condition based maintenance for electronics · condition based maintenance rcm environment...

© 2004 - 2007 © 2004 - 2010 9000 Virginia Manor Rd Ste 290, Beltsville MD 20705 | 301-474-0607 | www.dfrsolutions.com © 2004 – 2010

Condition Based Maintenance

A predictive approach for electronics

October 22nd, 2015

© 2004 - 2007 © 2004 - 2010 9000 Virginia Manor Rd Ste 290, Beltsville MD 20705 | 301-474-0607 | www.dfrsolutions.com

Condition Based Maintenance

RCM

Environment

Reliability

Documentation

Program

A New Concept for Electronics

Condition Based

Maintenance (CBM) is a

maintenance strategy that uses the

actual condition of the asset to

decide what maintenance needs

to be done.

CBM dictates

that maintenance should only be

performed when certain indicators

show signs of decreasing

performance or upcoming failure.


o Rio Grande Railway Company (1940’s) o Oil analysis for fuel and glycol

o US Army (50’s through 70’s) o Continued exploring ways to monitor condition

o Big Data (80’s and 90’s) o Explosion of monitoring data

o Decision Making (2000’s – present) o What does it all mean

o How to make use of the data

o Policy and Guidebook Creation o IAEA (TECDOC-1551)

o DoD (DoDI 4151.22, CBM+ DoD Guidebook)

o ISO 17359: Condition monitoring and diagnostics of machines

Wiseman, Murray. 'Omdec.Com :: A History Of CBM (Condition Based Maintenance)'. Omdec.com. N.p., 2015. Web. 18 Oct. 2015.

CBM: An evolving process


o Corrective maintenance (CM)

o High cost

o Least predictable

o Run to failure – gets the most from the equipment

o Preventive maintenance (PM)

o Most easily scheduled

o Reduced unplanned downtime

o Higher logistics cost

o Condition based maintenance (CBM)

o Reduced unplanned downtime downtime

o Lower logistics cost

o Run to within some percentage of failure

The Goldilocks method for maintenance?


o No one answer is universally appropriate

o Corrective maintenance

o Good for consumables and commodity level equipment

o When unexpected downtime is acceptable

o When secondary failure effects are minimized

o Planned maintenance

o Good for systems that do not have a means to monitor key performance indicators (KPI)

o Where unplanned downtime is less acceptable

o When secondary failure effects may be severe

o CBM

o Systems where KPI are available

o Where degradation models are available to interpret KPI

o To augment, not replace CM and PM

CM, PM, or CBM?


o Motor vehicles come with a manufacturer-

recommended interval for oil replacements.

o These intervals are based on manufacturers’ analysis, years of

performance data and experience.

o However, this interval is based on an average or best guess

rather than the actual condition of the oil in any specific

vehicle.

o The idea behind CBM is to replace the oil only when a

replacement is needed and not on a predetermined

schedule.

Example

https://www.maintenanceassistant.com/condition-based-maintenance/


o Now there are two types of CBM systems for motor oil

o Most CBM for motor oil is based on sensors throughout the

drivetrain send information about engine revolutions,

temperature and driving time to the car's computer.

o The data is run through a mathematical algorithm that predicts when

the oil will begin to degrade.

o Some CBM uses direct measurement of the quality or

physical property of the oil itself

Real-World Example of CBM

http://www.edmunds.com/car-care/oil-life-monitoring-systems.html


o To make the process less onerous, prioritize the assets

for which CBM might make sense based on what

happens when an asset or component fails.

o If the consequences of failure are catastrophic (large loss of

production, major safety risk), then CBM might be

appropriate.

o Compare the cost of failure or use-based maintenance

with CBM for a given asset and factor in the

approximate value of the asset failing to prioritize

candidate CBM assets.

http://www.plantservices.com/articles/2006/199/

Process


Apply six steps to your prioritized short-list of assets and

components.

The example provided is for a cooling water system where

out-of-range water temperature may have catastrophic

consequences.

1. Determine operating context for the asset being analyzed

(cooling water system is to maintain water between 40°F

and 45°F).

2. Define the asset’s functions (maintain water temperature

and contain water in the tank).

3. Assess possible failures (water too hot or too cold).

Six Steps


4. Identify possible failure modes or root causes (heat

exchanger fouled, valve closed, pump bearing fatigued).

5. Determine the most probable failure effects for each

failure mode (inefficient heat exchanger results in higher

utility cost, extra cooling tower sections in operation,

eventual inability to deliver quality parts).

6. Propose an appropriate maintenance task for each failure

mode using failure history, probability and costs to

compare financial and technical feasibility of corrective,

preventive or predictive actions (monitor heat exchanger

efficiency)

Six Steps (cont.)


“There is an upfront investment, which varies with the scale of the

utility and the scope of their implementation,” says Shawn

Lyndon, Senior Vice President & General Manager of Asset

Health Solutions at ABB. “But the payback is fairly swift,

typically in the two- to three-year range.”

According to an ABB analysis, a catastrophic transformer

failure can cost from three to 10 times the price of the

equipment itself. Considering the fact that CBM is much more

likely to identify transformer problems prior to failure, the

financial prudence of monitoring transformer health becomes

even clearer.

