"We are not inspecting the product; we are governing the entropy of the process itself."
Manufacturing errors rarely happen because a part is missing. They happen because the sequence, timing, or nuance of the action was wrong.
Our system answers: "What is happening and did it happen correctly?"
Traditional CV is a gatekeeper; it stops bad products from leaving. We introduce Live Action Governance. By understanding intent and progress, we intervene before the mistake is finalized.
Knowing the batch number isn't enough. You need to know exactly what happened to that specific unit.
We create a "Digital Twin" of the assembly history. Prove mathematically: "Our process was perfect." This protects from massive, blanket recalls.
Ensuring critical safety protocols, like the "Star Pattern" for bolt tightening, are followed every time. The system automatically detects the sequence and validates compliance.
Advanced activity recognition validates strict Standard Operating Procedures (SOPs). It verifies that: 1) The cleaning duration exceeds 15 seconds, 2) The correct scrubbing motion is applied (amplitude & oscillation), and 3) All required surface areas are fully covered.
Why this problem demands a solution now
| Metric | Value | Context & Implication |
|---|---|---|
| Cost of Downtime | $2.3 Million / Hour | Represents a 113% increase since 2019. Driven by inflation and JIT integration. |
| Recall Volume | 27.7 Million Vehicles | Total U.S. recalls in 2024. Indicates systemic quality control failures. |
| Recall Prevalence | 1 in 4 Vehicles | Ratio of cars on the road with open recalls, damaging brand trust. |
| Human Error Rate | ~23% of Downtime | Direct contribution of operator mistakes to line stoppages. |
| Top OEMs Affected | Ford, Tesla, Stellantis | High-volume manufacturers face the steepest challenges in maintaining consistency. |
Traditional "Machine Vision" relies on rule-based algorithms (pixel counts, contrast thresholds). It works for PCBs in black boxes. It fails catastrophically for human workers moving around a chassis.
If lighting changes (e.g., skylight opens), part rotates 5 degrees, or a hand obscures the view, rule-based systems fail. High "False Rejection Rates" cause frustrated managers to disable the system.
A camera sees if a bolt is present. It cannot understand how it was installed. It can't differentiate between a cross-thread struggle and a smooth install. It lacks semantic understanding.
Transform traceability from passive record-keeping to an active shield. Create a "Digital Thread" for every VIN with video verification of critical steps.
Automated "Andon" cord. If the VLM detects a skipped step (e.g., missed secondary latch check), it signals the PLC to stop the line or disable the tool.
Moves QC from "detection" to "prevention". Follows the 1-10-100 Rule: Defect costs $1 at station, $100 in field.
Analyze 100% of cycles without the "Hawthorne Effect" of a human with a stopwatch. Identify micro-stoppages and ergonomic issues.