The advent of automatic inspection in composites fabrication has led to great progress in inspection speed and quality, and generates a large quantity of inspection data, which can serve as a rich data source for closed-loop manufacturing. These advances represent only the first wave of innovation made feasible by this technology. Not only is automatic inspection capable of quickly verifying key features of each ply in a large component, it also can be leveraged to inspect a multitude of material, process and component attributes not included in current quality programs. By viewing inspection as part of a holistic quality solution, fabricators can transition to an approach in which they monitor in-process key performance indicators (KPIs) and adjust process parameters in real time to reduce non-conformance events. Artificial intelligence is a critical enabling technology, speeding the development of analysis algorithms for each attribute, and also employing inspection data for Deep Learning and continuous process improvement. This paper explores the range of attributes that automatic inspection may monitor, the method for incorporating this new level of monitoring into a holistic quality approach, and the ways in which a holistic quality program might advance the state of the art in composites fabrication.
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