CNC motor failures in large fabrication units are periodic due to high heat and unremitting tasks. Such problems are addressed using sophisticated Industrial Internet of Things (IIoT) devices and controllers. This chapter introduces an Offloading Control Scheme (OCS) using a deep learning (DL) paradigm for identifying CNC motor failures. The identified failures are reduced using modified operation cycles and control offloading based on completion/failure intervals. The learning paradigm identifies the failing and incomplete intervals across various allocated tasks and the motor running time. Depending on the interruptions between successive intervals and incompleteness, the offloading recommendations are provided. These recommendations are validated using learning interrupts for identifying shared/offloaded controls. Considering the completion intervals, the training is separated for the successive motor failure reduction from different motor operation cycles.