CASE STUDY

How Precision Auto Components Achieved 99.8% Quality Pass Rate

A case study detailing how digital QC checklists and automatic stock quarantines helped eliminate defective parts from loading bays.

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Precision Auto Components manufactures high-tolerance mechanical linkages for global automotive suppliers. Operating with high volumes and slim margins, they faced strict OEM penalties for defective pieces. With manual inspection cards, defects were often logged too late—leading to scrap claims and wasted floor hours.

The Challenge of Late Rejection Alerts

Under their old paper inspection process, QC checkers filled out pass/fail checklists at the end of the shift. By the time a supervisor reviewed the logs, the machine had produced hundreds of defective parts. There was no direct way to lock inventory or quarantine suspect batches immediately.

"Tolerances in automotive parts leave zero room for error. A single defective lot shipped to an OEM customer can ruin a supplier relationship."

Solution Part 1: Tablet Inspection Forms

Precision Auto Components deployed ATIITHI software directly at their final inspection stations. Using rugged floor tablets, QC checkers log key measurements directly onto checksheet forms. The system auto-calculates if the parts meet recipe specifications, highlighting out-of-spec dimensions in red instantly.

Solution Part 2: Automatic Stock Quarantine

If a batch fails inspection, ATIITHI automatically changes the stock category to Quarantined in the warehouse ledger. This prevents dispatchers from scanning the boxes for outbound delivery challans, removing the risk of shipping defective parts. Supervisors receive instant alerts with specific defect reason codes to fix the machine setup.

The Results

Within two months of launching ATIITHI’s QC module, Precision Auto Components achieved:

  • 99.8% First-Pass Yield: Line adjustments are made immediately when tolerance checks drift.
  • Zero OEM Rejection Claims: Automatic quarantine blocks bad parts from reaching loading bays.
  • Defect Analytics: Managers track reject trends per machine and shift to prioritize operator training.

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