Qcify Inc.

Antoon De Cleen

Raf Peeters

Pieter Ieven

Ruben Praets

Pieter Boogaerts

Jef De Busser

Simon Kerkhofs

A process includes receiving a target quality value, receiving a measured quality value, receiving a source quality value, and sending a source control instruction. The source control instruction is based at least in part on the target quality value, the measured quality value, and the source quality value. The target quality value, the measured quality value, the source quality value, and the source control instruction are communicated via the communication port. The measured quality value is generated by an inspection device configured to inspect a sample. The source quality value is associated with a quality level of a first group of samples. The target quality value indicates a desired quality value of an output group of samples. The source control instruction causes a source selecting device to select one of a plurality of groups of samples, each group having identified quality characteristics.

Product target quality control system

A process includes receiving a target quality value, receiving a measured quality value, and sending an inspection control instruction. The inspection control instruction is based at least in part on the target quality value and the measured quality value. The measured quality value is generated by a product inspector configured to inspect a sample before being sorted and may also include data generated by an output product inspector configured to inspect a sample after passing a sorting phase. The target quality value indicates a desired quality value of an output group of samples. The inspection control instruction controls the method of inspection performed by the product inspector. The measured quality values are received by a computing device, which in turn outputs the inspection control instruction to a product inspector.

Product target quality control system with intelligent sorting

A method includes collecting measurement data of a sample, determining a confidence value associated with the measurement data, determining if the confidence value is less than a confidence threshold value, and causing the measurement data to be stored in a memory device if the confidence value is less than the confidence threshold value. The method further includes utilizing the measurement data for training of a machine learning system, thereby updating the operation of the machine learning system. The measurement data is measured by an inspection device located at a first location. In one example, the measurement data is a captured image captured by an optical inspector. The confidence value associated with the captured image represents the confidence of the machine learning system regarding what is displayed in the captured image.

Automated inspection data collection for machine learning applications

A method includes the steps collecting measurement data of a sample utilizing an adaptable inspection unit or while the sample is in-flight, determining a volume or area of the sample based at least in part on the measurement data, and calculating a weight of the sample based at least in part on the volume or area of the sample. The measurement data includes a captured image that includes a plurality of pixels. The determining of the volume of the sample includes determining the number of pixels in the captured image that display a portion of the sample, or determining the maximum number of consecutive pixels that display a portion of the sample in two or three dimensions.

Growing community of inventors

Diest, Belgium

Antoon De Cleen