toughest challenges and improve their understanding.

• Improved predictability Early warnings of problematic trends enable a shift from reactive to proactive process control, streamlining the entire manufacturing process.

• Corrective actions included Effective corrective actions are recommended to rectify any problematic trend or situation already in its early stages.

• Ready to operate in no time The system learns by itself and does not need extensive configuration upfront like classical SPC.

• Engineer-ready No data science skills required, no extensive data preparation necessary, no prior domain expertise needs to be available.