Maintenance ManagementPredictive Maintenance and Digital Twin Technologies
This course examines how sensor data, machine learning, and digital twin models are moving maintenance from calendar-based intervention to condition-based and predictive intervention. Delegates explore practical entry points for African plants with mixed legacy and modern equipment, including low-cost sensor retrofits and cloud-based analytics platforms. The course is technology-aware but strategy-led, focusing on business case, data quality, and change management rather than vendor hype.
Course objectives
- Explain the difference between preventive, condition-based, and predictive maintenance approaches
- Identify suitable pilot assets and sensor strategies for predictive maintenance programmes
- Understand the role of digital twins in simulating asset behaviour and forecasting failure
- Assess data quality, connectivity, and integration requirements for predictive maintenance
- Build a business case and phased rollout plan for predictive maintenance adoption
Who should attend
- Reliability and maintenance engineers
- Plant digitalisation and automation specialists
- Maintenance managers exploring predictive programmes
- Instrumentation and control engineers
- Asset performance management analysts
Course outline
- 01From reactive to predictive: the maturity curve of maintenance technology
- 02Sensor selection, retrofitting, and data acquisition fundamentals
- 03Digital twin concepts and their application to critical asset monitoring
- 04Analytics platforms, alarm thresholds, and machine learning basics for maintenance
- 05Data quality, cybersecurity, and integration with existing CMMS and control systems
- 06Building the business case, pilot design, and scale-up roadmap
Scheduled sessions
| Dates | Venue | Format | Price | Register |
|---|---|---|---|---|
| 24 to 26 February 2027 | Victoria Falls, Zimbabwe | Classroom | R11,995 per delegate | Register Now |
| 22 to 24 April 2027 | Dar es Salaam, Tanzania | Classroom | R11,995 per delegate | Register Now |
| 1 to 3 May 2027 | Kigali, Rwanda | Classroom | R11,995 per delegate | Register Now |
| 23 to 25 May 2027 | Dubai, UAE | Classroom | R11,995 per delegate | Register Now |