Framing AI and robotics as solutions but prompting an honest exploration of what they can and cannot solve. AI and robotics are increasingly promoted as the next frontier for quality assurance in solar but how far can they really take us? This session takes a critical, grounded look at where AI is delivering meaningful improvements in PV system quality and where its limitations still require human expertise, better data, or a shift in approach.
From fault detection and predictive maintenance to automated inspections and performance forecasting, AI has already transformed parts of the PV lifecycle. But not all quality issues can be solved by algorithms. Incomplete datasets, misclassified failures, and emerging technologies with no historical field data challenge the current capabilities of even the most advanced AI systems.
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