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Revolutionize Automotive QA with an AI Auditor

In the automotive manufacturing sector, leveraging AI-driven quality assurance is no longer optional. It’s imperative. According to a recent report, AI-powered visual inspection systems in the automotive parts industry achieved a 95% defect detection rate while reducing labor costs by approximately 30%.
For Original Equipment Manufacturers (OEMs) and Tier suppliers simultaneously dealing with hundreds of incoming spec documents and rigorous standard compliance, this kind of leap in efficiency and accuracy is game changing. AROBS has been providing software and hardware solutions to the automotive industry for over 25 years. We expanded our services portfolio through AI-powered solutions provided by the FWF team, part of the AROBS Group.

The Client: a leading automotive OEM

Our client is a leading automotive OEM whose quality assurance team manages a complex ecosystem of supplier‑provided QA requirements. Dozens of small to large Tier 1 and Tier 2 suppliers deliver semi-formatted requirement documents that need to be assessed, mapped to industry norms, and validated against internal work instructions. Their goal was to modernise the QA requirement review process, accelerate decision‑making, and enhance compliance visibility.

The Challenge:

The client faced multiple pain points:

  • Suppliers deliver semi‑formatted QA spec sheets, and the OEM must review and approve them. Yet, there was no efficient way to determine whether the supplier’s existing processes already met or exceeded the specifications.
  • There was no systematic method to associate each requirement with the correct industry norm (e.g., International Automotive Task Force (IATF) or International Organization for Standardization (ISO) standards).
  • When a supplier’s requirement exceeds the industry norm, the OEM lacks visibility into whether existing internal work instructions or production processes fulfil that requirement.
  • Together, these gaps resulted in lengthy lead times for audits, an increased risk of oversight, and limited transparency for both the OEM and its suppliers.

The Solution

The FWF team deployed an AI‑agent‑based solution, “AI Auditor for QA Process”, designed to automate the entire review and audit chain:

  • The AI agent ingested the requirements submitted by each supplier and used built‑in domain logic (IATF + ISO) to build an Association Table that mapped each Specification correlated with Industry Norm.
  • For each requirement, the AI determined whether it met or exceeded the norm.
  • For those requirements flagged as exceeding the norm, the agent integrated with the client’s Production Management System and archived Work Instructions. It built an Audit Table that identified which requirements had existing process coverage, and which did not.
  • It then flagged the specific process documentation (work instruction, internal audit evidence) linked to each requirement, recommending whether the requirement is fulfilled or requires attention.

The Benefits

By implementing the AI Auditor solution, the client realised tangible business benefits:

  • 99% reduction in the time to go from supplier requirement intake to an audit decision (from weeks/months to minutes/hours).
  • The automated mapping to industry standards dramatically improved traceability and reduced the risk of human error.
  • The Audit Table provided clear, actionable visibility into gaps, as well as into specifications that exceed the norm but lack corresponding process documentation, enabling proactive remediation.
  • With this speed and accuracy, the OEM’s quality team shifted from reactive firefighting to proactive management, and the supplier ecosystem gained clarity on compliance expectations and process alignment.

Conclusion

Quality assurance in automotive manufacturing cannot afford delay or ambiguity. With the FWF by AROBS AI Auditor, OEMs gain traceability, speed, and certainty. Each supplier requirement is mapped, audited, and actioned automatically and accurately. If your organisation faces complex supplier-derived specifications, standard-norm mapping challenges, or inconsistent internal work instruction coverage, we can help.

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