AI in Quality and Manufacturing Digitalization

Engineering, quality, and supply chain teams each run on their own systems. Requirements and FMEAs live in engineering tools, control plans and audits in quality systems, and PPAPs and supplier data in yet another platform. Each silo works on its own, but there’s no digital thread connecting them. Information is re-entered, versions drift, and traceability breaks down. What engineering defines as critical doesn’t always reach the shop floor or the supplier. And lessons from problem solving rarely flow back into design.

This session explores how AI agents can support key engineering and quality processes, including:

• Generating system, subsystem, and component requirements, then cascading them into DFMEAs, DVP&Rs, PFMEAs, and control plans.
• Recommending root causes, corrective actions, and risk mitigations during problem solving and 8Ds.
• Reviewing APQP deliverables at each phase gate, along with PPAPs, audit findings, and supplier submissions, for completeness and consistency.
• Managing QMS, EMS, and integrated management system (IMS) documentation by drafting procedures, checking alignment with ISO 9001, IATF 16949, ISO 14001, and ISO 45001, and keeping documents current as processes change.

The session also explores how AI-powered machine vision can extend quality oversight on the shop floor through 100% inspection, with defect data feeding back into PFMEAs and control plans. It examines the emerging role of sensor-enabled robotics in building quality into manufacturing operations.

Alongside these capabilities, the session considers the governance and readiness requirements for AI adoption, including validating AI-generated decisions and managing automation through change control.

Key Takeaways

• How siloed engineering, quality, and supply chain systems break traceability—and how a digital thread connects them.
• How AI agents generate requirements into FMEAs, and Control plans.
• How AI automates APQP phase-gate reviews to accelerate launches and improve coverage.
• How AI recommends root causes and corrective actions to speed problem solving and 8Ds.
• How AI reviews PPAPs, audits, and supplier submissions faster and more consistently.
• How AI streamlines QMS, EMS, and IMS documentation and compliance.
• How AI machine vision enables 100% inspection and feeds defect data into FMEAs and control plans.
• Why manufacturing is moving toward sensor-enabled robotics that build quality into the process.
• Governance and readiness

Speaker

Antony John is the Vice President of Omnex Systems. He has 19 years of experience transforming technology businesses across global markets and different customer industry segments, for profitable growth. Antony also possesses strong experience working in the Information Technology, Automotive, Aerospace, Oil & Natural Gas, and Insurance industries. He currently leads the Product Development of EwQIMS, a revolutionary software solution for managing Enterprise Quality for APQP, Integrated Management Systems / QHSE, and Supplier Quality used by Fortune 500 companies, OEMs, top automotive manufacturers, and large semi-conductor organizations across the globe.