Predictive Three-Dimensional Printing of Spare Parts with Internet of Things.

This article focuses on optimizing the integration of the Internet of Things (IoT) and three-dimensional printing (3DP) within Industry 4.0 to improve spare parts supply management. It develops an analytical framework modeling an intelligent system where multiple machines equipped with embedded sensors are connected via IoT to a capacitated 3D printer supplying critical parts. The study finds that rather than enabling pure on-demand printing, the key benefit lies in predictive printing policies—either predictive print on demand or predictive print to stock—determined by system parameters such as printing speed and inventory costs. The research introduces benchmark systems to isolate the value of IoT, showing that IoT significantly reduces costs primarily through advance information from embedded sensors, while real-time information fusion adds additional but smaller benefits. Numerical experiments reveal that IoT’s value does not automatically scale with system size unless matched by adequate 3DP capacity, providing practical insights for investment and scheduling decisions in spare parts management and potential applications like bioprinting.