Manufacturers are increasingly turning to artificial intelligence, or AI, to help automate their processes and equipment. Part of AI’s appeal stems from its ability to determine the condition of in-service equipment, which allows it to estimate when maintenance should be performed on the machinery – predictive maintenance. Artificial Intelligence for Predictive Maintenance helps companies save money by tailoring maintenance routines to each piece of equipment’s needs, rather than having them conform to a set schedule.
Using AI in manufacturing comes with many advantages that will make your processes more efficient and cost-effective.
Some businesses use AI to visually inspect parts in factories. An AI system can recognize patterns of imperfections after being trained with just a few images. Inspection systems that don’t use AI often need datasets of roughly one million images before they’re able to notice these same patterns, so the AI system is a big improvement. Currently, many factories employ hundreds of people to try to find such imperfections, which can be more efficiently managed through the effective use of AI.
AI systems can also read and follow CAD instructions, which gives them the ability to build parts without hours of preprogramming. For example, dual-armed AI robots divide tasks between their arms as needed, analogous to how humans do similar work. The robot can use its AI to decide which arm to use on a given task, eliminating the need for exhaustive preprogramming that anticipates every possible contingency.
AI for predictive maintenance can also adapt to a rapidly changing market by using algorithms that optimize supply chains. This helps companies anticipate changes in the market, allowing management to move from a reactionary mindset to a strategic one.
These are just some of the common uses of AI in predictive maintenance in manufacturing. Now, with recent technological improvements making these systems smarter than ever, manufacturers are increasingly turning to AI maintenance as a means to dodge facility downtimes by anticipating when their equipment will need repairs.