CASE STUDY
How a Steel Fabricator Cut Downtime 40% and Saved $10M with Predictive AI
Summary
Company: $80M steel fabricator, 400 employees.
Wrong Starting Thought: “We just need sensors to monitor equipment.”
Why That’s Wrong: Sensors alone create false alarms, conflict with existing ERP systems, and can actually increase downtime.
WhatIf Approach: Strategy-first roadmap. Step-by-step rollout → predictive maintenance → supply chain AI → scheduling AI.
Results: $2M ROI in 90 days, $10M ROI in one year, 40% less downtime.
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Company: $80M steel fabrication firm.
Problem: Unplanned equipment downtime was costing $100K per day.
Win: $10M ROI and a 40% reduction in downtime.
Transformation: Shifted from constantly reacting to machine failures to predicting and preventing them — running the plant proactively.
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Challenges:
Machines breaking mid-job, leading to emergency repairs.
Lost contracts due to missed deadlines.
High labor costs from constant firefighting.
Hidden costs: $12M annually in penalties and wasted labor.
If nothing changed: More lost contracts and damage to the company’s reputation.
If they only added tools: Just adding sensors floods the team with alerts, most of which aren’t useful, creating more work instead of less. -
$2M ROI in 90 days
$10M ROI in one year
Downtime reduced by 40%
CLIENT FEEDBACK
“We went from repairs running us to us running the plant.” – COO
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