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TIA QualityHealth consists of applications where images are evaluated using deep learning algorithms that are focused on defect localization and classifications, near real-time image analysis is performed on streaming data and defect detection algorithms are used.
The first step for the defect localization is the use of related dataset. At this stage, TEKNOPAR image processing library is used. Images of defective and defect free products are collected by industrial high-resolution cameras. The library contains functions for data augmentation, resizing, imperfect data identification, image enhancement, ROI extraction, evaluation, and labeling appropriate for their use. According to the requirements of defect detection, deep learning, classical image processing or statistical methods are developed. Defects are localized and evaluated by the algorithms in the library, and the results are presented to the users via web-based applications. Being a flexible system, TIA QualityHealth can be customized according to the specific needs and requirements of the users.
TIA EDGE is a service by which the users select the edge device and install them so that the software calculates and transfers data at the edge (Edge) in any production facility. Edge devices used within the scope of TIA EDGE collect data instantly from the field.
TIA STREAM enables users to transfer data from data sources to relevant targets, TIA PLATFORM modules and/or different destinations. TIA STREAM easily integrates with all kinds of equipment and data sources thanks to its modular structure compatible with automation technologies.
TIA DETECT is a module developed for visual defect detection in industrial production facilities. It detects defects in optical or X-Ray images collected by industrial cameras to perform inspections and prevent defective products.
TIA DASHBOARD is a data visualization module developed with the involvement of real users. The module integrates directly with other modules in the TIA PLATFORM, enabling easy and understandable visualization of data and the use of modules.
