1. Reliability Centered Maintenance
Reg Cook MEng, MBA, ACGI, AMIMechE
Director Asset Management

2. telent Technology Services
A leading technology company delivering ICT, mission critical communication networks and operational systems, vital in the effective operation of the nation’s infrastructure.  
Industry sectors include Public Safety & Defence, Transport, Service Provider, Government / Public Services.
Asset Management specialises in business critical maintenance
Take you through our reliability centred maintenance journey

3. Opportunity - technology
Increased networking of assets
Mobile devices and data
Increased processing power
End devices more intelligent
Convergence of telephony and IT
Analytics and big data
Predict and prevent
Remote Support
Improve Performance
Reduce
Cost
Business Change
Comms changing – becoming more like IT and combination to old and new assets

4. Opportunity - RCM Traditional Maintenance Fix on failure
Planned maintenance
Periodic routines to change components or measure condition
Age based instead of usage based
Some routines are not targeted at failure modes
Sometimes following out of date standards
Assume predictable bathtub type failure profile
Reliability Centred Maintenance
Remote Condition Monitoring
Design for Reliability
FMEA
Remote Access
Remote Management

5. Operational benefits
Remote Technical desk support operational staff and site engineers
Remote Condition Monitoring
Remote Compliance Checks
Remote Diagnostics
Remote Fix
Remote Support
Monitor deterioration for the prevention of failure
Significant opportunity for IT based assets. Improve performance and reduce costs
Check assets are working and performing as intended
Understand root cause before resolving – improve efficiency and effectiveness
Lost of other stuff that we’re doing but focusing on remote stuff

6. Challenges Getting to grips with the tech to unlock vast potential
Managing and analysing large volumes of data
Collecting and data from old assets
Cost benefit
Reactive vs proactive and changing the culture
Remotely accessing assets
Network security
Need example of Visiowave picture monitoring

7. Challenges - Remote Condition Monitoring
To address deterioration in a planned way, understanding P-F is critical
Most literature targets individual mechanical components (e.g. pumps) with good failure data. We have a large and varied population of distributed assets
Initial cost increase as we rushed to address deterioration with limited impact on faults
Now taking iterative approach
Estimate P-F
Adjust when failure data received

8. What we’re aiming for Reduce Asset Life Cycle Cost Cost
Capital Cost
Running Cost
Cost of Failure
Increase Asset Life
Reduce PPM Cost
Reduce Corrective Maintenance Cost
Reduce Operating Costs
Reduce number of faults
Reduce Impact of failure
Fix quicker
Early detection
Running Costs
Cost
Need to build slide

9. What we’ve achieved so far ……..
85% increase in first visit fixes
2.7% year on year fault reduction
Reduce Asset Life Cycle Cost
Capital Cost
Running Cost
Cost of Failure
Increase Asset Life
Reduce PPM Cost
Reduce Corrective Maintenance Cost
Reduce Operating Costs
Reduce number of faults
Reduce Impact of failure
Fix quicker
Early detection
Running Costs
Cost
25% remote fixes for networked assets
43% reduction in PM resource over 5 years
17% reduction in CM heads over 5 years
£4.5m contract saving over 2.5 years
Obsolescence Management extending asset life
Example of one of our contracts

10. How we’ve approached
Working closely with customers to realise and share benefit
Heavy investment in processes and tools – critical to delivery improvement
Data driven
Cost benefit
Promote culture of continuous improvement and innovation
Close working important as risk averse environment doing things differently is challenging

11. Invested in processes and tools
TRAMMS asset management system and end to end automation
State of the art Service Desk staffed by senior engineers
ITIL ISO 20001
Asset Management ISO standard
Having the right systems and tools is essential
Developed asset management system ourselves so quick to adapt

12. Invested in processes and tools
Network monitoring
Analysis of asset and network performance, applications and systems
24/7 health monitoring
Forecasting of asset condition
Early identification of failing and offline assets such as routers, switches, Terminal servers, RTUs
Reduction in asset downtime and improved user experience of the SMS

13. Invested in processes and tools
Alarm Aggregation and prioritisation
Pulls alarms and events from different systems and presents to the operator

