2026
Laying the foundations
Demand drivers
Barriers to adoption of advanced and flexible manufacturing technologies
Integrated digital manufacturing and assurance data traceability
Advancing assurance certification and regulatory pathways
Challenges for circularity, remanufacture and maintenance
Assurance capabilities aligned with increasing high-value manufacturing rates and product complexity
Industry capability needs
Establish test beds to develop, integrate and validate novel inspection, measurement and test techniques and processes
Developed best practice for sharing and cyber security of certification and quality data
Integrated frameworks and maturity grids for assessment and adoption of assurance processes
Demonstration of data driven quality/fault prognosis, decision making and control
Coordinated sectorial collaboration to engage regulators and drive regulatory advancement and development of new standards
2030
Standards, skills and single sources of truth
Industry capability needs
Adoption of developed new product and process assurance standards
Establish test facilities supporting the testing of emerging products and applications
Acceptance of in-process practices as definitive and credible sources of inspection and measurement
Cross-sector transferable inspection, measurement and certification best practice
Priority industry capability needs
Accepted methods and frameworks to ensure single source of truth for assurance data
Advanced use of data and simulation across quality and certification activities
Simplified approaches, software and AI to address assurance challenges
Innovation requirements
Assurance skills pathways for technicians and certified professionals across all inspection, measurement and test activities
Cost/benefit/risk analysis framework for investment in inspection, measurement and test activity
Demonstrated integration of assurance requirements within MBD models
2035
In-process assurance and secure data sharing
Innovation requirements
Encourage adoption of secure digital sharing of assurance data among supply chains
Develop DoE programme to validate accuracy of in-process detection methods
Develop adaptive and dynamic inspection planning based on results and in-process measurement
Demonstrate credible consistency in detection of vision recognition systems
Establish secure comms traceable assurance data throughout the full model-based engineering (MBE) workflow
Process certification by analysis, reducing physical testing through analysis and in-process techniques
2040
Automated, AI-enabled certification at scale
Innovation requirements
Demonstrated secure external access and sharing of assurance data across external supply chain partners
Automating credible digital traceability of quality and certification data
AI developed towards accelerated certification pathways, automated decision making, inspection, measurement and test
Assurance for maintenance, repair and overhaul/remanufacture, repurpose, reuse and recycle