Application requirements determine the most appropriate inspection methods
Industry 4.0 is constantly evolving. Today machines automate the production, assembly and movement of materials. Industrial vision systems can inspect hundreds and even thousands of parts per minute reliably and repeatably, far exceeding human capabilities.
Image analysis with Deep Learning combines the specificity and flexibility of human visual inspection with the reliability, repeatability and power of a computer system. Deep Learning models solve complex vision applications precisely and repeatably that would be laborious to develop and virtually impossible to maintain using the traditional approach to industrial vision. Deep Learning models are able to distinguish unacceptable defects by tolerating natural variations in complex models. They can also be easily adapted to new examples without reprogramming basic algorithms. Deep Learning based image analysis software performs localization, inspection, classification and recognition of evaluative characters with greater efficiency than humans or traditional industrial vision solutions. More and more leading manufacturers choose Deep Learning and artificial intelligence solutions to solve the most sophisticated automations. Essentially, the choice between traditional industrial vision and deep learning depends on the type of application to be solved, the amount of data to be processed and the processing capabilities. Despite the many advantages, deep learning is not suitable for all applications.
At EPF, with our 60-year experience in the field of industrial automation and our qualified team, we have developed Beika®, a solution for quality control and objective and automatic inspection.
Beika® solves complex manufacturing applications that are too difficult or time-consuming for standard industrial vision systems to achieve reliable and consistent results through visual inspections by operators. The applications already successfully executed involve the main production sectors with thousands of references and present very interesting ROI depending on the complexity of the project.