MAINTENANCE OPTIMIZATION USING ADVANCED ANALYTICS

THE NIGERIAN INSTITUTION OF MECHANICAL ENGINEERS ( NimechE )
A DIVISION OF THE NIGERIAN SOCIETY OF ENGINEERS
PORT HARCOURT CHAPTER
PRESENT A SEMINAR
TITLED : MAINTENANCE OPTIMIZATION USING ADVANCED ANALYTICS.
PRESENTER : ENGR. VALERIE AGBERAGBA, FNSE
GM Generation Project NDPHC
Vice President WFEO ( 2016 - 2019)
Vice President NSE ( 2011- 2013
President APWEN ( 2006 - 2007 )
Date : Tuesday 11th March 2025, Time : 5: 00pm
THE CHALLENGE OF MAINTENANCE OPTIMIZATION
- Ensure asset reliability
- Reduce downtime
- Improve efficiency
- Traditional Method limited
UNLOCK THE POWER OF ADVANCED ANALYTICS
- Predictive Maintenance ( preventive maintenance )
- Condition - base maintenance ( monitor asset performance )
- Reliability - Centered maintenance ( Optimize reliability )
- Asset performance management ( Track and improve performance).
TYPE OF ADVANCED ANALYTICS
- Machine Learning ( patterns and predictions )
- Deep Learning ( Complex data patterns )
- Natural language Processing ( Analyze textual data )
- Statistical Modeling ( Data relationships )
BENEFITS OF ADVANCED ANALYTICS
- Improve asset reliability
- Reduced downtime
- Enhanced predictive capabilities
- Data - driven decisions
PREDICTIVE MAINTENANCE : A CASE STUDY,
Manufacturing facility implemented predictive maintenance machine learning algorithms used, downtime reduced by 25%, maintenance cost reduced by 15%.
IMPLEMENTATION ROADMAP
- Define objectives and KPIs
- Collect and integrate data
- Develop and display models
- Monitor and evaluate
CHALLENGE AND LIMITATIONS
- Data quality and availability
- Complexity of Models
- Integration with systems
- Change management and adoption.
CONCLUSION : Maintenance Optimization, Advanced Analytics offers significant opportunities. Leverage predictive models, Machine Learning, and Data - driven insights, improve asset reliability, reduced downtime, and enhance overall efficiency.