Smart factories in the era of I4.0 demand innovative solutions to automate processes, while increasing productivity and quality standards. Data capture and integration throughout the factories will help improve predictive maintenance processes, track the origin of errors, and agile adaptation to real-time demand forecast.

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Project Details

  • Date: 2018

Project Story

One of the biggest european manufacturers of home appliances needed to improve the detection process of production failures. Machine learning-driven algorythms used artificial vision to detect scratches, bumps and assembling/serigraphy defects at the end of the production line. Our solution integrates this real-time process with the development of an intelligence tracking and predicting tool.