Bringing Innovation to Market Faster with Optical Metrology

By October 30, 2020No Comments

The manufacturing process is an important part of the innovation cycle. Bringing new products to market requires constant communication and feedback between researchers, designers, engineers, suppliers, quality control, and more. Optical metrology, the practice of taking measurements using light, offers R&D teams more accurate, real-time data from the manufacturing process and final products. This allows businesses to optimize the innovation cycle and bring their inventions to market faster. 

Accurate Measurements

Optical metrology technology can measure not only dimensions, but also position, shape, and surface. This approach is especially useful in industries that utilize expensive, technical materials that can be damaged by contact-based measurements. The comprehensive data gathered by this technology gives R&D teams an accurate, in depth look at existing products and new samples. These insights can help focus resources and validate changes.

Real-time Feedback

Today’s optical metrology equipment is capable of measuring “millions of points per second.” This speed allows for measurements throughout the manufacturing process, rather than solely during late-stage quality control. This real-time feedback informs proactive (rather than reactive) data-backed decisions by human R&D teams and operators, as well as AI-powered inputs throughout the innovation cycle and manufacturing process. 

Connected equipment in smart manufacturing facilities also allows researchers, designers, and engineers to work remotely without sacrificing access to real-time data. This technology allows companies to manufacture globally while centralizing innovation. It’s also becoming more essential in an industry disrupted by COVID-19 restrictions. 

Automated Manufacturing

Manufacturing is embracing automation in order to compete in a global marketplace where skilled laborers are hard to find. Optical metrology is capable of measuring both quantitative and qualitative data points. Machine learning allows the equipment to not only measure manufactured parts, but also process and categorize information about defects and other important properties. These advanced features mean that optical metrology delivers more efficient quality control using less labor