Reducing Downtime and Enabling Real-Time Intelligence via iMEX and FactoryGPT for a U.S. Cabinet Manufacturer
A U.S. cabinet manufacturer producing 10+ million cabinets a year reported after each shift, with no standard KPIs and paper inspections. iMEX added live OEE and digital quality, and FactoryGPT detected anomalies before production was hit.
- Client
- U.S. cabinet manufacturer, 10+ million cabinets a year
- Industry
- Building products manufacturing
- Solution
- ITHENA iMEX with FactoryGPT
- Scope
- Live OEE, standard KPIs, digital inspections, anomaly detection
- Headline result
- 48% higher machine availability
Three numbers the plants moved.
Results after iMEX and FactoryGPT went live across facilities.
Increase in machine availability
Live OEE and downtime visibility got machines back running sooner.
saved per operator shift
Digital inspections and automated flows saved operators two hours each shift.
Reduction in unplanned downtime
FactoryGPT flagged throughput and cycle time anomalies before they stopped production.
Meet the organization and understand the context behind the transformation.
A leading U.S. cabinet manufacturer, producing over 10 million cabinets annually across multiple facilities for top retailers and homebuilders, faced challenges with post-shift reporting, inconsistent KPIs, manual quality records, and delayed anomaly detection. Partnering with ITHENA, the organization deployed iMEX to provide live OEE dashboards, standardized benchmarking, and digital quality workflows. FactoryGPT was added to enable natural language queries and automate corrective work orders before downtime compounded. This resulted in increased machine availability, fewer unplanned stoppages, and real-time operational intelligence across multiple facilities.
"We run 16 plants producing millions of cabinets a year, and we were still relying on end-of-shift reports and manual logs to understand what happened during the day. iMEX gave us live OEE across every facility, and FactoryGPT let our operators ask what went wrong and get an answer in seconds. We went from chasing problems after the fact to catching them before they cost us output."
— Vice President, Manufacturing Operations
Reporting after the shift was over.
OEE and downtime were only reported after the shift, and KPIs varied between facilities.
- Lacked real-time OEE and downtime visibility across production lines
- Operated without standardized KPIs, blocking consistent cross-facility benchmarking
- Relied on manual logbooks and paper inspections, slowing quality consolidation
- Failed to detect throughput and cycle time anomalies before production was impacted
- Struggled to identify equipment stoppage root causes without manual investigation
How ITHENA closed the gaps.
ITHENA deployed iMEX and FactoryGPT, moving the client from reactive reporting to proactive:
Real-Time Monitoring
Delivered persona-based OEE dashboards, providing operators live visibility into line availability, performance, and quality.
Standardized KPIs
Unified performance metrics across all facilities, enabling consistent plant comparisons and faster identification of underperforming lines
Digitized Inspections
Replaced paper checklists with structured digital workflows, ensuring consistent quality records across all production stages
Automated Flows
Enabled natural language queries on shift metrics and downtime, auto-triggering corrective work orders before losses compound
Anomaly Detection
Scanned throughput and cycle time data continuously, surfacing hidden performance losses before they impacted OEE
Downtime, seen while it happens.
An illustrative iMEX and FactoryGPT view of live OEE, downtime and anomalies across facilities. Figures other than the client's results are examples.