In June 2021, Google enriched its Google Cloud Platform with Visual Inspection AI, an artificial intelligence (AI)-driven, purpose-built solution designed to quickly and accurately detect defects and errors in a variety of production pipelines.
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It is a continuation of Google’s previous efforts to capitalize on the manufacturing industry, which the company has recognized as one of the key target industries for its growth. Strong demand for improvements comes especially from high-tech industries, which are wasting resources and money trying to reduce faults and errors in the production cycle.
Some of these companies are already using machine-learning solutions, including Google’s AutoML, to tackle this problem, but visual inspection proved to be an especially demanding task with much potential for improvement. Google published some of the results from its studies, focusing on the electronics industry, automakers, and consumer packaged-goods manufacturers, citing potential savings in production from tens of millions, to even hundreds of millions, of dollars yearly.
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Comments
What are the true cost of implment such AI
Wonder why the 14X ROI for $55 Million, 9X for $23 Million and 10X for $50 Million needed annually totaling $11.4 million to support this is not detailed more. The example shown is possible expenditures and costs, but not actual. If these combined companies are loosing $128 million a year they would not be in business long. Great presentation, but don't feel the number aren't realistic and truly represent real world costs and defects currently happening in today Manufacturing processes and methods.
Incoming Inspection.
I do not see any reason why this form of visual inspection can not be used for incoming inspections of items that require a visual inspection.
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