ROI


o Understanding the condition

o Monitoring KPIs

o Tracking performance degradation

o Understanding the equipment degradation rate

o Tracking KPIs over time

o Account for anticipated changes in loading

o Determining maintenance threshold

o When does degradation become failure?

o Historical data trending and analysis

CBM: How does it typically work?


o Vibration analysis – rotating equipment such as compressors, pumps, motors all exhibit a certain degree of vibration. As they degrade, or fall out of alignment, the amount of vibration increases. Vibration sensors can be used to detect when this becomes excessive.

o Infrared – IR cameras can be used to detect high temperature conditions in energized equipment

o Ultrasonic – detection of deep subsurface defects such as boat hull corrosion

o Acoustic – used to detect gas, liquid or vacuum leaks

o Oil analysis – measure the number and size of particles in a sample to determine asset wear

o Electrical – motor current readings using clamp on ammeters

o Operational performance – sensors throughout a system to measure pressure, temperature, flow etc.

Types of condition monitoring

https://www.maintenanceassistant.com/condition-based-maintenance/


o The degradation EFFECTS of the use environment are measured directly

o Symptoms assessed against historical thresholds and risk

Traditional CBM Example: Motor

Vibration Thermography Tribology

Analysis

Diagnosis

Maintenance


o The effects of environmental degradation rarely

provide measurable symptoms in electronics

o Binary state: It works or it doesn’t

o Historically run to failure or replaced periodically based on

historical information

o Requires measuring the use environment directly and

CALCULATING the degradation to determine the

condition

CBM in Electronics


o Understanding when a specific part will fail, given the

environment it is being exposed to

o Enabled by advancements in reliability physics

o Powered by advancements in application technology

o Why wouldn’t you use it to inform a more streamlined

maintenance program?

CBM: Application for Recently Practical PoF


o Physics of Failure: A formalized and structured approach to Root Cause Failure Analysis that focuses on understanding and not only fixing a current problem.

o To achieve an understanding of “Cause and Effect” failure mechanisms AND the variable factors that make them “Appear” to be irregular events

o Combines Material Science, Physics and Chemistry with Statistics, Variation Theory and Probabilistic Mechanics

A marriage of deterministic science with probabilistic variation theory for achieving comprehensive product integrity and reliability-by-design capabilities.

Physics of Failure


Wearout


Wearout: Damage Accumulation

4

| 99

%t i le

2

|

69

%tile

3

| 93

%tile

INITIAL UNRELIABILITY

FREQUENCY OF OCCURRENCE

STRESS/ STRENGTH

STRESS EXPOSURE TIME or USAGE

CYC’S

Material Decay Increases

UNRELIABILITY OVER TIME

STRESS INDUCED DAMAGE

ACCUMULATION Design’s Strength

Decay/Spreads Over Time / Usage


Reliability Simulation

o Inputs o Environmental stresses

o Design properties

o Damage models

o Outputs o Damage accumulation

o Time (remaining) to failure

Simulation Aided Condition Monitoring

Vibration Thermal Power States

Damage Models

Prediction

Maintenance

Design

Maintenance Scheduling o Fault Tolerance Analysis

o FMEA

o Safety Analysis

o Rework o Solder joints

o Component replacement

o Replacement o Logistics Scheduling

o Design Modification


o A problem of complexity

o There and back again

Input Requirements: Design and Materials

Box

PCBA

Components

Materials

Granularity

Behaviors and Effects


o Design files build from the part up

o Analysis builds up the model the same way

o Databases of materials properties

o Databases of component models

Managing physical complexity

o Automated PCBA model building

o Multi-board assemblies/Box level


o Structured vs unstructured data

o Structured data is ready for analysis

o Unstructured data follows different formats

o Often difficult to compile systematically

o Much of environmental data is typically unstructured

o Environmental stress types

o Life cycle phases

o Stress events

Describing The Use Environment


o Life cycle editor

o Handles complex environments

o Shock

o Sinusoidal vibration

o Random vibration

o Thermal Cycling

o Power Cycling

o Formats environmental stresses as

inputs for analysis

Structuring the Environment


o Each failure mechanism is modeled separately

o Drawing stresses from environment inputs

o Applying and assessing effects on each design and material

input

Predictive Models

211

2

2

1 11exp

TTK

E

V

V

t

t

B

a

n

)%063.0exp(~51.0~

exp RHkT

eVT f

aGGA

h

GA

h

AE

L

AE

LFLT

bcc

c

ss

s

9

2

221112


o Component level damage calculated

o Time to failure in current environment

o Each failure mechanism modeled separately

o Solder Joint fatigue

o PTH fatigue

o Mechanical overstress, etc

Applying Damage Accumulation Models


o How do you calculate the reliability at the solder joint

level and roll up to the box level?

