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DICA Electronics deploys Pleora’s Visual Inspection System for quality improvement


May 31, 2022  by Manufacturing AUTOMATION

Pleora Technologies announced that DICA Electronics deployed its Visual Inspection System. DICA is using the system to reduce manufacturing quality escapes and gather key data from manual processes to help speed root cause analysis.

The Visual Inspection System requires just one image to start using AI, with continuous and transparent training based on operator actions to improve and speed automated decision support.

“Visual inspection is still a crucial step for many manufacturers, but human error caused by fatigue or distraction often leads to quality escapes that cost time, money and eat into profitability,” explained John Butler, vice-president of sales and marketing at Pleora Technologies.

DICA offers electronic assembly services for a wide range of industries, including industrial controls, telecom, security and digital imaging. The manufacturer uses Pleora’s Visual Inspection System to help operators detect errors, such as incorrect components and orientation, solder defects and through hole issues, for unique component types, assembly steps and custom low-run products where automated optical inspection (AOI) is too complex and expensive.

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“Pleora’s Visual Inspection System provides a ‘second set of eyes’ for our human inspectors,” said Steve Vaughan, vice-president of operations at DICA. “Human visual inspection is a key component of our manufacturing processes, and Pleora’s system helps our operators make consistent and reliable decisions to ensure we always deliver to the quality standards expected by our customers.”

The Visual Inspection System is a camera-based solution with integrated inspection and tracking and reporting apps that are trained on a manufacturer’s unique products and processes.

With one good image, inspection apps for incoming, in-process and final quality control steps automatically compare products to a “golden reference” and visually highlight differences and deviations for an operator. As the operator accepts or rejects potential errors, the AI model is transparently trained based on their decisions.

The AI model starts automatically suggesting a decision for the operator even after one inspection. Over time, the speed and accuracy of automated decision-making improve as the system continuously learns from operator preferences.

Integrated tracking and reporting apps include automated and customizable reporting tools to provide data and insight on manual tasks. Manufacturers can collect and save data on the number of suspected and confirmed defects, add operator notes on detected issues and store product images for traceability, inventory and shipment management and batch tracking.


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