Achieve productivity excellence by turning the vast amount of data generated in your SMT production line into actionable insights. Predictive analytics solutions are based on a concept developed by the Valor Innovation team, which focuses on solving small problems, one step at a time, to reach productivity excellence. Each is an independent, dedicated solution that utilizes machine learning and artificial intelligence to improve yield, quality, and OEE, solving efficiency challenges in your production line.
Valor Predictive Analytics
Smart Manufacturing Predictive Analytics software for Electronics
Drive best-in-class production
Valor Predictive Analytics
Achieve productivity excellence by turning the vast amount of data generated in your SMT production line into actionable insights. Predictive analytics solutions are based on a concept developed by the Valor Innovation team, which focuses on solving small problems, one step at a time, to reach productivity excellence. Each is an independent, dedicated solution that utilizes machine learning and artificial intelligence to improve yield, quality, and OEE, solving efficiency challenges in your production line.
AOI SMT Machine False-Call Reduction
The Valor False-Call Reduction Predictive Analytics Solution uses AI model training based on historical AOI pass/fail information to predict with high accuracy whether each failed board has real errors or pseudo-errors, reducing manual review work by up to 60%.
Early SMT Defect Detection with Vanti
The Valor-Vanti Predictive Analytics solution collects data from test machines early in the production line and, using machine learning, predicts which units will fail the next test. Predicting faulty units earlier significantly reduces the cost of error.
Electronic Components Analytics with Cybord
The Valor-Cybord Predictive Analytics Solution dramatically reduces costs due to compromised or counterfeit and compromised components and improves product reliability. It visually inspects every placed component and uses AI and library comparisons to provide full authentic and homogenous component traceability information.
