Researchers have developed a new framework for predicting the remaining useful life of tools in circular manufacturing settings. This system combines uncertainty-aware functional prediction with component-level fatigue assessment, using sensor data like force and torque to forecast nine functional variables. The approach also analyzes material fatigue through stress reconstruction and crack growth analysis. Tests showed high accuracy in predicting functional variables, with thermal variables being near-perfectly predicted. AI
IMPACT This framework could improve efficiency and sustainability in manufacturing by enabling better reuse of components.
RANK_REASON This is a research paper detailing a novel framework for a specific application. [lever_c_demoted from research: ic=1 ai=1.0]
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