Computer Vision and Efficiency
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Nowadays, manufacturers try to save the environment by saving energy and decreasing carbon emissions. They want to reduce their role in the environmental crisis.
It requires complicated calculations involving estimated use of energy, chain management, and efficient production. Data science makes it easy to fulfill exceeding goals with AI-powered technologies and computer applications.
Modern methods of quality control prove helpful to achieve desired results. These methods are detection, classification, and object identification. The procedure may be evaluated through computer vision to obtain the expected outcomes.
Benefits for the company
Manufacturers may get the advantage of decrease labor cost, better quality control, high-speed capacity of processing, and consistent operability.
Feasability
Medium
Type of expertise/ AI domain
Computer Vision
Internal data required
Defect reports, manufacturing logs, etc.
Traditional vision systems can measure different parts for their tolerance. This system is efficient to measure the standard of different parts. It is equally important to detect the quality of manufactured parts for other defects, including dents, scratches, scuff marks, etc. In a traditional system, humans are responsible for checking these defects.