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About

Massimo Sorli is a mechanical engineering researcher whose career spans over three decades, with expertise encompassing robotics, parallel mechanisms, force measurement systems, and prognostics and health management (PHM) for industrial and collaborative robots. His early work in the 1990s laid important groundwork in robotic force and moment measurement systems and the kinematics of parallel robots, including the development of the Turin Parallel Robot (TuPaMan), contributions that continue to attract scholarly attention with citations reaching into the forties. In more recent years, Sorli has pivoted toward the reliability and condition monitoring of industrial manipulators, producing influential research on harmonic drive gear failures — among his most cited recent works with 47 citations — and dynamic parameter identification under varying thermal and mounting conditions. His 2023 multibody modeling work for collaborative robots directly supports advanced PHM applications, reflecting a commitment to bridging theoretical modeling with real-world industrial demands. Sorli's investigations into strain wave gear wear and comprehensive FMECA analyses of harmonic drives demonstrate a rigorous, systems-level approach to robot dependability. Collectively accumulating over 230 citations, his body of work makes him a valuable reference point for researchers and engineers seeking to improve robotic system reliability, maintenance strategies, and digital modeling fidelity in modern manufacturing environments.