AI and machine vision drive efficiency and accuracy to the factory

With so many innovations in AI and machine vision digitally transforming the manufacturing landscape, Intel’s Stephanie Grisafi and Sahar Ehsani joined To the Edge and Beyond to provide insight into exciting trends and opportunities at the forefront of this transformation.

Many manufacturers are familiar with the classic machine vision model with algorithms designed for specific products. Updates or changes to the product require the algorithm to be remodeled and relearned to adapt to a new system. Ehsani says, “But when? [it comes] to AI and machine vision, and you connect these new technologies together, the integration of the two yields a solution that is adaptable and selectable for different types and patterns of the product. AI becomes a self-learning tool in that device so that you can give [AI] the first model, and it will begin to learn and optimize itself for another condition.”

Grisafi says continuous learning is a critical benefit of using AI with machine vision in manufacturing: “As you add new data points, you train that algorithm further to deliver greater accuracy and performance. It will lead to faster decisions on the factory floor.” AI and machine vision can help make a factory environment safer through detection protocols, such as determining whether employees are wearing the correct safety equipment. Grisafi notes, “There are many great applications and benefits to adopting a machine vision solution in the factory.”

The consistency of machine vision eliminates human error by placing “eyes”. (its camera capabilities) in areas of machines that humans simply cannot control. Ehsani explains: “Machine vision removes human dependency. We have different sets of experts on the shop floor, but they have different skills. They have a different kind of vision. Machine vision can visualize things that the human eye can’t see, but the machine can can see consistently. We can use those experts [human] sources [who] are familiar with the process in the control layer rather than on the floor and dedicate their time to those repetitive tasks.”

The pandemic has cast a stark light on the reality that there is not nearly enough automation in today’s supply chains to meet growing demand. This is an area where AI and machine vision can play an important role. Ehsani says: “AI and machine vision bring automation to the supply chain, increasing efficiency and increasing accuracy in the factory. Technology enabled by machine vision solutions such as asset tracking and inventory management – ​​what goes into the warehouse and what coming out – these are the problems that machine vision could solve.”

Learn more about AI and machine vision solutions by connecting to Stephanie Grisafic and Sahar Ehsanic on LinkedIn or by visiting

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