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Google’s Visual Inspection AI spots defects in manufactured goods

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Google today announced the launch of Visual Inspection AI, a new Google Cloud Platform (GCP) solution designed to help manufacturers, consumer packaged goods companies, and other businesses reduce defects during the manufacturing and inspection process. Google says it’s the first dedicated GCP service for manufacturers, representing a doubling down on the vertical.

It’s estimated that defects cost manufacturers billions of dollars every year — in fact, quality-related costs can consume 15% to 20% of sales revenue. Twenty-three percent of all unplanned downtime in manufacturing is the result of human error compared with rates as low as 9 percent in other sectors, according to a Vanson Bourne study. The $327.6 million Mars Climate Orbiter spacecraft was destroyed because of a failure to properly convert between units of measurement, and one pharma company reported a misunderstanding that resulted in an alert ticket being overridden, which cost four days on the production line at £200,000 ($253,946) per day.

Powered by GCP’s computer vision technology, Visual Inspection AI aims to automate quality assurance workflows, enabling companies to identify and correct defects before products are shipped. By identifying defects early in the manufacturing process, Visual Inspection AI can improve production throughput, increase yields, reduce rework, and slash return and repair costs, Google boldly claims.

AI-powered inspection

As Dominik Wee, GCP’s managing director of manufacturing and industrial, explains, Visual Inspection AI specifically addresses two high-level use cases in manufacturing: cosmetic defection detection and assembly inspection. Once the service is fine-tuned on images of a business’ products, it can spot potential issues in real time, optionally operating on an on-premises server while leveraging the power of the cloud for additional processing.

Visual Inspection AI competes with Amazon’s Lookout for Vision, a cloud service that analyzes images using computer vision to spot product or process defects and anomalies in manufactured goods. Announced in preview at the company’s virtual re:Invent conference in December 2020 and launched in general availability in February, Amazon claims that Lookout for Vision’s computer vision algorithms can learn to detect manufacturing and production defects including cracks, dents, incorrect colors, and irregular shapes from as few as 30 baseline images.

But while Lookout for Vision counts GE Healthcare, Basler, and Sweden-based Dafgards among its users, Google says that Renault, Foxconn, and Kyocera have chosen Visual Inspection AI to augment their quality assurance testing. Wee says that with the Visual Inspection AI, Renault is automatically identifying defects in paint finish in real time.

Moreover, Google claims that Visual Inspection AI can build models with up to 300 times fewer human-labeled images than general-purpose machine learning platforms — as few as 10. Accuracy automatically increases over time as the service is exposed to new products.

“The benefit of a dedicated solution [like Visual Inspection AI] is that it basically gives you ease of deployment and the peace of mind of being able to run it on the shop floor. It doesn’t have to run the cloud,” Wee said. “At the same time, it gives you the power of Google’s AI and analytics. What we’re basically trying to do is get the capability of AI at scale into the hands of manufacturers.”

Trend toward automation

Manufacturing is undergoing a resurgence as business owners look to modernize their factories and speed up operations. According to ABI Research, more than 4 million commercial robots will be installed in over 50,000 warehouses around the world by 2025, up from under 4,000 warehouses as of 2018. Oxford Economics anticipates 12.5 million manufacturing jobs will be automated in China, while McKinsey projects machines will take upwards of 30% of these jobs in the U.S.

Indeed, 76% of respondents to a GCP and The Harris Poll survey said that they’ve turned to “disruptive technologies” like AI, data analytics, and the cloud to help navigate the pandemic. Manufacturers told surveyors that they’ve tapped AI to optimize their supply chains including in the management, risk management, and inventory management domains. Even among firms that currently don’t use AI in their day-to-day operations, about a third believe it would make employees more efficient and be helpful for employees overall, according to GCP.

“We’re seeing a lot of more demand, and I think it’s because we’re getting to a point where AI is becoming really widespread,” Wee said. “Our fundamental strategy is to make Google’s horizontal AI capabilities and integrate them into the capabilities of the existing technology providers.”

According to a 2020 PricewaterhouseCoopers survey, companies in manufacturing expect efficiency gains over the next five years attributable to digital transformations. McKinsey’s research with the World Economic Forum puts the value creation potential of manufacturers implementing “Industry 4.0” — the automation of traditional industrial practices — at $3.7 trillion in 2025.

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Categories
AI

Amazon launches computer vision service to detect defects in manufactured products

Amazon today announced the general availability of Amazon Lookout for Vision, a cloud service that analyzes images using computer vision to spot product or process defects and anomalies in manufactured goods. Amazon says that Lookout for Vision, which is available in select Amazon Web Services (AWS) regions via the AWS console and supporting partners, is able to train an AI model using as few as 30 baseline images.

Tasks in manufacturing can be error-prone when humans are in the loop. A study from Vanson Bourne found that 23% of all unplanned downtime in manufacturing is the result of human error, compared with rates as low as 9% in other segments. The $327.6 million Mars Climate Orbiter spacecraft was destroyed because of a failure to properly convert between units of measurement. And one pharma company reported a misunderstanding that resulted in an alert ticket being overridden, which cost four days on the production line at £200,000 ($253,946) per day.

Lookout for Vision aims to combat this by injecting a bit of AI into the mix, detecting manufacturing and production defects including cracks, dents, incorrect color, and irregular shape in products from their appearance. The service can process thousands of images an hour and requires no upfront commitment or minimum fee, Amazon says. Customers pay by the hour for usage to train the model and detect anomalies or defects using the service.

After analyzing the data, Lookout for Vision reports images that differ from the baseline via the service dashboard or a real-time API. Lookout for Vision is sophisticated enough to maintain accuracy with variances in camera angle, pose, and lighting arising from changes in work environments, Amazon claims. Still customers have the ability to provide feedback on the results, whether a prediction correctly identified an anomaly. Lookout for Vision will automatically retrain the underlying model so that the service continuously improves.

Customers using Lookout for Vision include GE Healthcare, Basler, and Sweden-based Dafgards. Dafgards is using the service to automate the inspection of its production lines and detect whether pizzas, hamburgers, quiches have correct toppings. And Amazon’s own Print-On-Demand facility, which prints books on demand to fulfill customer orders, is tapping Lookout for Vision to automate and scale visual inspection at each step of book manufacturing.

“Whether a customer is placing toppings on a frozen pizza or manufacturing finely-calibrated parts for an airplane, what we’ve heard unequivocally is that guaranteeing only high-quality products reach end-users is fundamental to their business. While this may seem obvious, ensuring such quality control in industrial pipelines can in fact be very challenging,” VP of Amazon Machine Learning at AWS Swami Sivasubramanian said in a press release. “We’re excited to deliver Amazon Lookout for Vision to customers of all sizes and across all industries to help them quickly and cost effectively detect defects at scale to save time and money while maintaining the quality their consumers rely on – with no machine learning experience required.”

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