Manufacturing

Predictive Maintenance

for Industrial Equipment

Key Results

35%
Less
Downtime
42%
Reduction
Maintenance Costs
99.2%
Uptime
Achieved

The Challenge

A manufacturing company with $500M+ equipment portfolio experienced unexpected failures causing production delays and safety concerns.

Pain Points

  • 18% unplanned downtime
  • $3.2M annual emergency repairs
  • Safety incidents from equipment failures
  • Reactive maintenance culture

The Solution

We implemented a predictive maintenance platform:

1
Sensor integration

IoT connectivity across 200+ critical assets

2
Failure prediction

ML models detecting anomalies 2-4 weeks ahead

3
Work order automation

Automatic scheduling based on predictions

Timeline: 16 weeks including sensor deployment

The Results

Before

  • 18% unplanned downtime
  • $3.2M emergency repairs
  • Reactive maintenance
  • Safety concerns

After

  • 11.7% unplanned downtime
  • $1.9M emergency repairs
  • Predictive approach
  • Zero incidents

"We went from fighting fires to preventing them. The safety improvements alone justified the investment."

Plant Director

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