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Predictive
Maintenance
Enhance your Maximo investment with
predictive capabilities to further improve
productivity, determine asset health and
reduce risk
Andrew Condos
Senior Product Consultant – Watson IoT Analytics
FMMUG18 :: Seattle 1
IBM Predictive Maintenance and Optimization (PMO) complements
IBM Maximo to obtain greater value from critical assets
Maximo
• Support maintenance activities from initial service
requests through planning, completion, recording
of results
• Capture details about asset infrastructure, spare
parts, performance, and work history
• Plan demand, streamline purchasing processes,
ensure contract compliance
• Prescribe lowest-cost, highest-utilization workforce
schedules
• Reduce overall risk, comply with appropriate
regulations
Predictive Maintenance
• Models calculate asset health scores and
predict asset life spans
• Real-time interactive dashboards monitor
assets and processes
• Detect asset failures and quality issues earlier
than standard statistical control processes
• Explore asset performance information to
determine root-cause of failure
• Provide optimized maintenance
recommendations to operations and
maintenance personal
FMMUG18 :: Seattle 2
work & asset management,
planning & scheduling, supply
chain, health & safety
asset + instrumentation + data
+ connectivity + analytics +
monitoring + reporting
MAHI vs Predictive
FMMUG18 :: Seattle 3
MAHI Predictive
Knowledge base
Known causations / Tribal
knowledge
Historical data
Time to Value Immediate Dependent on data sources
Logic Formulas
Predictive algorithms –
structured & unstructured data
Data requirements Minimal to start 6 months or greater
Maximo dependent Yes No
Application
Condition Assessment
Preventive Maintenance
Repair and Replace
Predictive & Prescriptive
Maintenance
Advanced Algorithms
Reliability Engineering
© 2015 IBM Corporation
Maximo Asset
Management
Predictive
Maintenance
description,
location,
material
types,
processes,
products,
suppliers…
4
Base data from Maximo used in Predictive
Maintenance
© 2015 IBM Corporation
Analyze data to develop predictive
models
data sources
identify relevant
data sources
develop optimum
model(s)
apply modeling
algorithms
maintenance
sensor health
top failure reasons
integrated health
feature based
custom
ensemble
industry-specific assets
5
• maintenance logs
• inspection reports
• repair invoices
• customer complaints
• warranty claims
• operator profiles
• test results
• maintenance logs
• inspection reports
• repair invoices
• customer complaints
• warranty claims
• operator profiles
• test results
© 2015 IBM Corporation
Transform asset performance data into
action
6
initiate work order with recommended actions
modify maintenance schedule
modify production schedule
conduct root cause analysis
review operator procedures
modify process design
initiate service call
develop new service or warranty program
optimize parts inventory & locations
initiate supplier review
conduct root cause analysis
modify process design
modify product design
• maintenance logs
• inspection reports
• repair invoices
• warranty claims
acquire analyze model optimize decisions
asset performance
product quality
monitor
act
model
© 2015 IBM Corporation
Acquire data to gain understanding of asset
performance
7
unstructuredstructured
• maintenance logs
• inspection reports
• repair invoices
• customer complaints
• warranty claims
• operator profiles
• test results
device-,asset-andindustry-
specificanalytics&models
• Which data best predict performance?
• What are the main factors for failure?
• When is this asset most likely to fail?
• What is the optimum maintenance schedule?
• What are the most effective repair procedures?
• What are the key variables in manufacturing
variance?
• Should we modify the warranty program?
© 2015 IBM Corporation
Automatically initiate or update Maximo work
orders with recommended actions
Nidal Cruz A. Withers
When removing the PM rotating assembly from the motor care must be taken to overcome the inherent magnetic forces
that will try to hold the rotating assembly (rotor and shaft) in the stator winding. It is recommended that the motor be
disassembled and reassembled in a vertical drive end shaft up position using a hoist to remove the rotating assembly.
In the horizontal position first remove any accessory items (fans, blower, feedback devices, etc.) Also remove the bearing
inner cap bolts (if provided). Mount the motor in a vertical drive end shaft up position and remove the drive end bracket.
The opposite drive end bracket can remain installed. The thread in the end of the shaft can be used with an eye bolt to lift
the rotating assembly with the hoist out of the frame/winding stator.
