Artificial Intelligence is benefiting to various industries including healthcare, education and manufacturing. But what is Artificial intelligence (AI)? In Layman language, a simulator of human intelligence, which makes the decision after analyzing various data utilizing a collection of different intelligent technologies including machine and deep learning, analytics and computer vision. The fourth industrial revolution is employing AI to enhance its overall efficiency. The technology is not only helping to reduce manufacturing cost as well as it is improving productivity and quality. Manufacturing is a capital-intensive process, and once a plant is a set-up, replacing, removing or renovating is exorbitantly expensive. New machines improve performance; reduce redundancies, while improving overall quality metrics. AI is proving an alternative route to achieve all this and at extremely competitive price points. Instead of now replacing machines, manufacturers are adding AI/ML tools to pre-inspect raw materials identify defects, perform quality evaluations, and a lot more.
Machine vision technology helps factory computers recognise objects with greater accuracy and reliability, and in many cases has replaced quality inspection performed by humans. But that's not the end of the story, because advanced automation technologies like machine vision can be further enhanced with the addition of machine learning, according to a report by technology market research firm ARC Advisory Group. Machine vision systems provide object recognition capabilities and have demonstrated their cost effectiveness in inspection, measurement, scanning and object detection in manufacturing by improving consistency, productivity and overall quality. However, an underlying limitation is that these systems are generally developed to handle a limited number of cases and they do not have the ability to train when an unexpected variation occurs, explained report author Anju Ajaykumar, analyst at ARC Advisory Group. Machine learning can help solve that problem and is already being used to build greater adaptability into machine vision systems, enabling them to understand and respond appropriately to manufacturing variations.
It is finally resonating with me that incorporating Deep Learning at the Edge has the potential to create a paradigm shift in the way robots are deployed in manufacturing operations. FANUC's aggressive move to integrated Deep Learning technologies could revolutionize the way robotic systems are deployed. When you consider how robots are deployed in manufacturing operations today, the application programs employ traditional procedural and function programming methods. But as robots increasingly rely upon vision systems to identify and locate geometric patterns on a work piece, the logic and decision making no longer has to be all pre-programmed in order to process the workpiece.
Artificial intelligence is among the most fascinating ideas of our time. It has captured the imagination of visionaries, science fiction writers, engineers and wall street analysts alike. In fact, artificial intelligence is in many ways a catalyst for the data revolution – something that has disrupted every aspect of modern life. As with all new technologies, some are faster to embrace them, and others are much slower. Is automotive manufacturing one of the faster ones or would it be among the last?
Science and technology are essential tools for innovation. In the next few years, the impact of Digital Transformation will accelerate. Internet of Things (IoT aka M2M, IIOT, IoE – though each has its specific focus) is considered the most important trend in digitization. From connected homes, cars, cities to entire industries such as healthcare, insurance, manufacturing, public sector and utilities – connected and increasingly intelligent devices are transforming entire ecosystems, and one of the components are robots. Today, in our first Robotics Q&A, Mauro Fenzi, the CEO of Comau, discusses about different types of robots that already have a huge impact on manufacturing and other industries.