Authors:

Wei Yuan

Date Created:

Not specified

Course Title:

Professor:

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About Paper:

This project analyzes the factors that affect Machine failure rates such as temperature, rotational speed, torque, tool wear, etc. This is very important for all manufacturing companies that need to produce machines as it helps the company to identify and proactively contact customers at risk of churn and try to repair the relationship in advance to reduce the risk of reduced revenue. Machine maintenance is one of the major expenses in terms of cost and downtime due to machine breakdown affecting the entire manufacturing process. Building a highly accurate predictive model can help a company identify problem areas in advance and maximize cost reduction. The failure rate is predicted by using random forest, logistic regression, KNN, and decision trees to get a model with high accuracy. Keywords: Machine Failure; Accuracy; Predict Model

Source:

Purdue University / 2024

Topics:

No topics listed

Co-authors:

Wei Yuan