Plattform
Fallstudien
A major production facility approached us toa ddress the operational issues behind a significant downtime rating. When thefacility’s management first assessed the situation, the maximum continuous runtime was a paltry 13 hours before a Cleaning-in-Place cycle was needed.
The relatively low uptime witnessed was having a seriously detrimental impact on both operational efficiency and capacity.
With the help of MontBlancAI, the team implemented a series of targeted optimizations using, among other things,AI-powered operational intelligence tools. As a result, the facilitysignificantly increased overall efficiency and capacity.
Here’s how they did it with the help of our cutting-edge operational intelligence tools.
The ultrafiltration (UF) system was crucial to the facility’s production process, so finding a viable solution was urgent. Thefacility was running Cleaning-in-Place (CIP) cycles once every 12 or 13 hours.Fouling and degradation, among other issues, were to blame.
As a result of excessive CIP cycles, the following issues were holding back the production process:
Production was being stopped at least once a day for cleaning, significantly reducing output.
Interruptions limited equipment utilization and efficiency, needlessly adding to production costs.
The short runtime restricted the ability to meet growing demand. The ultrafiltration system’s downtime was directly impacting profitability.
The team tackled the problem by creating a comprehensive optimization strategy, focusing on improvements to the UF system’s performance.
Using various operational intelligence tools and artificial intelligence for IT operations, the facility took the following steps:
Key personnel used MontBlancAI to monitor the system parameters around the clock, identifying fouling triggers along the way.
Based on the data we collated during the monitoring phase, the team optimized flow rates, pressure, and feed quality to minimize system stress.
MontBlancAI improved upstream filtration to reduce contaminants entering the UF system.
Using our tried-and-tested operational intelligence tools, the facility refined the CIP protocols to maximize cleaning efficiency while preventing overuse.
These changes were implemented with minimal disruption to existing operations, ensuring a seamless transition to a more efficient ultrafiltration process.
Following the implementation of our AI-driven optimization strategy, the production facility experienced a sudden leap in performance.
The Ultrafiltration (UF) system, previously constrained to just 13 hours of continuous operation, now achieves an impressive 22-hour runtime—a 70% increase in uptime. This dramatic improvement slashed the frequency of Cleaning-in-Place (CIP) cycles, driving down operational interruptions.
The result? A significant boost in OverallEquipment Effectiveness (OEE). More importantly, production capacity surged due to extended, stable production blocks of 21–25 hours.
While there were multiple positive takeaways to come from this project, three in particular caught the client’s eye:
Small adjustments to operating conditions and pre-treatment can significantly enhance system performance.
Monitoring and analysis were critical to identifying and addressing fouling triggers.
Reducing downtime directly translates to higher output and profitability.
The facility was able to deliver a tangibleROI for the client. The time and resources poured into the project were minimized, thanks to our operational intelligence tools.
Increase production capacity and reduce operating costs while preserving quality. Contact us today to discuss a more efficient future for your production operations.
