Certificate in Maintenance Scheduling Using Big Data, IoT and Agent Based Simulation

This course aims to equip students with the knowledge and skills required to optimize maintenance scheduling processes in various industries using cutting-edge technologies such as Big Data, Internet of Things (IoT), and Agent-Based Simulation. Maintenance scheduling is a critical aspect of industrial operations, and the integration of these advanced technologies can significantly improve efficiency, reduce downtime, and enhance overall asset management.

Course Overview

This course aims to equip students with the knowledge and skills required to optimize maintenance scheduling processes in various industries using cutting-edge technologies such as Big Data, Internet of Things (IoT), and Agent-Based Simulation. Maintenance scheduling is a critical aspect of industrial operations, and the integration of these advanced technologies can significantly improve efficiency, reduce downtime, and enhance overall asset management.

What you’ll learn
  • Understand the significance of maintenance scheduling in industrial operations
  • Gain knowledge about Big Data and its application in maintenance
  • Familiarize with IoT technologies and their role in real-time condition monitoring
  • Develop skills in agent-based simulation for maintenance planning
  • Learn how to integrate Big Data, IoT, and agent-based simulation in maintenance scheduling
  • Explore optimization techniques to enhance maintenance schedules
  • Develop decision support systems for effective maintenance decision-making
  • Analyze practical industry examples to apply the learned concepts effectively
Requirements

Candidates must;

  • Be proficient in English Language
  • Have access to either a computer or smartphone with Internet Connectivity
  • Be equipped with quality webcam and headphones
Duration & Fees
  • Regular – 8 Weeks – ₦200,000
  • Fast-Track -6 Weeks – ₦300,000
Program Dates
  • August – October, 2024
  • October – December, 2024
  • February – April, 2025
  • May – July, 2025