Reducing Cost of Quality by 7% with Sub-Second CTQ Traceability

How a global radial tyre manufacturer partnered with Linecraft AI to correlate sub-second temperature profiles directly with discrete PLC machine transitions—eliminating chronic curing defects and reducing total Cost of Quality by 7%.

Customer Background & Quality Mandate

In high-performance radial tyre production, vulcanization in the curing press is the decisive manufacturing transformation. Green tyres are placed into segmented molds where high-pressure steam, hot water, and mechanical bladders bake the rubber compound at precise temperature and pressure profiles over 12 to 18 minutes.

If mold temperature dips even briefly during the initial curing phase, polymer cross-linking fails to complete uniformly, resulting in hidden structural flaws such as bead porosity, tread separation, or sidewall under-cure. The customer—a major supplier to international automotive OEMs—faced a troubling rise in downstream X-ray inspection rejections and commercial fleet warranty claims.

The Operational Challenge: The Failure of Coarse Telemetry

The customer's quality assurance team launched comprehensive investigations, but their existing industrial software infrastructure created severe analytical bottlenecks:

• 5-Minute Historian Averages: The plant's existing process historian sampled temperatures once every 5 minutes or calculated 15-minute rolling averages. A 15-second temperature dip during steam valve switching was smoothed away by the averaging algorithm, looking like a flat line on operator dashboards.
• Disconnected Machine and Process Data: Temperature sensors recorded data into one database, while machine state events (bladder inflate, mold close, cure step) lived inside the PLC. Quality engineers could not match a temperature anomaly to an exact mechanical movement or tyre serial number.
• Escalating Cost of Quality (CoQ): Scrapping a fully cured passenger or truck radial tyre wastes all raw materials, compounding energy, and labor invested across the entire factory, while warranty claims damaged the supplier's commercial OEM standing.

"When your process historian averages data over minutes, you are blind to the transient sub-second excursions that actually destroy product chemistry."

How Linecraft AI Delivered Complete Traceability

The customer selected Linecraft Ikshana to establish true end-to-end digital part genealogy. Ikshana connected directly to the curing press controllers, industrial thermocouples, and barcode laser scanners at the cell infeed.

Ikshana bridged the gap between analog process variables and discrete machine logic:

• Sub-Second Continuous Sampling: Sampling process temperature, internal bladder pressure, and dome vacuum at 100-millisecond fidelity.
• Event-Locked Traceability: Mapping analog data directly against the micro-steps of the machine cycle (e.g., Step 14: Bladder Shaping Pressure Rise).
• Individual Tyre Genealogy: Binding every millisecond of sensor telemetry to the specific unique tyre barcode, creating an immutable digital birth certificate for every unit.

Data Discovery: Isolating the Transient Thermal Anomaly

Within two weeks of streaming live telemetry into Linecraft, the root cause of the elusive curing defects was exposed on the engineering console:

Figure 1: Linecraft Ikshana sub-second thermal telemetry. The sensor curve revealed a sudden 14-second temperature excursion below critical control limits at the exact moment of bladder pre-expansion, causing localized under-curing.

Linecraft’s high-resolution diagnostic revealed:

• The 14-Second Excursion: In 4% of curing cycles on Press Line #3, temperature plunged 11°C below the lower specification limit (LSL) during the critical transition from low-pressure shaping steam to high-pressure curing steam.
• The Mechanical Root Cause: Cross-referencing PLC valve timing exposed that the primary steam proportioning valve had mechanical stiction, causing a 6-second delay in opening. Cold condensate in the bypass line was momentarily injected into the mold cavity before fresh high-pressure steam arrived.

Customer Success Interventions: Precision Quality Control

Armed with timestamped proof, the customer took decisive corrective actions across maintenance and quality:

• Steam Bypass & Valve Overhaul: Replaced the sticky steam proportioning valves with high-response pneumatic actuators and installed automatic condensate trap blow-downs ahead of the mold manifold.
• Automated In-Line Quality Interlocks: Programmed Ikshana to trigger an automated alarm and divert signal to the downstream take-away conveyor whenever any CTQ parameter breached tolerance for >3 seconds, instantly quarantining suspect tyres for destructive lab testing.
• Closed-Loop Thermal PID Tuning: Recalibrated the PLC PID loop gains to anticipate thermal drawdowns during cold mold closures.

Quantified Customer ROI: 7% Reduction in Cost of Quality

The combination of mechanical remediation and automated digital quarantine delivered immediate commercial transformation:

Key Takeaways for Quality & Operations Executives

• Average Data Is the Enemy of Quality: Quality defects are created by transient excursions, not long-term averages. High-speed process telemetry is essential for modern quality control.
• Tie Analog Variables to Machine Steps: Knowing a temperature dropped is useless without knowing which valve, motor, or cylinder was active at that exact second.
• Shift from Post-Mortem Inspection to Real-Time Containment: Catching a defect while the part is still in the machine saves thousands in downstream processing and protects your brand reputation.