High level overview of Condition-Based Maintenance, Machine Health Monitoring and Prognostic Maintenance. Presented at Sensors Expo, 2013 by Dr. Navid Yazdi
Coefficient of Thermal Expansion and their Importance.pptx
Sensors Expo 2013: Condition Based Maintenance, Evigia Systems
1. Integrated Wireless Multi-Sensor System for
Machine Health and Condition-Based Maintenance
Dr. Navid Yazdi
CEO, Evigia Systems, Inc.
2. Sensors Expo 2013 Evigia Systems
Condition-Based Maintenance
(CBM)
Reactive
maintenance
Preventive
Maintenance
Degradation /
Alarm-Based
Maintenance
Predictive
Maintenance
Maintenance Strategies
CBM utilizes information about the
present degradation in conditions and
performance, and their projected
evolution to minimize the downtime.
3. Sensors Expo 2013 Evigia Systems
Condition Based Maintenance
• CBM Goals:
Automated Fault Diagnosis & Fault Isolation
Determine Remaining Useful Life of the system
Enhance predictability and productivity
Improve operation profitability
sensors
Feature
Extraction
Classification Diagnostics Prognostics
Actionable
Information
CBM System Components & Information Flow
4. Sensors Expo 2013 Evigia Systems
Machine Prognosis Approaches
• Model-Driven
– Employ the system physics
model or simulations under
normal & degraded
conditions
• Data-Driven
– Pattern recognition &
machine learning applied
to monitored system data
– Detect changes, devise
trajectory and estimate RUL
• Hybrid
Prognosis
Accuracy
Increase #
of Sensors
& Types
Sensor Data
Fusion
Customized
Data
Processing
6. Sensors Expo 2013 Evigia Systems
Advanced CBM – Challenges
• Cost!!
– Adding embedded sensors,
wiring, instrumentation
– Customization of algorithms
• Sensors disruption of process
or affect performance
• CBM sensors reliability
– Accuracy over long-term
– Additional failure points &
maintenance
Operations apply preventive, CBM ,
and reactive maintenance
Wireless multi-sensor nodes shift
balance to CBM across a larger set
7. Sensors Expo 2013 Evigia Systems
Wireless Multi-Sensor Node
• Flexible and cost effective network
• Distributed & large-scale sensing
• Less disruptive and easier to embed
• Retrofit existing equipment
• Reduced size, weight, power and cost
• Energy harvesting combined with
improved sensor node energy efficiency
• Improved link reliability in industrial
environments
– ISO18000-7 low-data rate apps with robust link
and low interference
– Variations of IEEE 802.15.4 PHY including
ISA100.11, WirelessHART Millimeter scale energy harvester
Courtesy: Univ Michigan-E. Aktakka, K. Najafi
Evigia RFID-pressure-temperature sensor
8. Sensors Expo 2013 Evigia Systems
CBM Sensors
Gather high-reliability & accurate in-situ information
Sensor
Functions
Environment
Structural characteristics
Dynamics
Performance Monitoring
Oil quality & corrosion
Sense
Parameters
Temperature, vibration, shock, pressure,
acoustic levels, strain, stress, voltage,
current, humidity levels, contaminant
concentration, usage frequency, usage
severity, usage time, power, heat
dissipation, corrosion, oil quality
Sensor Data
Features
Magnitude, variation, peak level, and rate
of change
Sensor
Precision
Initial specs, calibration, low-drift, multi-
sensor data fusion
9. Sensors Expo 2013 Evigia Systems
CBM Sensor Example: Chilled-Water System
Source: Secy. to CME/WCR/JBP, 2006 - irsme.nic.in
Parameter Purpose
Water Flow Rate Chiller water flow
Diff. Temperature Heat transfer, tube fouling
Diff. Pressure across
Pump & Evaporator
Track pump performance,
Chiller tube conditions
Motor Current Motor conditions
Vibrations Condition of pump &
structures
Oil condition & wear
particle analysis
Lubricant, gears,
Thermography scan Motor control & electronics
