A manufacturing facility was struggling with filling line inefficiencies, despite seemingly stable monthly performance reports. Frequent, untracked short stops and unclear performance fluctuations were silently eroding productivity.
By leveraging MontBlancAI’s advanced production monitoring tools, the facility uncovered and addressed these issues, delivering a remarkable 12.4% increase in Overall Equipment Effectiveness (OEE) within just six weeks. This case study details the challenge, the innovative approach, and the eventual results.
The Challenge
The operations team was aware of the critical importance of the filling machine to the facility's production process. So when the team uncovered persistent and serious operational flaws, they realized that swift, decisive action was essential.
Frequent Short Stops
The initial assessment and analysis revealed that multiple brief, unrecorded interruptions were disrupting operations daily.
Unclear Performance Fluctuations
Output inconsistencies lacked clear causes, hampering optimization efforts.
A Lack of Detailed Data
Short disruptions were neither tracked nor classified, masking their impact on efficiency.
These hidden inefficiencies stifled the facility’s productivity and profitability. Only a comprehensive, data-driven solution using intelligent manufacturing tools would deliver the desired results.
The Solution
To address the filling line inefficiencies, the facility used MontBlancAI to create and deploy a comprehensive optimization strategy, focusing on improving the system’s performance. Key steps included:
PLC Data Integration
The facility seamlessly connected to the filling machine’s PLC data without interrupting existing controls to gather real-time performance insights.
Interruption Analysis
The team identified that the line rarely operated for long without short-term interruptions, revealing hidden bottlenecks that monthly reports overlooked.
Granular Data Visualization
Daily, weekly, batch, and order-level visualization and analysis were implemented, empowering the facility with actionable performance insights.
The Outcome
In just six weeks, the team—using our production optimization software—delivered a remarkable transformation for the filling machine’s performance. Put simply, our AI-powered intelligent manufacturing solution delivered a 12.4% increase in Overall Equipment Effectiveness (OEE) through significant improvements to availability, performance, and quality.
By eliminating frequent, untracked short stops, the facility stabilized operations, enabling smoother, more consistent production runs. This surge in efficiency boosted output, reduced operational costs, and unlocked new capacity.
Key Takeaways
The facility’s work with the filling machine revealed powerful insights that drove a 12.4% OEE increase in just six weeks. Three lessons stood out—for both our team and the client.
Granular Data Uncovers Hidden Issues
Our production analytics platform exposed untracked short stoppages through real-time PLC data analysis. This demonstrated that small, overlooked disruptions can significantly erode efficiency.
Actionable Insights Boost Performance
By utilizing daily, weekly, and batch-level visualization, MontBlancAI delivered precise interventions that eliminated performance inefficiencies and maximized output.
Non-Invasive Solutions Deliver Rapid ROI
Integration with existing systems minimized disruption while delivering big efficiency improvements, showcasing the value of artificial intelligence in manufacturing.
Revolutionize Your Production Line
We boosted a filling machine’s OEE by 12.4% in just six weeks, unlocking efficiency and capacity without disrupting operations.
Our powerful platform can do the same for your operation with our proven intelligent manufacturing solutions.
Let MontBlancAI’s production monitoring software transform your performance. Contact us today to explore how we can drive similar results for your facility!
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Explore Additional Success Stories
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Optimize Dairy Production
Germany is home to one of the world’s most competitive dairy industries. The small and moderately-sized dairies in the country have to take every opportunity to make their operations more efficient and productive. This is a cost-effective and reasonably feasible way to compete with the large corporations. The pursuit of efficiencies and increased capacity plays a crucial role in this process, but traditional assessment methods are costly, time-consuming, and relatively unreliable.One relatively small dairy approached us due to our reputation for powerful production process monitoring software. The brief was simple: To decide whether optimizing existing equipment or investing in new machinery was the most cost-effective way forward.
UF System Optimization
A major production facility approached us to address the operational issues behind a significant downtime rating. When the facility’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 facility significantly increased overall efficiency and capacity. Here’s how they did it with the help of our cutting-edge operational intelligence tools.
Continuous CIP Validation
Monitoring and validating Clean-in-Place (CIP) processes can be a complex, time-consuming, and costly process, particularly for relatively modest operations. However, production intelligence software powered by AI can make it significantly easier. That’s why a German dairy, processing more than two million liters of milk, turned to MontBlancAI for help. Producing high-quality milk, cream, yogurt, cheese, and butter, the dairy relies on CIP to clean and sanitize equipment and pipelines, ensuring product hygiene, quality, and safety.Was there a way to streamline and enhance the existing CIP processes? Let’s take a look.
