Inspiration
What it does
How we built it
Challenges we ran into
Accomplishments that we're proud of
What we learned
What's next for Smart Predictive Maintenance
Inspiration
With over 20 years of practical experience in mechanical maintenance, I have seen how unexpected equipment failures can disrupt operations and increase maintenance costs.
This inspired my Smart Predictive Maintenance concept.
What it aims to do
The proposed system aims to help maintenance teams monitor pumps and industrial equipment, identify early warning signs of faults, and prioritize inspections before unexpected breakdowns occur.
How it is planned to work
The proposed solution will analyze operational indicators such as temperature, vibration, and pressure.
The goal is to combine equipment monitoring with an AI assistant that can explain abnormal readings and suggest appropriate maintenance checks.
Current development stage
This project is currently an early-stage concept. A working prototype using NVIDIA open-source models and Nebius infrastructure is planned but has not yet been completed or validated.
Challenges
The main challenges are developing a reliable software prototype, integrating an NVIDIA model through Nebius, and testing the system using representative equipment data.
What I hope to learn
I aim to learn how to integrate AI models into practical maintenance workflows and evaluate the usefulness of AI-generated maintenance recommendations.
Future plans
Build and test a functional prototype, improve the user interface, and explore future integration with real industrial sensors.
Built With
- and
- approach
- been
- before
- begin
- considering
- engineering
- evaluate
- has
- implemented.
- is
- model
- nemotron
- not
- planned
- prompt
- responses
- the
- to
- with
- yet
Log in or sign up for Devpost to join the conversation.