In today’s world, robots are becoming more and more influential. Health care, agriculture, food preparation, manufacturing and military are industries with utilization and demand of robots to boost efficiency and convenience for customer and provider. Although the demand and presence are high, the maintenance of these robots are still preventive rather than predictive. It is challenging to achieve the latter especially in the manufacturing world where the robots’ movement include high speed variations. In the market, the maintenance of the robots is done with manners utilizing statistical parameters or specific preprogrammed movements to detect if a damage is present. This needs to be handled in order to move to the predictive maintenance where the down time is only done when it is needed making it less costly and more efficient.