Fault Prediction System for Laser Cutting Machines

This repository contains a basic implementation of a system for fault prediction and detection on Navigator KS-12V laser cutting machines. The project explores the use of time series analysis and machine learning models to identify potential equipment failures.

Contents

• Preliminary code for data preprocessing and analysis.
• Initial scripts for implementing predictive models: LSTM and k-shape clustering for time series data.
• LaTeX files and supporting materials from the associated thesis.

Notes

This repository represents an early-stage prototype and proof-of-concept developed as part of a graduation project. The system was not fully implemented, but it demonstrates the groundwork for future development.