Items Tagged with 'Artificial Intelligence (AI)'

The integration of artificial intelligence (AI) into conformity assessments has gained attention as technology advances. This article outlines the advantages and drawbacks of AI in conformity assessments, reviews case studies, and underscores the necessity of human interaction in the process.

Explore how AI is revolutionizing nondestructive testing (NDT), enhancing inspection accuracy and efficiency in critical industries like aerospace and energy.

Unplanned downtime challenges manufacturers, but AI-powered predictive maintenance helps predict failures and reduce costs. A Deloitte study shows that 86% of executives view intelligent factory technologies as crucial for future competitiveness.

As manufacturing quality demands grow, the shift to artificial intelligence (AI) presents an opportunity to streamline paper-intensive processes, reduce errors, and enhance product quality through better data integration.

Optimism for 2025 is rising as logistics and supply chain sectors embrace digital transformation and automation to enhance resilience. Key trends shaping the industry are on the horizon.

The integration of automation and AI with metrology is transforming manufacturing by enhancing precision and efficiency. As Stefan Holt from MSI Viking notes, these technologies are redefining manufacturing processes and enabling adherence to stringent quality standards.

Hardness testing is essential in material sciences, particularly through hardness mapping, which generates detailed heat maps from thousands of indentations. Enhanced by AI-based evaluation, this method improves accuracy and is widely used in industries like automotive and aerospace. The article discusses the methods and future of AI-driven hardness testing.

Quality Infrastructure (QI) is vital for ensuring quality and safety through metrology, standardization, and accreditation. However, concerns arise about whether the QI has kept pace with these changes.

In a recent article for Quality called, How Generative AI Could Revolutionize Manufacturing Quality Functions, Graney said, “AI - ranging from generative, predictive, and “simple” machine learning - is poised to address the manufacturing challenges by automating data analysis, integrating multiple data sources, and providing real-time insights.

Amid the AI hype, we should ask if we're using it to achieve specific goals or just for the sake of it. The value of AI lies in its real-world application, not just as a buzzword. It's important to stay focused on our objectives and the challenges we aim to solve.