The document discusses the growth and benefits of predictive maintenance solutions, highlighting a market expectation of over $10 billion by 2022. It emphasizes the cost-saving potential of optimizing maintenance and reducing downtime, which can cut overall life cycle costs by up to 10%. APMOptimizerTM is presented as a tool for enhancing reliability and efficiency in industrial operations through data analysis and predictive maintenance strategies.

1. apmOptimizerTM
Intelligent Asset Predictive Maintenance
Optimization S.W
Cutting the Life Cycle Cost
Rudy Shainer – V.P Sales & Marketing

2. Predictive Maintenance
Market landscape
MarketPredictive Maintenance a $1,498M Market in 2016, Expected to Grow to
$10,962M by 2022
The main aspects driving this growth are:
• New PdM-based business models
• Increased senior executive buy-in for IoT / PdM
• General decrease in cost of IoTtechnology
• Favorable technology replacement from CBM to PdM
Back in 2014 an Accenture report predicted that
investment in the Industrial Internet of Things
would reach $500 billion by 2020.
A combination of cheap sensors, powerful data
processing and machine learning and Predictive
Maintenance Optimization has enabled
companies to make their industrial processes
significantly smarter, more efficient and cuts the
Life Cycle Cost.

3. apmOptimizerTM
Optimizing the Maintenance and the Downtime Life Cycle Cost

4. goalsapmOptimizerTM

5.  Optimizing Maintenance ,Availability, Reliability
and Performance
 Improving Design of Assets / Factory / Utility
 Cutting the Life Cycle Cost
apmOptimizerTM
What it can do?

6. Asset Life Cycle Cost (LCC)
Initial Cost
Only 10%
of total LCC
Maintenance ( 20%)
Operations
Energy
others
90%
Downtime (9%)

7. Total Maintenance & Repair LCC ~ 20%
Total Downtime LCC ~ 9%
apmOptimizerTM
Optimizing in average 35% of the
Maintenance Life Cycle Cost and up to 50% of the Downtime
can cut ~ 10%
from Total LCC*
* (35% from 20%) + (50% from 9%)
apmOptimizerTM

8. Optimizing the Availability
and Cutting the Life Cycle Cost
 In average 35% saving on Maintenance cost
 In average 50% saving on Downtime cost
 Millions $$$ saving annually for large assets
 Increasing Availability and Reliability of the asset
 For New asset’s Design or for Improving exist assets
 Short ROI
 Reduce the total Life Cycle Cost up to 10%

9. Industries

10. Industrial Asset / Plant / Factory
Life Cycle Cost is $$$ Billions
Chemical Power Utility
Rail Automobile
Wind FarmOil & GasAerospace
Electronics

11. apmOptimizerTM
Vision for preventive maintenance is a key
lever to boost the productivity and efficiency of your Assets and
plants while minimizing the Lifecycle costs of your plants.
You can identify the causes for irregularities and minimize
unplanned downtime. In addition, enjoy greater flexibility in
managing repair activities, reduce your maintenance costs.
Maintenance Optimization
with vision: apmOptimizerTM

12. Data Collection &
Preparation
Model Analyze Optimize Report
Data
Gathering
Recommendations for
Optimal Maintenance
Validation
How it works

13. apmOptimizerTM
capabilities
Model asset behavior
 Lifecycle cost calculation
 Sensitivity analysis: identify cost and failure drivers
Optimize Maintenance and Logistics
 Repair / Discard policy for replaceable items
 Spare stock locations and quantities
 Preventive Maintenance Schedule
 Inspections Schedule
13

14. Features
 Field Data Analysis
 Life-Cycle cost
 Optimization
 Level Of Repair Analysis
 Scheduled Maintenance
 Predictive Maintenance
 Spare parts
 Performance Optimization
apmOptimizerTM

15. 15
Scheduled &
Predictive Maintenance
Optimization
Maintenance
Logs
(CMMS)
Component Failure
Distributions
Asset Behavior Model
Spare Parts Optimization
Asset (ERP)
Sensors Component Health
Analysis
Level Of Repair
Analysis
Resources
Optimization
3rd Party3rd Party
3rd Party
3rd Party
apmOptimizerTM
Optimization flow for existing Asset

16. Breakdown
structure
Reliability /
Failure data
Logistics Support
Parameters
Maintenance
Tasks &
Resources
Environmental
Operations
Profile
Initial
Maintenance
Strategy
 Life Cycle Cost Optimization
 Spare Parts Optimization
 Schedules & Predictive
Maintenance Optimization
 Level of Repair Analysis
 Resources Optimization
Inputs Outputs
Inputs and Outputs
apmOptimizerTM

17. after using
Large Downtimes
Low Availability
Increasing Maintenance Costs
over lifetime
Too many unplanned
Stoppages
Conservative Preventive
Maintenance schedules
No Predictive Maintenance
Too few / many Spares
Inflated Resources Allocation
Uncontrolled Performance
Levels
17
Minimal Downtimes
Maximal Availability
Minimal Maintenance Costs
over lifetime
Maintenance is Planned
Optimal Preventive
maintenance schedules
Optimal Predictive
Maintenance
Optimal Spares level
Optimal Resources Allocation
Predicted Performance Levels
apmOptimizerBefore
Benefits

18. Customer
Facility
Sensors
CMMS
Alerts
Collect data
Optimize
Maintenance
Machine
Learning
Intelligent Predictive maintenance
Concept
apmOptimizerTM
IoT

19. Short term
CMMS ERP MES BQR
Machine
learning
Analytics
Next – Gen Intelligent Predictive
maintenance on Cloud

20. BQR Confidential Information
apmOptimizerTM
Dashboard and Detailed Reports
 Life Cycle Cost
 Maintenance recommendations
 Spare Parts

21. For more information , please contact:
Rudy Shainer
V.P Sales & Marketing
Tel: +972 3 962 5911
Mobile: +972 585593088
Skype: rudysh10
Email: rudy@bqr.com
Web: www.bqr.com
Address: 5 Mazal Eliezer St.
Rishon-Lezion 7510102, Israel