Qcify Inc.

Visys Nv

Qcify Inv.

Raf Peeters

Bert Peelaers

Pieter Boogaerts

Joachim Van Der Perre

Bert Switten

Antoon De Cleen

Pieter Ieven

Ruben Praets

Jef De Busser

Simon Kerkhofs

Bert Dirix

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

An adaptable inspection and sorting unit includes an attachment mechanism, an inspection sensor device that is capable of inspecting a sample, a sorting device that is capable of deflecting the sample, a data port that is capable of receiving information, and a power port that is connectable to a power source. The attachment mechanism, the inspection device, the sorting device, the data port, and the power port are physically connected together. A memory circuit and a processor circuit read information received via the data port, control the inspection sensor device, and control the sorting device. The adaptable inspection and sorting unit is capable of inspecting and deflecting a sample traveling along the processing line. The speed of the sample is measured utilized to determine a delay between inspecting the sample and sorting the sample.

Adaptable inspection and sorting unit

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.

Automated sample weight measurement via optical inspection

A method for generating a quality inspection data block for a distributed ledger includes: determining an identification code associated with a sample to be inspected, inspecting the sample and thereby generating quality inspection data associated with the sample, and after completion of the inspecting of the sample combining the identification code and the quality inspection data into the quality inspection data block. The method also includes adding the quality inspection data block to the distributed ledger. An inspector including a sensor that senses a characteristic of a sample, a memory that stores sensor output data, and a processor configured to: determine an identification code associated with a sample to be inspected, generate quality inspection data based on the sensor output data, and combine the identification code and the quality inspection data into a quality inspection data block. In one example, the inspector is an in-flight 3D inspector.

Quality inspection data distributed ledger

A sub stream auto sampling system includes an inspection unit and a sorter unit. The inspection unit includes a camera configured to capture an image of a sample, a light configured to illuminate a sample, a processor configured to process the captured image, and a memory configured to store the captured image. The sorter unit is configured to divert a sub stream of samples, from a main stream of samples, toward the inspection unit. The output of the inspection unit may be directed to the main stream of samples, or the output of the inspection unit may be directed to a collection unit. In addition to the inspection performed by the inspection unit, weighing of the sub stream of samples may also be performed by a weighing unit before the sub stream of samples are routed to the main stream of samples or the collection unit.

Sub stream auto sampling

An adaptable sorter unit includes an attachment mechanism, a device that is capable of moving a first sample by use of a vacuum, a pressurized air inlet, and a valve. The pressurized air inlet is connected to the valve that controls a flow of pressurized air through the device. The valve may be electronically controlled or pneumatically controlled. The location of the adaptable sorter unit may be adjustable based, at least in part, on data captured by an optical inspector. An array of adaptable sorter units may be configured side-by-side to cover the width of the processing line. The device may be a venturi vacuum. The adaptable sorter unit may include a baseline vacuum control valve that causes a baseline vacuum force to be applied. An electrical control signal may be used to open the valve, the frequency of which may control the amount of time the valve is opened.

Vacuum adaptable sorter unit for existing processing lines

An adaptable sorter unit includes an attachment mechanism, a sorting device that is capable of deflecting a sample, a data port that is capable of receiving information, and a power port that is connectable to a power source. The attachment mechanism, the sorting device, the data port, and the power port are physically connected together. The adaptable sorter unit also includes a memory circuit and a processor circuit configured to read information received via the data port and control the sorting device. The sorting device is a vacuum system, a mechanical pedal system, or an air jet system. The attachment mechanism is a mounting bracket, a mounting bracket receptacle, a weldable material, a clamp, a bolt, or a screw. The attachment mechanism connects the adaptable sorter unit to a processing line such that the adaptable sorter unit is capable of deflecting a sample traveling along the processing line.

Adaptable sorter unit for existing processing lines

An adaptable inspection unit includes an attachment mechanism, an inspection sensor device, a data port that is capable of transmitting information, and a power port that is connectable to a power source, all of which are physically connected together. The adaptable inspection unit also includes a memory circuit and a processor circuit. The processing circuit controls the inspection sensor device and writes information transmitted via the data port. The attachment mechanism is a mounting bracket, a mounting bracket receptacle, a weldable material, a clamp, an adhesive, a magnet, a latch, a lock, a locating pin, a rail, a slide, locking pin, a bolt, a screw, gravity or friction. The attachment mechanism is used to connect the adaptable inspection unit to a processing line such that the adaptable inspection unit is capable of capturing an image of a sample traveling along the processing line.

Adaptable inspection unit for existing processing lines

An in-flight 3D inspector includes a sample input funnel, a sample chute, a trigger, a plurality of cameras, a light source and storage device. A sample is placed in the sample input funnel and is caused to travel down the sample chute. The trigger is located on the sample chute and detects when the sample passes the trigger. In response to detecting the passing of the sample, the trigger outputs a trigger signal that indicates when the sample will pass through a focal plane on which all the plurality of cameras are focused. In response to the trigger signal, the sample is illuminated by the light source and the plurality of cameras capture an image of the sample as the sample passes through the focal plane. The captured images are stored on the storage device and used to generate a 3D image of the sample.

In-flight 3D inspector

An optical inspector with feedback capability includes an optical device that captures an image when a sample is within the field of view of the optical device, a storage device that stores the captured image, a processor that determines a quality characteristic value of the sample based on the captured image, and an interface circuit that outputs inspection data or a command based on the quality characteristic value. A method of controlling a sample processing line is also disclosed, the method including capturing an image of a sample traversing the processing line, determining a quality characteristic of the sample based at least in part on the captured image, and causing the operation of a device included in the processing line to be adjusted based at least in part on the quality characteristic value. In one example, the optical inspector is an in-flight 3D inspector located in the processing line.

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San Mateo, CA, United States of America

Raf Peeters