Detect failed air pumps
Budget: €30 – €250 EUR
AirPump failures
A customer is manufacturing devices containing air pumps that provide pressure for a machine cycle. Ideally, the air pressure rises sharply and remains stable throughout the machine's cycle, where it drops sharply. However, it can happen that the air pressure drops due to pump failure, or the air pressure rises or drops slowly.
The goal of the project is to detect a pump failure. The typical air pump failure is a temporary pressure decrease in the first half of the cycle.
Data structure
Data
The data consists of the following columns (in this particular order):
MachineId - Id of the machine
MeasurementId - Id of the measured cycle
Pressure - Air pressure (kPa)
The data does not contain timestamps, but for each machine and measured cycle combination, observations (i.e. rows) of the pressure values are ordered by time, and the time intervals between individual observations are always the same.
Labels
The labels consists of the following columns (in this particular order):
MachineId - Id of the machine
MeasurementId - Id of the measured cycle
PumpFailed - True if pump failed
SlowStart - True if the pressure rised slowly
SlowEnd - True if the pressure dropped slowly
Your task:
Develop a predictive model for the PumpFailed column and report its performance in appropriate metrics.
Explain your model.
Notes
We suggest you to use Python and Jupyter notebook for this assignment.
Requirements
Spend maximum of one working day on this assignment
Document your work so the Jupyter notebook is self-explanatory
Data:
https://drive.google.com/file/d/12X9E7Y6P8dimPG95eMBFJ9Onw479ZV-Z/view?usp=sharing
A customer is manufacturing devices containing air pumps that provide pressure for a machine cycle. Ideally, the air pressure rises sharply and remains stable throughout the machine's cycle, where it drops sharply. However, it can happen that the air pressure drops due to pump failure, or the air pressure rises or drops slowly.
The goal of the project is to detect a pump failure. The typical air pump failure is a temporary pressure decrease in the first half of the cycle.
Data structure
Data
The data consists of the following columns (in this particular order):
MachineId - Id of the machine
MeasurementId - Id of the measured cycle
Pressure - Air pressure (kPa)
The data does not contain timestamps, but for each machine and measured cycle combination, observations (i.e. rows) of the pressure values are ordered by time, and the time intervals between individual observations are always the same.
Labels
The labels consists of the following columns (in this particular order):
MachineId - Id of the machine
MeasurementId - Id of the measured cycle
PumpFailed - True if pump failed
SlowStart - True if the pressure rised slowly
SlowEnd - True if the pressure dropped slowly
Your task:
Develop a predictive model for the PumpFailed column and report its performance in appropriate metrics.
Explain your model.
Notes
We suggest you to use Python and Jupyter notebook for this assignment.
Requirements
Spend maximum of one working day on this assignment
Document your work so the Jupyter notebook is self-explanatory
Data:
https://drive.google.com/file/d/12X9E7Y6P8dimPG95eMBFJ9Onw479ZV-Z/view?usp=sharing