o Manual calculations are onerous

o Typically only done during design or failure analysis

o Critical components

o Between the design files and the environment analysis

all the information exists to automate the process

Batch Processing


o Data Input o Parses standard EDA files (schematic, layout, parts list) automatically

o Uses embedded libraries (part, package, materials, solder, laminate)

o Can build box-level finite element analysis model in minutes

o Sherlock Analysis o Produces holistic analysis critical to develop reliable products

o Easy to assign and create standard structures and conditions

o Assessment options include: Thermal Cycling, Mechanical Shock, Natural Frequency, Harmonic Vibration, Random Vibration, Bending, Integrated Circuit Wearout, Thermal Derating, Failure Rate, Conductive Anodic Filament, High Fidelity PCB Model

o Report & Recommend o Presents results in multiple formats: Tabular / Histogram / Life curve /

Overlay

Automated Design Analysis™ Process


o Import Standard Design Output Files (Gerber/ODB)

Capturing Design Information


Applying Material Properties

o Embedded / Fully Populated Libraries: o Parts/Package/Laminates/Materials/Solder


o FEA 3D Modeling

o Shock/Vibration Analysis

o Fully 3D elements for the PCB, components and mount points

o Simulation accuracy

o Meshing algorithm

o Sub-assemblies, heat-sinks, chassis analysis

o FEA Engine

o Multi-core and 64 bit support

o Faster analysis

Stress Analysis


Thermal Cycling Fatigue

o Cumulative Damage Index (CDI)

o Time to failure

o Thermal profile and Flowtherm results

Thermal Fatigue Analysis


o Vibration/Shock/Bending

o Loading

o Mounting

o Direction

Mechanical Overstress and Fatigue Analysis


Time-Dependent Reliability Results Summary

Constant Failure Rate Generic Actuarial MTBF Database

PTH Thermal Cycling Fatigue

Thermal Cycling Solder Fatigue

Vibration Fatigue

Over All Module

Combined Risk


o Condition

o Design life minus damage percentage

o 100% damage = failure

Applications for Maintenance

Granularity

LRU-Box Level

SRU-Board Level

Component Level

o Maintenance decisions can be made at the most appropriate level o LRU Replacement

o SRU Services

o Component Rework


Benefits


o Less downtime

o Grouping repair/rework requirements (all expected failures in next 3 years, for example)

o Eliminates multiple failure events

o Only the failed component is identifiable

o Components near failure still appear deceptively functional

o Customer Perception

o Component replacement or refurbishment routine

o Non-emergency setting

o Corrective maintenance rarely necessary

o High reliability applications

o Lower risk of failure at critical times

Reduction in unplanned downtime


o Spare parts allocation

o Tracking condition as it evolves and scheduling replacement

allows for lower lead time requirements

o Reduced reliance on stockpiling against unexpected failure

o Reduces collateral damage at point of failure

o Secondary failure modes

o Expensive catastrophic system failure less likely as a result of

electronics failure

Logistics Scheduling


o Reduce catastrophic board failure

o Lower replacement requirements

o Selective repair preserves assemblies

o Extends asset time for long life requirements

o High reliability applications

o Components expensive/difficult to source

o Appropriate end of life buys

o Reduces the need for Gray Market sourcing

o Critical as systems are more frequently required to

fulfill unexpected extended lifetime expectations

Obsolescence


Challenges to CBM for

Electronics


o Collecting and applying use environment information

o Current CBM practices monitor equipment

o New system will monitor and apply ambient conditions

o Aligning administrative processes

o Need to coordinate with current CBM programs

o Requires an additional expertise to set maintenance

policy

o Mechanically savvy system operators

o Electronically savvy system operators

o Will require some process development

o Repair directives and procedures

o Determine how far out to look

Integration with emerging CBM programs


o Design files not often resident with user

o May be an additional level down (ODMs, Subcontractors, etc.)

o Participation of designer

o Design file inputs

o Aggregated reliability model

o Scrubbed for sensitive IP

o Participation of user

o Collation of environmental data

o Tracking material condition (damage amounts)

o Feeding back reliability information to designer for next generation

Applying Collaborative Engineering Principles


o Further increase in granularity

o Moving beyond Reliability Centered Maintenance

(RCM)

o Applying worst case realistic environments to population

o Allows for individualized maintenance plan for each

device

o Requires more rigorous recordkeeping

o Traveling documentation

o More rigorous serialization

SN Level Documentation


o Contracting Requirements changing

o Total cost of ownership becoming more of an evaluation

criteria

o Requiring more physics of failure justification for

o Sparing

o Logistics

o Maintenance Frequency

o Business Considerations

o Competitive development bids tied closer to maintenance bids

o Potentially evaluated concurrently

Unreliability as a profit center


What’s Next?


o Proof of concept successfully performed:

o Thrust Reverser Control Unit

o http://www.dfrsolutions.com/resource-center/our-

publications/case-studies/case-study-silicon-hills-design/

o Looking for additional program interest

Moving Forward

http://www.dfrsolutions.com/resource-center/our-publications/case-studies/case-study-silicon-hills-design/

















Thank you! Ed Dodd

Director, Business Development

DfR Solutions

[email protected]

310-640-5811

mailto:[email protected]

condition based maintenance for electronics · condition based maintenance rcm environment...

Documents