- May 19, 2017
May 19, 2017 –Sciemetric Instruments has released QualityWorX Vision – a data management and analytics platform that harnesses machine vision image data to help drive quality and productivity.
Machine vision is a multibillion-dollar market as manufacturers increasingly turn to using this technology for automated quality inspection. With the Industry 4.0 trend towards using data for more than basic traceability, the challenge becomes how best to handle terabytes of images and image datasets in production real time. QualityWorX Vision is intended to enable manufacturers to improve and optimize their investments in machine vision inspection.
Images and image data can be collected and archived in a centralized database, from either a single station or an entire production line. This image data can then be analyzed with the other datasets that pertain to a specific part or assembly. The result is real-time insights that empower smarter decision making.
QualityWorX Vision allows quality and manufacturing engineers to:
- Collect and store images, including image overlay information, along with their scalar data and digital process signatures – no more walking down to the production line with a USB stick to get the data.
- Launch, calibrate and set limits for machine vision stations faster with access to images, SPC histograms and trend data for upper and lower specification verification.
- Eliminate silos by collecting data from a single machine vision station, multiple vision stations or all stations on the plant floor (e.g., leak test, fastening systems, in-process test stations, etc.) into one consolidated part history record.
- Collect data from major image vendors such as Cognex and Keyence into one system, with more on the way.
- Carry out selective warranty recalls, faster root cause analysis and issue resolution through advanced data analytics and access to consolidated birth histories with images, scalar data and digital process signatures.
Image data can now be used in tandem with other datasets such as scalars and digital process signatures to drive continuous quality improvements for higher first-time yields, and to reduce scrap and rework rates and warranty claims.