Skip to content

telkamp7/predictive_maintenance

Repository files navigation

Predictive Maintenance

This project is dedicated to evaluating the viability of implementing predictive maintenance in a manufacturing environment. The approach integrates data analytics and machine learning to forecast equipment failures proactively. Through the meticulous collection and analysis of data from sensors and equipment, the goal is to refine maintenance schedules, mitigate unplanned downtime, and elevate the overall operational efficiency of the manufacturing process. The project seeks to demonstrate the tangible benefits of predictive maintenance, emphasizing its potential to optimize resource allocation and improve the overall reliability of manufacturing operations.

Project structure

The directory structure of the project looks like this:

├── Makefile             <- Makefile with convenience commands like `make data` or `make train`
├── README.md            <- The top-level README for developers using this project.
├── data
│   ├── processed        <- The final, canonical data sets for modeling.
│   └── raw              <- The original, immutable data dump.
│
├── docs                 <- Documentation folder
│   │
│   ├── index.md         <- Homepage for your documentation
│   │
│   ├── mkdocs.yml       <- Configuration file for mkdocs
│   │
│   └── source/          <- Source directory for documentation files
│
├── models               <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks            <- Jupyter notebooks.
│
├── pyproject.toml       <- Project configuration file
│
├── reports              <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures          <- Generated graphics and figures to be used in reporting
│
├── requirements.txt     <- The requirements file for reproducing the analysis environment
|
├── requirements_dev.txt <- The requirements file for reproducing the analysis environment
│
├── tests                <- Test files
│
├── predictive_maintenance  <- Source code for use in this project.
│   │
│   ├── __init__.py      <- Makes folder a Python module
│   │
│   ├── data             <- Scripts to download or generate data
│   │   ├── __init__.py
│   │   └── make_dataset.py
│   │
│   ├── models           <- model implementations, training script and prediction script
│   │   ├── __init__.py
│   │   ├── model.py
│   │
│   ├── visualization    <- Scripts to create exploratory and results oriented visualizations
│   │   ├── __init__.py
│   │   └── visualize.py
│   ├── train_model.py   <- script for training the model
│   └── predict_model.py <- script for predicting from a model
│
└── LICENSE              <- Open-source license if one is chosen

Created using mlops_template, a cookiecutter template for getting started with Machine Learning Operations (MLOps).

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published