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AI gives manufacturers an unprecedented ability to skyrocket throughput, streamline their supply chain, and scale research and development.
FREMONT, CA: Ever since the Industrial Revolution, the manufacturing sector has focused on mitigating cost by increasing operational efficiency, developing a safer work environment, and improving the customer experience, making supply chain management even more complex in ways never imagined. Artificial Intelligence (AI) seems to be the remedy and promises to redefine the manufacturing industry. Here are some key used for AI in manufacturing.
• Defect Identification
Today, many assembly lines have no systems in place to identify defects. Even those in place are basic, requiring skilled employees to build and algorithms to differentiate between functional and defective components. The majority of these systems cannot integrate new information, resulting in countless false-positives, which must be manually checked by an employee. By integrating this system with artificial intelligence and self-learning potentials, manufacturers can save countless times by significantly reducing false-positives and the hours needed for quality control.
• Quality Control
Manufacturing needs acute attention to detail, a necessity that is exacerbated in the electronics space. Quality assurance has been a manual job, demanding a highly skilled engineer to ensure that electronics and microprocessors were being manufactured correctly. Today, image processing algorithms can validate whether an item has been accurately produced. By implementing cameras at key points along the factory floor, this sorting can happen seamlessly and real-time.
• Assembly Line Integration
Today, much of the device that manufacturers use sends a massive amount of data to the cloud. This data tends to be siloed and doesn’t play well together. Getting a holistic picture of the operation needs different dashboards and an expert to make sense of it. By creating an integrated app that takes data from the Internet of things (IoT) connected equipment, manufacturers can ensure that they are getting a complete view of the operation.
• Generative Design
AI can help manufacturers design products. A designer or an engineer inputs design objectives into generative design algorithms. These algorithms then find all the possible permutations of a solution and create design alternatives. Finally, it leverages machine learning to test each iteration and enhance it.