North Shore
Inspection
BluMark
Beta-Q
update an existing work order with
maintenance recommendations
8
© 2015 IBM Corporation
Predictive analytics can benefit any asset-
intensive industry
9
Demonstration
FMMUG18 :: Seattle 10
Q&A
FMMUG18 :: Seattle 11

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IBM Maximo Predictive Maintenance FMMUG 2018

  • 1. Predictive Maintenance Enhance your Maximo investment with predictive capabilities to further improve productivity, determine asset health and reduce risk Andrew Condos Senior Product Consultant – Watson IoT Analytics FMMUG18 :: Seattle 1
  • 2. IBM Predictive Maintenance and Optimization (PMO) complements IBM Maximo to obtain greater value from critical assets Maximo • Support maintenance activities from initial service requests through planning, completion, recording of results • Capture details about asset infrastructure, spare parts, performance, and work history • Plan demand, streamline purchasing processes, ensure contract compliance • Prescribe lowest-cost, highest-utilization workforce schedules • Reduce overall risk, comply with appropriate regulations Predictive Maintenance • Models calculate asset health scores and predict asset life spans • Real-time interactive dashboards monitor assets and processes • Detect asset failures and quality issues earlier than standard statistical control processes • Explore asset performance information to determine root-cause of failure • Provide optimized maintenance recommendations to operations and maintenance personal FMMUG18 :: Seattle 2 work & asset management, planning & scheduling, supply chain, health & safety asset + instrumentation + data + connectivity + analytics + monitoring + reporting
  • 3. MAHI vs Predictive FMMUG18 :: Seattle 3 MAHI Predictive Knowledge base Known causations / Tribal knowledge Historical data Time to Value Immediate Dependent on data sources Logic Formulas Predictive algorithms – structured & unstructured data Data requirements Minimal to start 6 months or greater Maximo dependent Yes No Application Condition Assessment Preventive Maintenance Repair and Replace Predictive & Prescriptive Maintenance Advanced Algorithms Reliability Engineering
  • 4. © 2015 IBM Corporation Maximo Asset Management Predictive Maintenance description, location, material types, processes, products, suppliers… 4 Base data from Maximo used in Predictive Maintenance
  • 5. © 2015 IBM Corporation Analyze data to develop predictive models data sources identify relevant data sources develop optimum model(s) apply modeling algorithms maintenance sensor health top failure reasons integrated health feature based custom ensemble industry-specific assets 5 • maintenance logs • inspection reports • repair invoices • customer complaints • warranty claims • operator profiles • test results • maintenance logs • inspection reports • repair invoices • customer complaints • warranty claims • operator profiles • test results
  • 6. © 2015 IBM Corporation Transform asset performance data into action 6 initiate work order with recommended actions modify maintenance schedule modify production schedule conduct root cause analysis review operator procedures modify process design initiate service call develop new service or warranty program optimize parts inventory & locations initiate supplier review conduct root cause analysis modify process design modify product design • maintenance logs • inspection reports • repair invoices • warranty claims acquire analyze model optimize decisions asset performance product quality monitor act model
  • 7. © 2015 IBM Corporation Acquire data to gain understanding of asset performance 7 unstructuredstructured • maintenance logs • inspection reports • repair invoices • customer complaints • warranty claims • operator profiles • test results device-,asset-andindustry- specificanalytics&models • Which data best predict performance? • What are the main factors for failure? • When is this asset most likely to fail? • What is the optimum maintenance schedule? • What are the most effective repair procedures? • What are the key variables in manufacturing variance? • Should we modify the warranty program?
  • 8. © 2015 IBM Corporation Automatically initiate or update Maximo work orders with recommended actions Nidal Cruz A. Withers When removing the PM rotating assembly from the motor care must be taken to overcome the inherent magnetic forces that will try to hold the rotating assembly (rotor and shaft) in the stator winding. It is recommended that the motor be disassembled and reassembled in a vertical drive end shaft up position using a hoist to remove the rotating assembly. In the horizontal position first remove any accessory items (fans, blower, feedback devices, etc.) Also remove the bearing inner cap bolts (if provided). Mount the motor in a vertical drive end shaft up position and remove the drive end bracket. The opposite drive end bracket can remain installed. The thread in the end of the shaft can be used with an eye bolt to lift the rotating assembly with the hoist out of the frame/winding stator. North Shore Inspection BluMark Beta-Q update an existing work order with maintenance recommendations 8
  • 9. © 2015 IBM Corporation Predictive analytics can benefit any asset- intensive industry 9