Role-Based Programme
RB1588

AI-Powered Quality Inspection & Testing

Smarter Defect Detection, Test Analysis & Quality Control

IMAGE REQUIRED
Duration
4 Hours
Level
Awareness
Delivery
Instructor-Led
Format
Awareness Session

Programme Objectives

  • Understand how AI can support Quality Inspection and Testing across inspection planning, test-data review, defect analysis, documentation, and reporting.
  • Explore practical prompting techniques for inspection checklists, test-result analysis, defect classification, deviation summaries, and quality records.
  • Apply AI to organise inspection information, identify patterns, structure findings, and prepare quality-control outputs.
  • Identify opportunities to improve inspection consistency, testing visibility, documentation quality, and issue-detection efficiency.
  • Recognise measurement accuracy, approved specifications, traceability, calibration requirements, and human-review responsibilities when using AI.

Tools covered

Generative AI AssistantsAI-Assisted Inspection AnalysisTest Data SummarisationDocument IntelligenceSpreadsheet AnalysisDefect ClassificationInspection Checklist GenerationQuality Reporting

Who should attend

  • Quality Inspectors
  • Quality Testing Professionals
  • Quality Control Executives
  • Quality Assurance Professionals
  • Quality Engineers
  • Inspection Engineers
  • Testing Engineers
  • Quality Analysts
  • Process Quality Professionals
  • Product Quality Professionals
  • Manufacturing Quality Professionals
  • Quality Supervisors
  • Quality Management Team Leads

Prerequisites & Participant Readiness

  • Basic understanding of quality inspection, testing, or quality-control activities
  • Familiarity with specifications, test records, defects, measurements, or inspection checklists is helpful
  • Basic computer and spreadsheet skills
  • No AI or programming knowledge required
  • No previous Generative AI experience required

TOC Modules

Concepts
  • Understanding Generative AI and its relevance to inspection and testing
  • Identifying AI applications across checklist preparation, test review, defect analysis, and reporting
  • Understanding AI assistance versus inspector, tester, and quality-professional judgement
  • Recognising activities where approved specifications, calibrated instruments, and physical verification remain mandatory
Practical activities
  • Mapping common Quality Inspection and Testing activities to potential AI applications
  • Comparing a traditional inspection task with an AI-assisted approach

Scenarios

Inspection Requirement to Defect Report

Quality Specification → AI-Assisted Inspection Checklist → Inspection Results → Acceptance Check → Defects → Non-Conformance Summary

Participants use AI to organise a sample inspection requirement, review results against supplied criteria, identify potential defects, and prepare a structured non-conformance summary for professional review.

Test Results to Quality Management Summary

Test Data → AI Analysis → Pass / Fail Results → Recurring Defects → Exceptions → Priority Actions → Management Summary

Participants use AI to analyse sample testing information, identify patterns and exceptions, and prepare a concise management-ready quality summary while retaining all final inspection and disposition decisions with authorised quality professionals.

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