Wall-thickness
ultrasound
Corrosion & erosion check
Eddy current test Locate leaking tubes
Airborne ultrasonic Air leak
10. Sensors Expo 2013 Evigia Systems
CH 53-K Chopper CBM
• NAVAIR state-of-the-art heavy lift
chopper by Sikorsky (UT)
• Increased complexity while require
increased reliability and longer
maintenance cycle
• Light-weight and efficient (Low SWaP+C)
• CBM Requirements:
– Local & global structural damage detection
– Loads monitoring
– Environmental monitoring
– Fleet Management
11. Sensors Expo 2013 Evigia Systems
Multi-Sensor Node: Baseline Technology
• 10’s-100’s discrete components
including sensors assembled at
board level
– Larger size (inches)
– Higher Cost ($10’s-100’s)
– Larger power dissipation
& shorter battery life ( months)
12. Sensors Expo 2013 Evigia Systems
Requirements and Challenges
• Embedded multi-sensors and equipment condition monitoring
– 5-10x smaller size & cost
• Multiple sensors
– Strain, Temperature, Vibration,
Shock/Mechanical sensors, Humidity
• Size < 0.5 cubic inches
• Weight < 0.5oz
• Energy efficient < 300μW
• Cost $5-20
• Standard based rugged wireless data link
13. Sensors Expo 2013 Evigia Systems
Solution
• Chip-scale multi-sensor prognostic sensor system
– Integration of energy efficient sensors and electronics on chip
– Mass-volume manufacturing technologies
Sensor Interface &
Control Circuitry
Digital Interface
Bus
Digital Memory
SPI/I2C Serial
Interface
Sensor Event
Management &
Real-Time Clock
IC-MEMS Micropackaged Prognostic Sensor Chip
Shock/Acceleration
Sensor
Strain Sensor
Vibration Sensor
Temperature
Sensor
Low-powerICs MEMS Sensors Wafer-Level Micropackaging
14. Sensors Expo 2013 Evigia Systems
Features, Advantages, Benefits
Feature Advantage Benefit
Multiple sensors (Strain, Vibration,
Temperature, Shock)
Multiple condition
parameters
Provide full suite of parameters
Compact size (<0.5 cubic inches) Reduces size by 10x
Enable embedding of the prognostic
sensor in equipment
Light weight (< 0.5 ounces) Reduces weight by 10x
Enable embedding of the prognostic
sensor in equipment
Energy-efficient (20-300 micro watts
average depending on mode of
operation)
Reduces power draw
Extend module power up option,
Extend battery life
Manageable cost ($5 to $20, vary by
sensor mix)
Reducing cost by 10-50x
Cost savings; Broaden usage in
submodules and systems
Optional Wireless link compatible
with the DoD infrastructure
Ease of integration in
military systems
Leverage from the installed
infrastructure; Reduce the installation
and operation costs
15. Sensors Expo 2013 Evigia Systems
Prognostic Sensor Microsystem
Temperature
Sensor
Wired Serial
Data Interface
Humidity
Sensor
Strain
Sensor
Vibration
Sensor Event-Management
And
Logic Control
Memory
M
U
X
Shock
Sensor
Capacitance
Readout
and ADC
Wireless Data
Link
Prognostic Sensor Module
Prognostic Chip PMSC-A
Flash Card
Memory
1Gb+
• Strain-Vibration-Shock-Temperature sensors with wireless data link
• Target military rotary wing aircraft (CH-53), and other defense and
industrial equipment prognostics applications
19. Sensors Expo 2013 Evigia Systems
Specifications
Sensor
Sensor types supported Low bandwidth: temperature, strain, shock; High-bandwidth: Vibration
Sensor integration 4 shock, 1 strain, 1 vibration, temperature
External Sensor Support 11 shock, 1 strain, 2 vibration
Memory
Internal EEPROM Size 16 kbit (167 to 375 low-bandwidth sensor events)
External Flash Supported
2 Gbits (> 44 million low-bandwidth sensor events, 134 million vibration sensor
samples [70 minutes total])
External Flash Interface Serial (SPI) , 2 master SPI flash memory interfaces
Timing
Input Clocks 32kHz
RTC Length 17 years
RTC Resolution 30 bits
