5 Use Cases Of AI and ML In Manufacturing Industry


In today’s times, we can hardly sift through Twitter or open a magazine without coming across the words: artificial intelligence, automation, machines, bots, robots, etc.

The world’s top-producing factories have switched to the digitalization of their operations. The large amounts of data flow from every tool are giving organizations more information than they know what to do with.

But unfortunately, due to the absence of resources, many companies are not able to convert this information to cut down on costs and enhance efficiency. For that, Artificial Intelligence and Machine Learning come to the rescue!

AI and ML are providing manufacturers an unparalleled ability to shoot up output, improve their supply chain, and step up their research and development game.

Let’s discuss some key uses of AI and ML in manufacturing industries:

  • Defect Detection

    Presently, there is no mechanism or technology set up for various stages of assembly lines to detect flaws across the manufacturing chain.
    By inculcating AI and ML manufacturers can save endless hours by decreasing false negatives and the time needed for quality control.

  • Quality Assurance

    Quality assurance has been a job that requires a well-trained engineer to guarantee the proper manufacture of electronics and microprocessors.
    Currently, algorithms for image processing can automatically verify if an object is created perfectly. This takes place automatically and in real-time by locating cameras at key points along the plant floor.

  • Assembly Line Integration
    A significant volume of data is sent to the cloud by various types of equipment that manufacturers use.
    Manufacturers can guarantee that they get a God-like view of the process by building an optimized app that pulls data from the breadth of the IoT-connected equipment they use.
  • Assembly Line Optimization
    In addition, by layering the abundance of data into the IoT environment of Artificial Intelligence, manufacturers can create a range of automation. For example, supervisors get warnings when the equipment breaks down. The system immediately activates evacuation planning or other reorganization operations.
  • Generative Design
    AI will assist companies design products in addition to smoothening the manufacturing process. Here’s how it functions: an engineer inputs generative design algorithms for design goals. These algorithms then investigate all a solution’s conceivable permutations and produce alternatives for design. Ultimately, to validate each iteration and build on it, it uses machine learning.
    The manufacturing industry is a technically advanced field and manufacturers have been adopters of technologies and advanced digital solutions.
    So, it is no surprise that manufacturers across the globe are now investing in AI and ML technologies to empower their operations.

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