Contemporary Generation: Artificial Intelligence Contribution to Manufacturing

The manufacturing industries’ main purpose is transforming raw materials into finished goods, usually on a large industrial scale. The creation and trading of quality manufacturing items could expose challenges that could put a great deal of strain on companies. Delivering a product that needs to meet global high-quality standards, requires: navigating through often a confusing logistical supply chain; customer driven time-to-market deadlines and maybe, if it is a new product, companies will have to cope effectively in terms of cost, design and time required to fulfil this unfamiliar project. This paper highlights the positive influence AI (Artificial Intelligence) has on the manufacturing processes. Contemporary manufacturing industries are characterized by a comparatively low level of IT spending and tend to be at the forefront in the use of IoT (Internet of Things). Predicting and reducing failures can yield significant cost savings in contemporary generation of goods. This paper presents the research on predictive maintenance in AI with the use of Unsupervised Learning (UL) algorithm, related to manufacturing industries. This is done to show how the implementation of innovative technologies is beneficial in terms of reduction in human error and the need for human availability andassistance. All of which leads to the lowering of costs by automating specific parts of the industrial processes and tasks, in this case, predictive maintenance. Innovative technology is common in the present generation, but what is still lacking is the right use when it comes to businesses and specific needs.