Manufacturing
Raise first-pass yield without slowing the line, predict failures before they stop production, and align your APS with a supply base that rarely moves in straight lines — all integrated with your MES, SCADA, and ERP through OPC-UA and ISA-95 boundaries.
What holds plants and networks back
Quality control at speed is the tension every operations leader knows. Manual inspection cannot keep pace with modern cycle times, yet fully automated vision without domain grounding floods teams with false positives or misses subtle defects. A Deloitte analysis of smart factory initiatives found that manufacturers deploying AI-driven quality saw up to 35 percent reductions in defect rates — but only when models were trained on plant-specific conditions, not generic image sets.
Predictive maintenance programs stall when sensor data stays siloed in OEM-proprietary historians and PLCs, or when models alert so often that maintenance crews tune them out. Vibration, thermal, current, and pressure signals need to converge through OPC-UA or MTConnect into a single failure-risk model — ranked by criticality with enough lead time to align parts, labor, and production windows.
Production scheduling breaks when ERP promises meet shop floor reality: tool changes, operator skill matrices, and upstream material arrivals that do not match the frozen plan. Most APS modules in SAP, Oracle, or Infor optimize on capacity alone — they cannot reason about changeover sequences, shared tooling conflicts, or real-time WIP position on the floor.
Supply chain disruption is now a permanent feature of planning, not a one-off event. IATF 16949 and PPAP requirements mean automotive suppliers cannot just swap vendors. Pharma and food manufacturers face cGMP and FSMA traceability constraints. Tier-two visibility, alternate sourcing, and logistics variability need to feed the same decisions as internal capacity and OEE targets.
Where Birdeye Labs plugs in
Quality Inspection
Machine vision pipelines for surface defects, dimensional tolerance, and assembly verification — trained on your line conditions and retrained via human-in-the-loop feedback. Deployed at the edge on industrial PCs or NVIDIA Jetson, pushing structured pass/fail and defect-class data to your MES and SPC systems through OPC-UA.
Predictive Maintenance
Models that fuse vibration, thermal, current, and acoustic sensor data with CMMS work-order history and production context. Failure-window estimates ranked by asset criticality and OEE impact so maintenance crews get actionable interventions — not another wall of unranked alerts from the SCADA historian.
Production Optimization
Scheduling and sequencing that respect changeover matrices, operator skill certifications, shared tooling constraints, and real-time WIP position. Scenario modeling that lets planners compare trade-offs before locking the plan — integrated with your SAP PP, Oracle Manufacturing, or Infor CloudSuite.
Supply Chain Intelligence
Demand sensing that blends customer orders, POS sell-through, and commodity indices your category actually responds to. Supplier risk scoring across tier-one and tier-two with lead-time variability tracking — so procurement and planning act on the same numbers before disruptions hit your production schedule.
Modernize manufacturing with AI
We scope use cases against the OEE, first-pass yield, and OTIF metrics your plant and network already track — then deliver integrations that sit beside your MES, CMMS, ERP, and quality systems through OPC-UA and ISA-95 boundaries instead of replacing them overnight. If you are ready to move from pilots to production, we should talk.
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