Maintenance Scheduling using Big Data, IoT and Agent Based Simulation

Introduction to Big Data and its relevance to maintenance scheduling

Data collection methods in industrial settings (sensors, SCADA systems, etc.)

Data preprocessing and quality assurance techniques

Understanding IoT and its role in maintenance

IoT sensors and devices for condition monitoring

Real-time data acquisition and communication protocols

Fundamentals of agent-based modeling and simulation

Agent-based simulation in maintenance planning and scheduling

Building simulation models for maintenance scenarios

Leveraging Big Data for predictive maintenance

IoT applications for real-time asset monitoring

Case studies on successful implementations

Introduction to maintenance optimization

Genetic algorithms, swarm intelligence, and other optimization methods

Applying optimization techniques to maintenance schedules

Development of decision support systems for maintenance scheduling

Human factors and the role of decision-makers

Visualization and interpretation of maintenance data

Application of the learned concepts in different industries (manufacturing, transportation, energy, etc.)

Real-world case studies of successful maintenance scheduling projects

Identifying potential challenges and how to overcome them