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Classification of equipment damage

Classification of equipment damage

Photos of defective spare parts are analyzed by a machine learning algorithm and the damage is classified. This information is used in the development of new products and in the selection of suppliers.

1

Process

In the development of new products, it is important to identify and eliminate the defects of past product lines. To ensure this, the service technician takes a photo of defective spare parts.

2

Algorithm

Based on historical data and similar photos of this spare part, the Machine Learning algorithm analyses the damage and classifies it into pre-defined classes.

3

Decision

Based on the classification of repair damages from previous product series, detailed information on repairs and complaints is available. This information is incorporated into product development of new products and the selection of suppliers and components.

More Use Cases

Handwritten documents can be read out and prefilled using machine learning algorithms. By further input, these documents can be edited again, which again benefits the accuracy of the algorithm.

Electronic patient records can be evaluated using machine learning algorithms. This automatically provides doctors with suggestions for diagnoses and therapy options.

Diagnostic suggestions can be made by analyzing X-ray or MRI images using an algorithm.

Through standardized images of different leathers, a machine learning algorithm can classify leather and assign it to the right garments.


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