Discover how advancements in AI and automation are transforming universal testing machines, offering enhanced accuracy and safety while posing new challenges in workforce training and user experience.
ISO 9001 is leading changes in quality. Sustainability has changed from a suggestion to a requirement, and upcoming revisions will align the standard with the latest in Industry 4.0, including AI and IoT technologies.
Prepare for a transformative shift in quality management as sustainability becomes essential. Major updates are set for 2026 with ISO 9001, integrating AI into quality systems, followed by a significant overhaul of ISO 14001 in 2028.
Probes and styli are vital for smart manufacturing, evolving into advanced sensors that enhance automation and quality control. These precise tools measure parts, guide machines, and enable real-time adjustments, improving efficiency and reducing defects in CNC and robotic applications.
The use of advanced 3D scanning tools is revolutionizing quality control, design, and manufacturing, particularly with the adoption of digital standards and 3D printing. However, this shift presents challenges in maintaining consistent standards globally and across different regulations.
Fatigue testing has made significant progress in recent years, especially in test and environmental conditions. Remote monitoring has advanced with the use of AI-enabled camera systems, making it easier to integrate legacy instruments.
Automation requires precise data and careful attention to uncertainty, especially in longer processes with less human involvement, according to Chris Gordon from Optronic Laboratories.
Liquid penetrant testing is known for being relatively easy to perform, but it does requires skilled technicians to perform and interpret results accurately and consistently.
Liquid penetrant testing (LPT) is a versatile, portable, simple, and sensitive method for detecting surface defects. It can be used on a wide range of materials and is excellent at finding surface discontinuities such as defects, porosity, lack of fusion, or surface-breaking cracks.
IoT integration connects sensors and objects with each other and with applications and databases. CMMs benefit from this integration with multiple sensors integrated with metrology software and measurement databases.