IJCA Vol 4 i1 2025 webmag - Flipbook - Page 43
2025 | Volume 4, Issue 1
written instructions. Other innovations include:
• A²TP: Adaptive Automated Test Platform
• A²S Lab: AI-driven sensory testing system
These platforms automate testing, analyze data
in real-time, and 昀氀ag non-conformities early in the
production process.
Impact:
• Simpli昀椀es setup and operation of advanced test
systems
• Speeds up and improves the accuracy of conformity
assessments
• Identi昀椀es production issues earlier, helping prevent
costly recalls
• Pushes metrology toward a more e昀케cient and datadriven future
Case Study 5: TDK Corporation (Japan) – Embedded
AI for Diagnostics and Compliance Monitoring
Company: TDK Corporation
Application: Real-time diagnostics and compliance
monitoring for automotive, automation, and medical
devices
Challenge:
Implementing real-time AI analytics is constrained
by limited hardware processing capacity, especially
in embedded systems. Maintaining accuracy and
reliability across diverse and dynamic operating
conditions is essential to meet strict safety and
compliance standards.
AI Solution:
In 2025, TDK introduced an AI-integrated platform at
CES that combines:
• Sensor fusion
• Predictive analytics
• Advanced materials engineering
This system uses embedded AI to enable real-time
diagnostics, compliance monitoring, and predictive
risk analysis.
Impact:
• Ensures continuous compliance in critical
applications
• Reduces the need for human-led diagnostics
• Enhances predictive maintenance capability
• Improves the reliability and e昀케ciency of
measurement systems
Today, AI is enhancing metrology by automating
complex measurement processes, improving data
analytics, and enabling real-time monitoring. Key
areas of AI application include:
43
• AI-Driven Quality Control: AI enables real-time
defect detection and quality control in industries like
automotive and healthcare. For example, AI-powered
imaging and deep learning models help identify
defects in car manufacturing before they become
critical. BMW has implemented AI-driven vision
systems to inspect assembly lines, reducing defects
and improving production e昀케ciency.
• Predictive Calibration and Self-Learning Metrology
Tools: AI can analyze past calibration data to predict
when instruments are likely to drift out of tolerance,
allowing preemptive adjustments. This approach
optimizes calibration intervals, reducing downtime
and costs. NASA utilizes AI for predictive calibration
of spacecraft instruments, ensuring precision in deepspace missions.
• AI and Digital Calibration Reports: The introduction
of AI-enabled Digital Calibration Reports streamlines
documentation and ensures traceability in compliance
with ISO 17025:2017 standards. Siemens employs
AI-driven calibration systems in its metrology labs,
reducing human error and enhancing compliance.
For an example of how AI is being integrated into
calibration documentation—including predictive
analysis, technician-AI veri昀椀cation, and blockchain
security—see Appendix A.
• Risk Analysis in Conformity Assessment: AI-driven
risk models assist in evaluating the probability of
false acceptance and false rejection in conformity
assessment, signi昀椀cantly improving decision-making
processes. The pharmaceutical industry, including
companies like P昀椀zer, leverages AI for risk-based
conformity assessments to meet FDA compliance
requirements.
• AI in Ethical Governance and Accreditation: The
International Accreditation Service (IAS) Technical
Advisory Committee is actively exploring the
implementation of AI as an advanced mechanism to
improve the e昀케ciency and accuracy of conformity
assurance, accreditation, certi昀椀cation, and testing
operations—ultimately aiming to better meet global
customer requirements.
For a list of national, regional, and international
organizations involved in conformity assessment and
accreditation, see Appendix C.
Future Developments: AI’s Expanding In昀氀uence
Looking ahead, AI is expected to become even
more deeply integrated into metrology, opening new
possibilities for precision engineering, automated
