Articles Tagged with ''quality control''

Managers in regulated industries often rely on control charts to confirm that processes are under control. That expectation is built into most quality systems, but when engineers use those charts only to document compliance, they lose a chance to study how the process behaves.

Explore some introductory, practical considerations on how to bring a visual AI to routine manual visual inspection.

Cloud-based digital color management solutions improve communication of colors between brands and suppliers. They integrate all phases of color management—from creation to production assessment—through a single, effective platform.

The future of manufacturing belongs to companies that can move faster, train smarter, and deliver consistent quality with fewer barriers to finished results. One key method of achieving this coveted four-way win is adopting portable 3D scanning and probing technologies.

Digital ecosystem provides systematic controls for work instructions, change management and data collection.

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.

AI is revolutionizing quality control in electronics manufacturing by enhancing inspection processes and reducing costs. Anna-Katrina Shedletsky emphasized the power of machine learning and deep learning to automate tasks, improve product quality, and deliver significant ROI, making quality control the perfect starting point for AI implementation.

The shift to electrification in the automotive industry demands tighter manufacturing tolerances and increased NVH testing for electric drive gears. This proactive approach helps identify potential noise issues early, enhancing quality and efficiency while reducing costs.

Quality control in manufacturing and engineering relies heavily on compression force testing to determine material strength, durability, and stability. This article highlights the key uses and equipment needed for such testing.

Time series analysis enables manufacturers to track quality data, revealing patterns, trends, and anomalies to maintain consistent production standards. This method can be applied to daily production output or hourly quality measurements.