IOT: THE INTERFACE OF CONDITION

MONITORING & RELIABILITY

N A G I G E B R A E E LA S S O C I AT E P R O F E S S O RI N D U S T R I A L A N D S Y S T E M S E N G I N E E R I N G

BACKGROUND

• The advent of inexpensive sensor technologies and wireless communications have enabled numerous industrial IoT applications.

• Asset Monitoring and Management is one of the fastest growing industrial applications of IoT.

• Some key challenges that need to be addressed• How to combine asset monitoring data with existing reliability programs?

• How to effectively analyze and visualize asset monitoring?

• How to use these analytics to enable an efficient decision making process (maintenance/operational/logistical)?

RELIABILITY AND CONDITION MONITORING

• Difference between Reliability and Condition Monitoring

BACKGROUND

• What do we typically do in Reliability Analysis?

Cumulative Operating Time

Num

ber o

f Fai

lure

s

Cumulative Opt. Time

Pro

babi

lity

of F

ailu

re

Range of failure uncertainty

Likely failure timeMTTF or MTBF

Replaced Prematurely

Unexpected Failures

Maintenance Records

Step 1Collect/Organize

Maintenance Records

Step 2Visualize and Analyze

Failure Events

Step 3Reliability Risk Profile

BACKGROUND

• What do we typically do in Condition Monitoring?

Step 1Identify & Collect

Data Sources

Step 2Visualize & Define Baseline Patterns

Step 3Classification & Detection

Equipment ID Baselines & Standards

Historical Sensor Data

Real-time Sensor Data

Step 4Early Warning &

Severity Classification

WHAT’S THE PROBLEM?

• What is achievable using Reliability Analysis cannot be accomplished by Condition Monitoring.

• Quantifying Failure Uncertainty

• Managing and Monetizing risk

• Strategic Planning and Decision Making (PMs)

• What is achievable using Condition Monitoring cannot be accomplished using Reliability analysis.

• Visibility into the asset health

• Fault Detection and Diagnostics

Cumulative Opt. Time

Prob

abilit

y of

Fai

lure

Range of failure uncertainty

Likely failure timeMTTF or MTBF

Replaced Prematurely

Unexpected Failures

INTEGRATING RELIABILITY & CONDITION MONITORING

Condition Monitoring

Reliability

Decision Making

(Monetization)

SYSTEM INPUTS: LET’S START WITH RELIABILITY INFO.

Cost of Unexpected Failure

Cost of SparePart Stockout

Lead Time (Supplier to Warehouse)

Storage/carrying Cost (per day)

Preventive Maintenance

Reliability Risk Profile

STRETCHING RELIABILITY DATA TO ITS LIMITS

Reliability Risk Profile

Probability Distribution

Repair/Replacement Cost Function

MTTF

Optimal Repair or Replacement Time

(2.7 mons.)

Spare Part Inventory Cost FunctionOptimal Spare Part

Ordering Time(1.5 mons)

0200

400600

8001000

0

50

1000

0.02

0.04

0.06

0.08

Frequency (Hz)% of Life Accomplished (mins)

Am

plitu

de (V

rms)

EXAMPLE OF CONDITION MONITORING DATA

Ampl

itude

/Sev

erity

Lev

el

• Vibration signatures acquiredas the asset/equipmentprogresses over its lifecycle

• The figure shows post-processed vibration dataat different life percentiles of the equipment.

• Fault-specific features extracted in real-time (red dots) and modeledover time.

UPDATING RELIABILITY USING REAL-TIME CONDITION MONITORING DATA

Real-time Condition Monitoring Data

UpdatedRisk Profile

(Remaining Life)

Updated Probability Distribution

Updated Replace. Cost Function

Optimal Repair or Replacement Time

(1.3 mons.)

Optimal SpareOrdering Time

(1 week)

Updated Spare Part Inventory Cost

Function

DEMO

EXAMPLE OF DEPLOYMENT INTERFACE

Fleet Health Management System

Fleet Detections Prognostics & RUL Replacements Service Logistics

Fleet Health Management System

Fleet Detections Prognostics & RUL Replacements Service Logistics

Fleet Health Management System

Fleet Detections Prognostics & RUL Replacements Service Logistics

THANK YOU