Your ERP releases production orders, but what happens on the shop floor is a black box until someone enters data hours later. We close that gap with automated machine-level tracking that connects ERP orders to actual execution in real time. Charlotte's manufacturing identity is splitting in two directions at once. Legacy energy suppliers built around Duke Energy's grid infrastructure are retooling for EV components, while Siemens Energy and ABB push turbine and switchgear production along the I-85 corridor toward full digital thread adoption. The result is a workforce fluent in heavy electrical assembly but largely unfamiliar with connected factory operations.
Charlotte's Tier 1 automotive suppliers are being forced into digital compliance by OEM mandates from BMW Spartanburg and the incoming VinFast plant, but most are still running disconnected Epicor and SAP instances with no real-time shop floor visibility.
Link ERP production orders to specific machines and operations. Track job progress at the machine level — started, in-progress, quantity complete, and quantity remaining.
Know exactly what's running, where it is, and how much is done. WIP dashboard shows all active jobs across the shop floor with live status.
Part counts from machine signals — no operator scanning or data entry. Accurate counts for scheduling, costing, and inventory transactions.
Actual vs. planned throughput by machine, product, shift, and operator. Identify bottlenecks and capacity constraints with real data.
Operator login at machines with time-on-job tracking. Actual labor hours for job costing, efficiency reporting, and capacity planning.
Automatically post production completions, scrap quantities, and labor hours back to the ERP. Eliminate end-of-shift data entry and the errors that come with it.
Map your production workflow from order release through each operation to completion. Identify the data points that matter for tracking, costing, and scheduling.
Connect machines to capture cycle-complete signals, part counts, and job status. Configure operator interfaces for job selection and reason codes.
Build the bi-directional integration between shop floor and ERP — pull production orders down, push completions and labor back up.
Deploy real-time production dashboards for supervisors, planners, and management. Configure alerts for late jobs, bottlenecks, and quality holds.
Refine tracking based on real usage — adjust workflows, add data points, and optimize ERP writeback rules based on operational feedback.
Production Tracking for Charlotte automotive operations - configured around local workflows, data ownership, and implementation governance.
Production Tracking for Charlotte energy infrastructure operations - configured around local workflows, data ownership, and implementation governance.
Production Tracking for Charlotte aerospace & defense operations - configured around local workflows, data ownership, and implementation governance.
Production Tracking for Charlotte food & beverage operations - configured around local workflows, data ownership, and implementation governance.
Production Tracking for Charlotte financial services operations - configured around local workflows, data ownership, and implementation governance.
Production Tracking for Charlotte healthcare & medical operations - configured around local workflows, data ownership, and implementation governance.
For many mid-market manufacturers, production tracking with IoT covers what they actually use an MES for — job tracking, WIP visibility, and production reporting. If you need full MES capabilities (routing enforcement, quality gates, genealogy), we can implement that too.
Operators use a touchscreen or tablet at the machine to select jobs, log downtime reasons, and enter reject counts. The system is designed to be faster than the paper traveler it replaces — typically under 10 seconds per interaction.
Yes. We integrate with existing barcode and RFID systems. Machine-level tracking supplements scanning with automatic cycle data that scanners can't capture.
We integrate production tracking with SAP, Epicor, Infor, Microsoft Dynamics, NetSuite, Odoo, and custom ERP systems. The integration writes completions, labor, and scrap directly to your ERP production orders.
Most manufacturers are still running workflows that require a person to touch every exception, every order, every routing decision. AI agents eliminate that bottleneck — not by replacing your people, but by handling the work that was always below their pay grade.
Most manufacturers forecast demand with spreadsheets, gut feel, and last year's numbers adjusted by 5%. ML models trained on your actual order history, seasonality patterns, and market signals replace guesswork with predictions your planning team can act on.
Odoo Maintenance captures work orders, failure reasons, repair times, and equipment history. We build AI models on top of that data to identify failure patterns and recommend maintenance windows before breakdowns occur — no new hardware, no IoT infrastructure required.
Odoo Quality captures inspection results, non-conformances, scrap reasons, and lot traceability across every production order. We build AI models on top of that data to surface defect patterns, predict quality risk, and trigger alerts before scrap accumulates — no cameras, no hardware.
Most manufacturers price by cost-plus formula or by whatever the sales rep negotiated last time. AI pricing models factor in material costs, competitive positioning, customer segment, order size, inventory position, and market conditions — governed by business rules so every price stays within approved boundaries.
When an order hits your system, someone decides which warehouse ships it — usually based on habit, proximity, or whoever answered the phone. AI order routing makes that decision in real time, optimizing across inventory availability, shipping cost, delivery speed, and warehouse workload.
Manufacturers still process thousands of POs, invoices, RFQs, spec sheets, and BOLs manually — reading PDFs, retyping data into the ERP, and fixing the errors that come with it. Document intelligence extracts structured data from unstructured documents automatically, with validation rules that catch errors before they enter your systems.
Your dealers call or email to check stock before placing orders because they can't see what's available. We give them live ATP visibility across all your warehouses — available, allocated, in-transit, and expected replenishment dates — straight from your ERP and WMS.
We govern cloud migration in phases — every dependency mapped, every workload sequenced, every cutover window defined. Zero-downtime migration for manufacturers who can't afford an outage.
Most manufacturing AI projects die in the pilot phase. We deploy AI that integrates into your actual workflows -- demand forecasting, predictive maintenance, pricing optimization, and intelligent routing -- governed by operational data contracts.
Your demand planning process runs on last year\u2019s sales adjusted by a gut-feel percentage. ML models trained on your actual order history, seasonal patterns, and market signals produce forecasts that are measurably more accurate \u2014 and they improve automatically as more data accumulates.
Your legacy system holds critical data that modern applications need -- but it has no APIs, no webhooks, and no modern integration points. We build a REST/GraphQL API layer on top of your legacy system so new applications can access data without touching the core.
Metrotechs starts with the operating questions: which records are trusted, which workflows are manual, which systems own each decision, and where AI can safely improve throughput.
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