PdM-O Predictive Maintenance Optimization
Predictive Maintenance (PdM) includes many techniques whose goal is to identify approaching equipment failures, and conduct Preventive Maintenance (PM) before the failures occur.
PdM is also known as Condition Based Maintenance.
BQR’s PdM-O module Optimizes the periods between scheduled inspection events for equipment at the various asset hierarchy levels, accounting for equipment ageing (failure distribution), logistics, cost, and grouping of maintenance tasks.
For optimization of scheduled Preventive Maintenance, click here.
Benefits
Highlight
Optimization accounts for grouping of inspection tasks in order to reduce the number of times that an assembly is opened
Steps for conducting a Predictive Maintenance Optimization
Import (optional)
- Import the block tree, components and failure modes from BQR’s FMECA using BQR’s Core Database
- Alternately, data can be imported from CSV files
User Input
- Define project data such as: Life-Cycle period and operation profiles
- Define the reliability model, repair and replace policy for each block
- Define logistics options for the asset including: spare stocks, OEMs, shops, and transportation routes
- Define costs of inspections, maintenance actions, and downtime
- Define resources required for each inspection and maintenance task (optional)
- Define additional scenarios in order to compare cost and availability
Analysis
- The software validates the user data. If data is missing, user is notified
- Software optimizes the period between inspections for each block, and finds the optimal schedule that minimizes Life-Cycle Cost (LCC) while maintaining high asset availability
Reports
- Detailed inspections schedule
- All reports can be saved as Excel, HTML or Word files
Features
- Flexible asset behavior model
- Part libraries
- Import tree from Excel or BQR CARE
- Fast analytic calculations
- Search and Sort functions
- Notify user if project data is incomplete or inconsistent
- Detailed help and wizard for beginners and advanced users