The use of machine learning in warranty management is a growing trend, enabling businesses to analyze complex data sets and identify patterns that may indicate defects or malfunctions.
There are several types of machine learning models that can be applied in warranty management, including supervised learning (e.g. logistic regression), unsupervised learning (e.g. clustering), and deep learning (e.g. neural networks). Each type of model has its own strengths and weaknesses.
Here's an example of how machine learning can be used in warranty management: a company with multiple dealerships might use a model to predict when a vehicle is likely to need a warranty, based on factors such as mileage, age, and maintenance history.