Combined Expertise for Quality Inspection in ADAS camera zones of windshields
Against this background, ISRA VISION and LaVision are entering into a collaboration in the field of optical quality inspection in ADAS camera zones of windshields. The objective is to create added value for customers through the synergetic use of both measurement approaches and to enable an extended, process-oriented evaluation of component quality.
ISRA VISION contributes its extensive expertise in automated inline/offline inspection and the reliable detection of production-related defects. LaVision complements this with high-precision optical metrology for analyzing image transmission quality based on SFR/MTF methods in the ADAS camera zone.
By combining both competencies, a measurement solution is created that enables a more holistic view across manufacturing and validation processes and establishes a direct link between optical and functional windshield quality.
Added Value for Manufacturers
This creates clear added value for manufacturers: more meaningful measurement data, improved process transparency, and a future-ready alignment with increasing requirements in ADAS and automated driving.
The collaboration represents a synergetic solution in a market where production quality alone is no longer sufficient. What matters increasingly is the interaction between stable manufacturing quality and validated optical performance in the ADAS camera zone – this is exactly where the collaboration creates value.
About ISRA VISION
ISRA VISION is a leading provider of technologies for industrial image processing (machine vision). As part of the Atlas Copco Group, a global leading provider of innovative technologies, products and services, we offer an extensive range of solutions for surface inspection, robot guidance and automated metrology.
About LaVision
LaVision specializes in high-precision optical metrology for analyzing image transmission quality in ADAS camera zones of windshields. Its systems enable SFR/MTF-based evaluation of optical performance and support the functional validation of modern driver assistance systems.