Maintenance Scheduling using Big Data IoT and Agent Based Simulation
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Maintenance Scheduling using Big Data IoT and Agent Based Simulation
Maintenance Scheduling using Big Data IoT and Agent Based Simulation
20 -
24
Apr
2025
London,
United Kingdom
What are the Goals?
By attending this training course delegates will be able to make a substantial, positive impact on the Maintenance Scheduling Planning and Optimization best practices within their organization, more specifically:
- How to determine the actual maintenance schedules and downtime rates
- What influences the downtimes and breakdowns
- Maintenance principles, downtimes and preventive maintenance applications
- Using Predictive Analytics to Optimize Asset Maintenance
- Means and methods how to reduce/minimize/optimize asset life cycle costs
- Harness the Big Data and IoT benefits in maintenance planning and scheduling
- Simulate the influence of changing maintenance schedules on downtimes
- Learn how to avoid downtimes trough proper use of asset inventories
Who is this Training Course for?
This training course is designed for all professionals working in the field of data analysis, oil and gas exploration, geology and reservoir modelling, process improvement, asset management and maintenance management.
This training course is suitable to a wide range of professionals but will greatly benefit:
- Procurement Planners, Maintenance Planners, Asset Managers, Maintenance Managers
- Data Scientists and Data Analysts
- Logistics and Supply Chain Planers
- Other professionals involved in procurement, maintenance and operations of assets
Daily Agenda
Topics to be covered:
Amongst a wide range of valuable topics, the following will be prioritised:
- Big Data and IoT in maintenance management
- Import, analyse and interpret Big Data Through Predictive Analytics for Maintenance Optimization
- Understand the benefits of IoT for automation of maintenance scheduling and downtime reduction
- Perform the optimization of maintenance scheduling using AnyLogic simulation software
- IoT and adaptive maintenance: Integrated data collection
- Maintenance requirement forecasting
- Ripple and Bullwhip effects on production originating from poor maintenance plans
- Development of Work Programs and the Maintenance Calendar
- Sizing the Maintenance Staff
- Defining and optimizing supply chain process of spare parts in Any Logistic
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