14. Invested in processes and tools
Condition monitoring:
Monitors attributes such as voltage vibration and temperature which can lead to failure
Range of assets including lifts escalators, doors and equipment rooms
Available on smart devices
Developed by telent
Acumen supporting other assets

15. Case Study
CCTV Cameras

16. Case Study – CCTV Cameras
Maintain 38,000 cameras across the UK Transportation network
Important for:
Traffic Management
Crowd control
Station Management
Evidence gathering to support police and health and safety investigations
Traditionally lots of periodic planned maintenance
with typically tight fix SLAs (e.g. 4 hours)
Big Opportunity to reduce cost and improve performance

17. Figure 2 - Failure probability patterns
Case Study – CCTV Cameras
Not everything follows bathtub
Technology Assets typically follow E and F (exception is LEDs and bulbs)
Typically random failures across asset a population
Periodic planned maintenance less effective as cannot predict failures.
With fix SLAs of 4 hours PPM should be a waste of time
Figure 2 - Failure probability patterns
Mentioned earlier not everything follows bathtub

18. Case Study – CCTV Cameras
We studied fault trends before and after planned maintenance and found there was no appreciable change in reported faults
Our data showed we were addressing quite a few camera faults during PPM which was surprising when fix SLA was 4 hours
As a follow up we did a remote study of cameras across 3 stations and found:
Around 8% of camera faults are reported within 24hrs - after further study these were typically found to be operationally critical
For around 90% of camera faults the time between a camera failing and it being reported was between 3 days and 3 months with an average report time was 19 days
As part of study to work out optimum planned maintenance interval Big data approach. Surprising that we were resolving faults in planned maintenance when 4 hour fix SLA

19. Case Study – CCTV Cameras
In response we developed Arbitex
Automated checking of camera Alignment and image quality
Most analogue and digital cameras
Low bandwidth
High accuracy
Realised there was a customer need. Couldn’t find anything for mass deployment so developed ourselves

20. Case Study - Arbitex delivers
Assurance that CCTV estate is fully functional
Notification of faults, allowing potential rectification before an issue is logged.
Better availability with longer fix SLAs hence lower cost
Supports a lower cost approach to planned maintenance (because we’re now continually checking)
Customers can view reference images and the latest snapshots through the customer portal – no need for shot books
Deployed across 10,500 cameras for London Underground and Network Rail
Provide better value lower cost maintenance

21. Case Study - Arbitex alignment tool
Available on smart devices
Tells the user which way to move the camera
Reduced costs: A single engineer can realign or replace a camera
No longer to need engineer in Control room
Ensures that the camera is exactly in alignment (historically, this was done by eye)
End to end system assurance
4 hour fix SLA expensive and doesn’t offer value for money

22. Benefits of Arbitex End to end system assurance
Improved asset availability
Significant cost reduction in corrective and planned maintenance
Remove shot books

23. Other examples

24. TFL Traffic CCTV 860 cameras across London
Working with TFL and Costain we replaced Encoders and installed camera monitoring to identify issues and trends
Enhanced repairs to address top failure mode and enhance design
Reduced Faults by 58% over 3 years
Reduced field visits by 81% improving safety and reducing cost

25. NRTS DVRs Reduced Outages from 5 in Q1 to 0 in Q2 and Q3
We collect stats for over 2000 HDDs including temperature and reallocated sectors. This allows us to replace and prevent failure
Replace HDDs if more than 10 reallocated sectors in 30 days

26. Condition Monitoring of TFL DVRs
20% reduction total in reported DVR faults and 24% remote fixes
Monitor to give early warning of failure:
Temperature
Fan speeds (RPM)
System availability
Video input / being recorded
CPU utilisation
Memory
Application services
Still learning
Condition monitoring to predict and prevent faults
Active status monitoring detects at the point of failure improving availability
Replaces traditional PPM and delivers significant cost reductions
20% reduction total in reported DVR faults and 24% remote fixes
Still learning – predict further improvements as we learn more and more assets are networked

27. Traffic Signal Maintenance London
Reduced: Reported failures from 120 per day to 65 per day and repeat faults by more than 75%.
Our software team extract and slice data from TfLs system automating reporting
Our System Engineers use this data to target improvements and fix the underlying cause of problems