Preventive-Maintenance-System

A simulation-based preventive maintenance system designed to detect potential faults in DC motors using real-time temperature and current sensor data.

🚀 Project Overview -

This project is a simulation-based preventive maintenance system for a DC motor using Arduino. It detects two common fault conditions — overheating and overload — using temperature and current sensors. Faults are displayed on an LCD screen and automatically shut off the motor to prevent damage. This project reflects an industry-relevant integration of electronics and mechanical maintenance concepts.

📌 Key Features -

• 🔥 Overheat detection using a temperature sensor

• ⚡ Overload detection using a simulated current sensor

• 🧠 Real-time motor health status on a 16x2 LCD

• 🛑 Automatic motor shutdown on fault detection

• ✅ Restores operation when normal conditions return

🎓 Why This Project?

As a mechanical engineering student, this project bridges the gap between mechanical systems and electronics-based monitoring, which is crucial for modern Industry 4.0 systems. It demonstrates skills in:

• Preventive maintenance

• Sensor integration

• Embedded systems

• Arduino programming

• Circuit simulation

🛠️ Components Used

Component	Description
Arduino Uno	Main controller
16x2 LCD Display	Shows system status
LM35 Temperature Sensor	Monitors motor heat
Potentiometer	Simulates current load
NPN Transistor	Acts as motor switch
DC Motor	Load device
9V Battery	Power supply
Breadboard & Jumper Wires	Circuit prototyping
Diode & Resistors	Safety components

⚙️ How It Works

This system continuously monitors a DC motor's temperature and load. When a fault is detected:

• 🟢 Normal: LCD shows only system status

• 🔴 Fault Detected: LCD shows fault type and corresponding sensor value

• 🔌 The motor is automatically turned OFF using a transistor switch during any fault

• ✅ Motor resumes operation when all readings return to safe range

This approach reflects real-world preventive maintenance principles.

🧪 Simulation

The project was simulated to visualize the circuit and test functionality.

• 🧪 Circuit Diagram:

• 📽️ Watch Simulation Demo:
  ▶️ Click here to view on Google Drive

📈 Real-World Relevance

This project models how predictive maintenance is used in Industry 4.0 to reduce unexpected machine failures, save costs, and improve safety. It’s a great introduction to condition-based monitoring (CBM) in mechanical systems.

🔐 License

This project is for educational and portfolio use only.
📎 Please do not reuse or distribute without permission.
© Rahul Bhoyar, All Rights Reserved.