Researchers at the Department of Energy’s Oak Ridge National Laboratory have developed an on-machine tool condition monitoring system designed to detect wear in cutting tools used in machining. The system uses a flexible tactile sensor that presses against a tool’s cutting edge to capture detailed surface information. As the sensor conforms to the shape of the tool, it records fine features of the cutting edge that can indicate wear or damage. Computer algorithms then analyze the images in real time to assess tool condition.
Machining relies on the controlled removal of material to form parts, and tool condition can affect productivity, part quality and process stability. Cutting tools wear gradually during use, which can lead to diminished part quality or tool failure. To reduce those risks, manufacturers may replace tools before the end of their useful life, increasing tooling costs and the frequency of tool changes.
ORNL said the monitoring system is intended to provide faster and more consistent information about tool wear than approaches affected by sensor noise or changing imaging conditions. The system can deliver wear measurements in seconds and achieved 98 percent accuracy, according to the laboratory. Because the tactile method is not dependent on lighting conditions, the researchers said it could be integrated into automated manufacturing environments.
“This innovation bridges the gap between accurate sensing and decision-making on the factory floor,” said Ritin Mathews, lead researcher on the project. “It gives manufacturers a clear picture of tool health, so they can plan operations with confidence and improve efficiency.”
The technology is aimed at helping manufacturers determine when tools should be replaced, rather than relying on estimates or fixed replacement schedules. ORNL said the approach could reduce disruptions from tool failures and lower labor costs linked to corrective maintenance.
“By integrating this tactile sensor, manufacturers can reduce disruptions caused by tool failures and minimize labor costs tied to corrective maintenance,” Mathews said.
The system may be relevant for production involving high-value components made from difficult-to-machine materials, including titanium alloys and nickel-based superalloys. ORNL said the work is described in the journal Wear.
“This system delivers proactive analysis of tool wear progression, enabling manufacturers to detect and address potential issues before they compromise the machining of critical components,” said Chris Tyler, ORNL’s group leader for Advanced Machining and Machine Tools Research.
Other ORNL researchers involved in the project include Greg Corson, Josh Harbin and Scott Smith. The project is supported by the U.S. Department of War’s Industrial Base Analysis and Sustainment Program. The research was conducted at the Manufacturing Demonstration Facility, which is supported by the Department of Energy’s Advanced Materials and Manufacturing Technologies Office.
