False Calls are, and have always been, a major concern for every electronics manufacturer. Based on discussions with current customers, the estimated ratio of AOI false calls ranges anywhere between 30% to 80% depending on the AOI program.
Since these false calls can’t be depended upon, manufacturers normally have an operator standing behind the machine to verify all the defects the AOI delivers – which translates to higher labor costs and a significant risk to decreasing the line’s cycle time. Needless to say, not an ideal scenario.
This is where AI, or artificial intelligence, comes in to make a stunning difference.
Using one of the IIoT.Edge’s machine learning algorithms, the application is able to review every defect flagged by the AOI and detect false calls with a high degree of confidence.
The algorithm then automatically screens out the high confidence false calls, and only sends the remaining defects to the verification operator. This in turn, dramatically reduces the amount of potential false calls the Operator needs to screen.Less time spent verifying false calls means less wasted time and labor. We’ve seen this most recently with a major EMS customer in Europe who reported a reduction of up to 60% in manual verification due to the use of this algorithm.
Additionally, by reducing manual verification, we’ve also seen an indirect impact on overall throughput, which is something all electronics manufacturers can appreciate!