The word "artificial intelligence" strikes fear on everybody's mind and there is a valid reason for that. AI which is the short form of artificial intelligence could be your enemy as it could displace your job. Manufacturers and service providers love it because they could get their job done with less man power. And who wouldn't want? Less cost and less headache and you could get your line run twenty four hours without the worry of human demands.
But we are also aware that AI has brought many benefits not only to manufacturing but also services. Artificial Intelligence also brings to the manufacturing table its capability to open up completely new avenues for business, especially with its new capability of self-learning. With the advantage of predictive maintenance, it has become a very sought-after use for manufacturers to move a notch up in efficiency. Predictive Maintenance uses designed algorithms to predict the next failure of a system and then alerts personnel to perform focused maintenance procedures to prevent the failure, just in time to prevent unnecessary down time. In today's scenario, AI is used to deploy sound sensing to predict some occurrences that are not right.
Manufacturers can now engage Generative Design to also make defined design brief as input, designers and engineers can make use of an AI algorithm to explore all the possible configurations of a solution. The set of solutions generated by the algorithm can then be tested using Machine Learning and Digital Twining. It is now possible to test whether a thing works before it is made.
AI, together with Additive Manufacturing is today employed to assist in catering to mass customisation. Manufacturing, either big or small is able to take individual orders and supplying it in the fastest of time. AI algorithms are also used to optimize the supply chain of manufacturing operations and when coupled with big data analytics is able to forestall supply setbacks in remote places.
AI is now deployed to take an overall view of whole processes to focus on areas of inefficiencies in terms of energy use and production outputs. As production disturbances do occur along the manufacturing chain, AI is deployed to sense pressure deviations in pumps, lubricant issues, leaking valves and even increasing bearing heating.