10sun / iot-predictive-maintenance

Internet of Things : Predictive Maintenance

This repository contains notebooks and scripts to get you started experimenting with predictive maintenance models.

The data for this project can be found here.

This repository is meant to accompany this blog post.

Getting Started

Generating Train and Test Data

To generate necessary train/test data, execute the following command:

make data

This will produce a data/ folder, which will contain the following:

data
├── processed
│   ├── RUL.csv
│   ├── test.csv
│   └── train.csv
└── raw
    ...

The files in processed/ are cleaned and consolidated versions of the original files (stored in raw/), saved as CSVs.

train.csv and test.csv

The test.csv and train.csv files are in the following format:

Column	Description
dataset_id	id of the dataset where this instance is found
unit_id	id of engine (unique in each dataset)
cycle	number of operational cycles since beginning of engine operation
setting 1	value of operational setting 1
setting 2	value of operational setting 2
setting 3	value of operational setting 3
sensor 1	value of sensor 1
...	...
sensor 21	value of sensor 21

In the case of train.csv, observations continue until the time of failure of the unit. In test.csv, observations cease some number of cycles before engine failure.

RUL.csv

Column	Description
dataset_id	id of the original dataset of this instance
unit_id	id of engine (unique in each dataset)
rul	the remaining useful life of this unit, after its maximum cycle in the test dataset

Example Notebook

For some example visualizations and exploration, see the example notebook in notebooks/example.ipynb.