The unproper wear of Personal Protective Equipments is a common safety infraction on construction sites, which can lead to risking the lives of the workers. By using a deep learning system plugged to on-premises cameras, you can automatically determine if individuals are correctly wearing the appropriate protective equipment, such as face coverings (surgical masks, N95 masks, fabric masks), head coverings (hard hats or helmets), and hand covers (surgical gloves, safety gloves, cloth gloves).
Detecting defects late in the production process can lead to costly failures and harm customers relationship. Deep learning models can identify and classify defects while ensuring the overall quality of manufacturing products. After determining what defects the system should detect (Small fractures in vehicle parts like camshafts, brake discs, and brake pad...), manufacturing errors can be recognized automatically in order to reduce production costs, speed the manufacturing process, and improve accuracy.
Spot welding is a method of attaching two or more metal pieces together by applying pressure and heat to the weld region using an electric current, resulting in subtle variances in each weld. These acceptable deviations are frequently captured by machine vision cameras as shadows or reflections, which machine vision software interprets as a fault. Deep learning algorithms can distinguish between true problems and picture fluctuations.
Surface defect identification is a sensitive process that needs high levels of precision. Fatigue and monotony may affect traditional visual human inspection. Using a deep learning system helps prevent cars from leaving the factory floor with flaws while meeting expected quality standards, especially when the company's reputation is at stake.