SciEtech

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.