[For the manufacturing industry / Free participation] AI visual inspection is not just about "detection and done" - a method to identify defect causes from inspection data and link it to process improvement.
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[For the manufacturing industry / Free participation] AI visual inspection is not just about "detecting and ending."
A method to identify defect causes from inspection data and link it to process improvement.
In manufacturing sites, there are various challenges in the inspection process, such as labor shortages, skill transfer, and variability in visual inspections.
As a response to these challenges, the use of AI visual inspection is advancing, but simply determining good and defective products with AI does not lead to process improvement.
What is important is to accumulate and analyze inspection data to clarify "when, where, and why defects are occurring."
In this seminar, we will introduce specific examples from the basics of AI visual inspection to methods for analyzing defect causes using inspection data, as well as how to improve upstream processes and prevent recurrence.
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In manufacturing sites, there are various challenges in the inspection process, such as labor shortages, skill transfer, and variability in visual inspections. While the use of AI for visual inspection is advancing as a response to these challenges, simply determining good and defective products with AI does not lead to process improvement. The key is to accumulate and analyze inspection data to clarify "when, where, and why defects are occurring." This seminar will introduce specific examples.



