Condition-based maintenance (CBM or CBM+) is a strategy of performing maintenance on a machine or system only when there is objective evidence of need or impending failure. CBM is enabled by the evolution of key technologies, including improvements in - sensors, microprocessors, digital signal processing, simulation modeling, multisensor data fusion, reliability engineering, Internet of Things (IoT) connectivity, data warehousing, cloud computing, machine learning (ML), artificial intelligence (AI), and predictive analytics. CBM involves monitoring the health or performance of a component or system and performing maintenance based on that inferred health and in some cases, predicted remaining useful life (RUL). This predictive maintenance philosophy contrasts with earlier ideologies, such as corrective maintenance — in which action is taken after a component or system fails — and preventive maintenance — which is based on event or time milestones. Each involves a cost tradeoff. Carl Byington with PHM Design, LLC reviews some of the elements of CBM. #phmdesign https://phmdesign.com

2. With Reliability Centered
Maintenance
Time to Action
Based on
Population
Statistics
With Condition-Based Maintenance + Prognostics
(CBM+)
Actual
conditions
Results in:
Scheduled
preventative
maintenance
Results in:
Opportunistic
maintenance at
no additional risk
Benign
Aggressive
Remaining Useful Life

3. Very early
incipient fault
Proper
Working
Order - New
Desire: Advanced Sensors
and Detection Techniques to
“see” incipient fault
Prognostics Diagnostics
Need: Understanding of fault to
failure progression rate
characteristics
Predicted useful life remaining
System, Component, or
Sub-Component Failure
Develop: Useful life
remaining prediction
models – physics and
statistical based
Secondary Damage,
Catastrophic Failure
Need: Better models to
determine failure effects
across subsystems
Determine effects on
rest of aircraft
The Goal is To Detect “State Changes” as Far to the Left As Reasonable
State Awareness Detection

4. § Detection
Monitored parameter(s) has departed its normal or acceptable operating
envelope.
Inherently a tracked change and exceedance event problem.
§ Diagnosis
Identify, localize, and determine severity of an evolving (incipient fault
through functional failure) condition.
Inherently a classification problem.
§ Prognosis
Reliably and accurately forecast remaining operational time to end of useful
life, future condition, or risk to complete mission.
Inherently a prediction problem.

5. The application of the appropriate sensors (data), analysis (knowledge), and
reasoning (context) to estimate the health and track the degradation of equipment.
A philosophy of maintaining equipment based on an estimation of its condition and
maintenance logistics. Enhanced application of CBM is through the prediction
(prognosis) of the equipment remaining useful life or time to service need.
A health management approach to reduce/eliminate inspections and time-based
maintenance through accurate monitoring, incipient fault detection, and prediction of
impending faults. Often discussed in context with Autonomic Logistics.
Data acquisition hardware and software with elements of feature extraction (condition
indicators), detection logic, regime recognition and usage estimation. Typically involves
onboard hardware and ground station maintenance planning elements.

6. CBM/PHM applied to the unique case of structural elements and large, relatively static
elements. Deals with the development and implementation of techniques and systems in
which monitoring, inspection, damage detection, and modeling become an integral part of
structural integrity assessment and maintenance planning. SHM merges and builds upon
a variety of techniques related to machinery detection, diagnostics, and prognostics.
Flight performance and aircraft systems data is collected, downloaded, analyzed and
visualized to provide quantitative data and actionable information to assess aircrew
performance, troubleshoot system malfunctions, and identify and address unfavorable
trends. Make data available in a manner to increase safety and positively affect operations.
Growth and ‘smarter’ extension of the HUMS concept in the helicopter world but more
general in the fixed wing and other communities. IVHM generally describes the knowledge
processes used to estimate asset health and readiness computing as well as systems that
perform feature extraction, detection, diagnostics, and reasoning. Again, typically involves
onboard monitoring hardware and software for maintenance/logistics planning elements.

7. • Naval Safety Center
– FY 1980 thru FY 1990
• 204 Helicopter Losses, 57 Fatalities
• 85 of 204 Attributed to System Failures
• 54 of 85 Avoidable with health monitoring
system
– FY 1992 thru FY 1993
• 29 Mishaps
• 14 of 29 Attributed to System Failures
• 11 of 14 Preventable with health monitoring
systems
• Similar Trends for Army
– FY 1985 thru FY 1993
• 15 Class A Mishaps (CH-47D)
• 5 due to Material Defects
Byington, Nickerson, George, “Prognostic Issues for Rotorcraft Health and
Usage Monitoring Systems,” 51st Meeting of the Society for MFPT, April 1997.

8. • 1988 Survey of over 500 plants (power, paper,
metals, food processing, textiles)
– 50-80% reductions in repair costs
– 30% increase in revenue
– 50-80% reduction in maintenance costs
– 30% reduction in spares inventory
– 20-60% increase in overall profitability
Technology for Energy Corporation, as Reported in the
Handbook for Condition Monitoring, Ed. By Rao, Elsevier Science, 1996

9. • ALCOA saved $1.1M in 1992 in motor repairs alone
• Armco Steel saves $12M annually through CBM
• Oil producer reduced gas turbine outages by 20% and
eliminated lost oil production of 1100 barrels/hour
• Oil refinery produced $1M/yr savings through 29%
maintenance cost avoidance (100 major/3900 minor)
• Nuclear power plant estimated first and second year
savings of $2M and $3.5M, respectively
Rao, B.K.N, ed., Handbook of Condition Monitoring, Elsevier Science, Ltd.,
Kidlington, Oxford, UK, 1996.

10. Condition-Directed Maintenance, Electric Power Research Institute,
Compressed Air Magazine, August 1990.
$17-18
$11-13
$7-9
$3.5*

11. Condition-Based
Corrective
Preventive
Percentage of Maintenance Actions
100%
Present Future
Eliminated
Adapted from Nickerson
“Condition-Based
Maintenance” in P/PM
Technology Magazine
Cost Chart Adapted from “Machinery Oil
Analysis - Methods, Automation &
Benefits”, Larry Toms, p. 23, 1995.
= Greater Availability
= Lower Total Costs
= Better Performance
Number of Faiure Events
Cost
Condition
Based
Preventive Corrective
Total Cost
M
a
i
n
t
e
n
a
n
c
e
C
o
s
t
Operating or
Performance
Cost
Number of Failure Events

12. § Increased availability
• Early notification of degrading conditions and future failure
• Fewer unplanned failures
• Faster repair time associated with fixing minor problems
• Reduced potential for loss of service or equipment
§ Reduced cost of operations
• Reduced costs of problem identification and repair
• Reduced probability of catastrophic failure
• Reduced spares inventory and redundant equipment
• Accurate identification of problem
• Reduced maintenance actions with no fault found
• Identification of remaining useful life and recommended
remedial action
• Provides “condition” for support of condition-based
maintenance

13. • Improving current operations, maintenance, and logistics requires
more than reliability engineering and time-based maintenance
• Reliability engineering, design engineering, system engineering and
maintenance analysis are pillars of new PHM/CBM Design paradigm
• Rich source of advanced, automated diagnostics/prognostics
techniques have been demonstrated in selected applications
• PHM design tools and algorithm optimization should consider
functional models, dependencies, failure modes, symptoms,
algorithm attributes, and performance metrics
• Good detection and diagnostics =/= Prognostics, and thus will not
give all the big P benefits but it is certainly a good start for any CBM