Surface roughness measurement can be challenging

In an interview with CTE Editor Alan Richter, Ira E. Friedman, precision tool education manager for The L.S. Starrett Co., Athol, Massachusetts, discussed surface roughness measurement, including the latest equipment developments, common challenges, noncontact measurement applications and profile parameters.

Ira E. Friedman is precision tool education manager for The L.S. Starrett Co. Image courtesy of L.S. Starrett

Cutting Tool Engineering: What are the latest trends and developments in surface roughness measurement equipment?

Ira E. Friedman: Users of metrology instruments, especially hand-held metrology devices, expect those instruments to have fundamental features, including the ability to communicate with smart devices. Full-color screens and graphical displays, which were rare only a few years ago, are now expected as standard features. Users also prefer USB charging, USB data storage and Bluetooth connectivity. Engineers and quality managers also now have surface measurement tools to examine numerous part parameters. With this development comes a host of quality improvements. While R_a may appear on the print, now they can examine a host of parameters, archive the data and explore ways to improve the process.

CTE: What common challenges do metrology equipment manufacturers and end users face?

Friedman: Surface roughness measurement devices are being used more and more in challenging environments, such as directly on the shop floor. This is forcing metrology manufacturers to design more robust systems while still offering the sensitivity to measure the finest details at high levels of accuracy. Surface roughness measurement equipment is evolving with new interfaces and smart technology. With the influence of smartphones and other intuitive devices, surface roughness measurement is easier, faster and less demanding to perform with a high degree of accuracy and reliability. However, the setup for measuring very small parts with a minimum radius can be difficult to achieve. This challenge is typically overcome by using a smaller cutoff value, resulting in a shorter trace. And in some cases, operators will benefit from training to interpret data.