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Using AI to Control Quality During Production

Using Ai To Control Quality During Production

Using AI to Control Quality During Production

Reduces Costs Eigen Innovations uses Intel technology to assist companies

in identifying flaws early on and maintaining product quality.

Few things are more annoying than expecting a much-anticipated package and discovering it is damaged. A business needs to manufacture accurately and provide customers with high-quality products, whether it is selling oven doors or auto parts.

Based in New Brunswick, Canada, Eigen Innovations is an AI software startup that helps manufacturers make flawless items in the factory, guaranteeing that consumers obtain high-quality products. Eigen increases customer pleasure while saving manufacturers time and money with the use of Intel technology.


Chief sales officer of Eigen Innovations Jon Weiss says that his company’s automated inspection solutions assist producers in locating unseen flaws on their manufacturing lines.
Early problem detection and resolution increases process effectiveness and reduces costs, enabling producers to guarantee that the best product is produced each and every time. Eigen’s OneView AI platform is used to assess each part on the production line for flaws, instead of randomly selecting samples for quality testing.

Superiority is supreme.


Production line defects are expensive and inefficient. In a world driven by consumerism and rising product prices, businesses need to take production quality into account. According to Weiss, the entire cost of producing subpar goods qualifies as the cost of quality.

According to Weiss, “manufacturing companies usually have extremely narrow profit margins, but many of them are unaware of their quality cost.” He claims that quality “can cost a manufacturer up to a whopping 40% of revenue” when all is said and done.

However, Weiss points out that it is quite challenging to find flaws. Sample testing is a common practice used by many businesses, in which products are routinely taken off the assembly line to look for issues. It’s challenging to have faith in things that weren’t inspected, though, because very few products undergo testing.


This is when Eigen enters the picture. Eigen’s solutions inspect every part, on every line, in every factory, in contrast to standard quality testing. Manufacturers have access to information and insights that enable them to make decisions and enhancements in real time, ultimately lowering the cost of quality and increasing revenue.

A fault can be found in real time, as opposed to after hundreds or thousands of pieces have already passed through the line. Which parts are impacted, precisely where the issue is, and what went wrong will all be known to the manufacturer. Eigen’s OneView software can even initiate a signal that instructs a robot to remove a product for further testing or pauses the machine autonomously. Better yet, AI models are always analyzing photos from the production line and learning in order to prevent errors in the future.

Ultimately, the cloud capabilities are what customers find the most useful. “Customers have instant access to enterprise-wide improved inspections,” Weiss says. “And once the customer is happy with an inspection model’s level of accuracy, they can do a one-touch deployment across all machines with Eigen’s inspection solution.”


So what would normally be a manual, time-intensive process – including downtime on the factory floor for installation – can now be done with the click of a button.

Happy Customers for the Win


Southern Fabricators, a North Carolina-based contract manufacturer specializing in metal fabrication, is an Eigen customer. Known for creating complex product assemblies like components for farming equipment and forklift frames, Southern Fabricators produces hundreds, sometimes thousands, of pieces every day, with each piece made up of dozens of parts that need precise welds.

Here’s how OneView works for Southern Fabricators: When sensors see a problem on a weld and AI confirms the concern, OneView alerts technicians to the potential defect. It will show what happened, with a dashboard of variations in fuse times, temperatures and other relevant metrics to identify the root cause of the issue. The AI models also look at the thermal imagery and determine whether it’s a good or bad weld.


Every step of the inspection process is catalogued, providing full traceability down to individual serial numbers. Weiss explains that this full traceability helps mitigate recalls.
However, if a recall is needed, the factory can identify which set of products had an issue and only recall the affected products.

Rocky Carpenter, plant manager at Southern Fabricators, says the company has a six- to eight-week lead time on orders, so it’s critical to be agile and swift. The business needs as much predictability as possible, especially with razor-thin margins and long lead times. With the help of Eigen’s solution, Southern Fabricators has saved money (Eigen’s technology paid for itself within six months) and reduced rejects on the shop floor.

Weiss says Eigen’s customers are looking for performance and access to real-time data. And Eigen was tasked with finding a solution that could withstand industrial environments full of harsh tools like high-heat welders.


When exploring options, graphics processing units were ruled out due to debris and heat concerns.
In comes the Intel central processing unit (CPU), with its low latency and speedy performance. In the testing phase, Eigen deployed various Intel® Core™ CPUs and the OpenVINO™ toolkit and immediately saw a significant jump in performance.

Flexibility is Key


Weiss says what drew Eigen to Intel was a similar approach to flexibility and choice for customers.
Eigen wants to give customers “the widest range of deployment options” and that’s made possible by using Intel and its OpenVINO edge technology. He explains that Eigen’s deployment flexibility has ultimately become one of its key differentiators and a strong value-add for its customers. Eigen’s hardware-agnostic approach lets customers choose the hardware that works best for them and seamlessly feeds data into one dashboard.

Another advantage of OpenVINO? Horsepower. Weiss says the speed of OpenVINO is unmatched. He gives an example of a customer that produces specialty paper. In just eight seconds, machinery can build up residue, causing $120,000 worth of damage. Using OpenVINO, “the customer is able to assess, analyze and act within one second, ensuring there is no equipment failure on the line.


A Competitive Edge


What separates Eigen from other AI software companies is its focus on manufacturing.
“We live and breathe manufacturing production environments,” says Weiss. “That’s all we do. We only do inline quality inspection in factories.”

Eigen also employs thermal applications, using cameras to help manufacturers find defects that the human eye can’t see — like its consideration of the quality of a weld. The company’s OneView-managed solutions offer the most comprehensive thermal inspections on the market.


Eigen’s solution is aimed at “simplifying the path of AI adoption without the need for data scientists or writing code,” says Weiss. He explains that Eigen’s easy-to-use technology empowers technicians to resolve potential issues quickly and train AI models at the touch of a finger.


Despite headlines claiming artificial intelligence is replacing people in the workforce, the reality is that many factories are struggling to fill jobs. “If you have any process that is overly dirty, dangerous or dull, it should not be done by humans. It should be automated,” says Weiss. “Let’s get those people doing higher value, higher impact tasks.”

 

 

 


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