Physical AI & predictive maintenance

Anonymized plant pattern: vision/robotics signals and PdM remaining-useful-life joined to orders and capacity � so failure windows reshape promises before the line stops.

Context

A process-heavy plant had rich Physical AI and CMMS predictive alerts. Customer promise dates still assumed full capacity.

Challenge

• Physical AI and PdM were dashboard orphans.
• Emerging capacity loss never hit MRP or ATP.
• Maintenance and planning fought after the break, not before.

Approach

• Joined MES, PdM, and order graph in the supply chain brain.
• Decision recommendations for plan shift and spare PO with human approval.
• RUL shown as capacity impact, not only a health score.

Outcomes (qualitative)

Capacity impact visible before the failure window. Maintenance and planning shared one decision object.