Traditional maintenance often relies on manual inspections and scheduled check-ups. While these are useful, they can be time-consuming, prone to human error, and they risk to miss the early signs of potential failures. As a result, organizations are increasingly turning to advanced technologies to implement proactive maintenance strategies.
In industrial manufacturing, the analysis of image data enhances monitoring and optimizes defect detection. Standardized processes allow the use of machine learning (ML) to handle complex image signals. For more challenging tasks, AI models like Convolutional Neural Networks (CNN) offer more effective solutions. Discover how pre-trained models boost efficiency and the benefits this technology brings to real-world applications.
Those traditional statistical methods are excellent tools, but they have certain limitations regarding their ability to respond to highly complex relationships in the data. This is where AI and ML come in.
Machine Learning describes a collection of algorithms that learn from data. This is useful to gain insights and to make predictions. These algorithms can detect relations that were previously unknown to the users. Machine Learning contains many different algorithms, older and more recent ones, as well as complex and simple ones. Brief history lesson: Many of […]