Performance
ADC Resolution 11-bit
Sampling rate
Low-power mode: 0.125Sec-4hrs
Vibration Active: Up to 10kSPS
Digital Interface
Communications Interface 4-wire SPI slave
Supply
Voltage 2.5V - 3.3V
Current
Low-power mode (@3.3V): <30µA Instantaneous Sensors , On-Chip NVM
<320µA Instantaneous , Average : 1 sample per minute: <2µA
Vibration Active: <100µA not including external flash memory
Battery Life [500mAHr cell] >25 years in low-power mode , 1 Samp/min (not including self-discharge)
20. Sensors Expo 2013 Evigia Systems
Development and Deployment
• Energy-efficient integrated strain sensor,
vibration sensor, and 3-axis mechanical
shock sensor are complete
• Manufacturing process being qualified
(MRL4)
• Sensor & electronics IC rev 1 (TRL5)
• Single chip sensor-electronics Q1’14 (TRL 6)
• Module with wireless link Q2’14 (TRL6)
21. Sensors Expo 2013 Evigia Systems
CBM Case Study: Army TACOM
Condition Based Maintenance Plus, Return on Investment Analysis Ken Fischer (01/12/11)
US Army RDECOM-TARDEC
• Army TACOM Life Cycle Management Center is responsible
for the sustainment of all ground vehicle platforms and
supporting equipment.
• CBM+ Initiative to transition military from traditional
reactionary and time-based preventative maintenance to
deliver maintenance only upon evidence of need (CBM).
• CBM+ potential savings in:
– Reduction in direct costs of part replacement and associated
maintenance labor costs
– Reduction in inspection times, reduced logistic down times, and ability
to change the level of repair for diagnosable failure modes
– Reduction in maintenance costs due to reduced mean time to repair
(MTTR)
– Reduced mean logistics down time (MLDT) due to improved forecasting
and advanced reporting of impending failures
– Savings from logistics efficiencies as repair parts are better staged
where most needed.
HEMTT Heavy Transport
Introduced 1982
13,000 Vehicles currently in service
Operations & Support (O&S)
costs account for 60% – 80%
of the total lifetime cost for
military platforms.
22. Sensors Expo 2013 Evigia Systems
CBM Case Study: Army TACOM
Condition Based Maintenance Plus, Return on Investment Analysis Ken Fischer (01/12/11)
US Army RDECOM-TARDEC
• Sensor data acquisition system for engine, transmission, tires and batteries
– $15k estimated per vehicle for “enabling technologies” of sensors, data acquisition/processing
and infrastructure
This initial TACOM CBM study identified $26M in potential cost savings
(direct and avoided costs) for an analysis of 1045 vehicles
• DoD is looking for COTS
solutions for Wireless
Diagnostic Sensors (WDS) to
support this activity
• Lowering the costs of the
enabling sensor technologies
will have a significant ROI
impact when implementing a
CBM initiative over a large
number of vehicle systems
23. Sensors Expo 2013 Evigia Systems
CBM Case Study: Army AMCOM
AMCOM Condition Based Maintenance, AMC CBM Summit 7/18/08
US Army AMCOM, Gary Nenninger
• CBM Digital Source Collection (DSC) system for rotor aircraft, monitors 50+ sensor inputs
– UH-60, AH-64, CH-47 Aircraft outfitted with DSC sensors and communications
– Monitoring rotor characteristics, engine health, drive train health, structural health and exceedance
(over-temp, over-torque, etc.) conditions
• Sensor weight, connectivity, and robustness are major concerns in implementation
– Current CH-47 DSC sensor infrastructure is > 45 pounds
24. Sensors Expo 2013 Evigia Systems
CBM Case Study: Army AMCOM
AMCOM Condition Based Maintenance, AMC CBM Summit 7/18/08
US Army AMCOM, Gary Nenninger
• Results of AMCOM one-year CBM implementation (350 aircraft deploying DSC system):
– Significant savings of >11,000 maintenance (MMF) and ~1,300 test flight (MTF) hours
