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It is a company in northwestern Italy that operates in the industrial electronics sector and has 70 employees.
The company was facing a problem with automated visual inspection of printed circuit boards received from the subcontractor, with an average failure rate of 3.2 percent. The failure rate at the subsequent functional test was 9.8%.
To address this problem, the client enlisted the help of Widecons, which developed a dedicated Machine Learning algorithm to progressively and continuously improve visual inspection.
After four months, the average PCB failure rate under the new visual inspection increased to 6.3 percent, with a significant reduction in the functional test failure rate of 3.2 percent. After one year, it changed to 7% at the new visual inspection and 1.5% at the functional test.
In addition, with clearer failure data from visual inspection, an agreed-upon assessment with the subcontractor made it possible to increase PCB quality at the source. In addition, visual inspection at subcontractors was decentralized and in-house inspection was eliminated. The client company has also benefited from the reduction in volumes returned to the subcontractor, reduced lead times, and increased productivity and quality of PCBs and finished product.
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