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case study Transform

Smart Factory Transformation for a Leading Beverage Manufacturer

A North American beverage leader leveraged AI-powered predictive maintenance to eliminate bottlenecks, optimize production, and reduce costs.

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The Challenge

Frequent Breakdowns

Frequent Breakdowns

High Maintenance Costs

High Maintenance Costs

Limited Machine Visibility

Limited Machine Visibility

the client

A Beverage Manufacturing Giant

North America

Technology Stack

  • AI & ML
  • Digital Twins
  • Predictive Analytics
  • BI Dashboards
  • Oracle

Engagement Model

  • Technology & Digital Integration

the impact

98%

Uptime

84%

Downtime Reduction

25%

Productivity Boost

Substantial Savings

how we did it

The shift was bold.

The impact? Unmatched.

The Need & The Challenges
The CES Solution
Results & Business Impact

The Need

Traditional maintenance methods led to frequent breakdowns, rising costs, and limited machine visibility. The client needed a proactive, data-driven approach to optimize production efficiency and reduce downtime. CES introduced AI-powered predictive monitoring, turning reactive maintenance into a proactive strategy.

Challenges

  • Unplanned Downtime: Frequent machine failures disrupted production, causing missed targets.
  • High Maintenance Costs: Reactive, manual diagnostics led to unnecessary expenses.
  • Limited Machine Visibility: Lack of real-time insights resulted in delayed interventions and unexpected failures.

To eliminate operational bottlenecks, CES implemented an AI-driven machine monitoring system with real-time analytics and predictive maintenance.

  • Digital Twin Technology: Created real-time machine replicas for proactive performance tracking.
  • AI-Powered Predictive Maintenance: Analyzed sensor data to detect failures before they occurred.
  • Interactive Dashboards: Provided engineers with real-time operational insights.
  • Automated Alert System: Instant notifications for preventive action.
  • Seamless System Integration: Optimized workflows with existing maintenance tools.
  • 98% uptime achieved through predictive maintenance and early intervention.
  • 84% downtime reduction, ensuring continuous production with minimal disruptions.
  • 25% productivity surged as engineers spent less time diagnosing issues.
  • Real-time monitoring cut scrap rates from 3.6% to 0.8%,improving product quality.
  • Significant cost savings in operational and maintenance, bolstering long-term financial sustainability.
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A challenge solved. A SMART solution delivered. This was our approach for transforming bottling productivity with AI-powered predictive maintenance. Ready to scale with AI-driven smart manufacturing? Let’s make it happen—discover more at AI & ML.