– Extended component life and improved confidence in reliability
– An estimated $101M in one-year direct and indirect cost savings
– Improved mission readiness and hours flown, adding more available aircraft to operations
5% increase in Fully Mission Capable (FMC) status is
equivalent of 1.5 more aircraft. 1,431 increased Hours
Flown is equivalent of 2 additional aircraft at OPTEMPO
MMH: Maintenance Man-Hours
MTF: Maintenance Test Flight
AMCOM One-Year CBM Implementation
~ $101M in savings from CBM trial
Impact of equipping aircraft with DSCs
25. Sensors Expo 2013 Evigia Systems
CBM Case Study: Army AMCOM
AMCOM Condition Based Maintenance, AMC CBM Summit 7/18/08
US Army AMCOM, Gary Nenninger
• True benefits: avoidance of catastrophic component failure leading to loss of life and aircraft
– Impending failure of specific AH-64 rotor bearing identified via CBM data, confirmed on teardown
2 Pilots saved
$16M aircraft saved
26. Sensors Expo 2013 Evigia Systems
Prognostics Case Study: Caterpillar
Multi-sensor Equipment Health Diagnosis And Prognosis
European Journal of Operational Research, 2007
• Prognostics and Health Management (PHM) study, analyzing health-state probability to
predict the useful remaining life of Caterpillar hydraulic pump components.
• Diagnostics is the assessment of the current and past health of a system based on observed
symptoms, and prognostics is a predictive assessment of the future health
• Uses novel multi-sensor fusion approach to adjust the weight or importance assigned to any
sensor in the PHM analysis, yielding multi-dimensional model for PHM predictions
– Temperature, vibration, oil particle count sensors
Advances in networked multi- sensor technology enable corresponding
advances in applications of diagnostics and prognostic health management
• Multiple sensors may have cooperative, complimentary
or competitive predictive qualities, PHM studies can
take advantage of multi-sensor characteristics
• Weighted multi-sensor fusion approach shows accuracy
of PHM predictions was increased by 18.5% over single-
dimensional model for Caterpillar 9J5082 Multiple hydraulic pumps and drive engine on test stand
27. Sensors Expo 2013 Evigia Systems
Case Study: Nuclear Material Storage
• Hazardous material transport and storage presents a significant maintenance challenge
– Nuclear and radioactive materials, hazardous waste products, corrosive or toxic
chemicals, volatile bulk process ingredients
• CBM enabled by custom container-mounted multi-sensors to monitor transit/storage
location, seal breakage, package impact, temperature, humidity, radiation levels, and
presence of gases and certain biological elements
Annual inspection
and monitoring direct
cost savings of over
$2,000 per container
• CBM system lowers life-cycle management costs, reduces the
requirements for manned surveillance and inspection, minimizes
the potential hazardous exposure for plant personnel, and
extends maintenance cycles of storage and transport vessels
28. Sensors Expo 2013 Evigia Systems
About Evigia Systems
Contact:
Dr. Navid Yazdi
CEO, Evigia Systems, Inc.
nyazdi@evigia.com
www.evigia.com
Twitter: @EvigiaRFID
3810 Varsity Drive
Ann Arbor, MI 48108
(734) 302-1140
• Evigia Systems (Ann Arbor, MI) develops wireless sensing, identification and
tracking products and integrated solutions for military, security, and
commercial applications
• Expertise in MEMS-based sensor development, integrated multi-sensors,
robust wireless communication, ASIC design, and Active RFID systems
• Focus on delivering sensing technology with smaller form factors, higher
energy efficiency, increased functionality, and lower production costs