Transcript Features

Presenter Name
Presenter Job Title, IBM Organization Name
Date
IBM Predictive Maintenance and
Quality
© 2013 IBM Corporation
Market forces are amplifying day-to-day issues
Customer
demands
Complex
supply chains
Raw material
price volatility
Compliance
and scrutiny
Poor Asset
Performance
Limited
Process
Integration
• #1 Risk to
Operations is asset
failure1
• Lack of visibility of
predictors across
organizational
silos
• Lack of visibility
into asset health
• High costs of
unscheduled
maintenance
Aging
workforce
Lean
operations
2
• Difficulty
synchronizing
demand and
supply
• Inability to
accurately forecast
asset downtime
and costs
• Too many manual
processes &
disparate
information
sources
• Leads to
unnecessary
process
proliferation
• Losses in
processes have
become norm
• Aging assets
pushed to limits to
meet consumer
needs
• Resource
complexity make
it harder to
respond to
changing needs
© 2013 IBM Corporation
Analytics is a key enabler in maximizing asset productivity and
process efficiency
3x
Organizations that lead in
analytics outperform those that
are just beginning to adopt
analytics by 3 times
Fig.1: Best-in-Class companies use the data
they collect more effectively, and turn that
data into actionable intelligence
83%
83 percent of CIOs cited
analytics as the primary
path to competitiveness
Fig. 2: Best-in-Class companies
leverage all technology enablers
to enhance outcomes
Source: Aberdeen Group. Asset Management: Using Analytics to Drive Predictive
Maintenance. Mar 2013.
Asset Performance
 Improve quality and reduce failures
and outages
 Optimize service and support
Source: IBM Institute for Business Value and MIT Sloan Management Review, “Analytics:
The New Path to Value”
3
Process Integration
 Optimize operations and
maintenance
 Enhance manufacturing and
product quality
Source: IBM CIO Study, "The Essential CIO"
© 2013 IBM Corporation
Assets are more than just manufacturing machinery
1. Manufacturing process
 Manufacturing machinery utilized to create a product
2. Field-level assets
 Consumer Appliances
o

Vending Machines
o

Electrical grids, water/sewage infrastructure, IT systems, telecom lines/cables, security
systems
Buildings
o
4
Earth movers, mining equipment, cranes, wind/gas turbines, nuclear plants, solar panel
arrays, oil drills, oil rigs
Networks
o

Planes, trains, ships, tanks, buses, passenger automobiles, fleets, electric vehicles, gas
powered autos, motorcycles, snow mobiles, lift trucks
Heavy Equipment Machinery
o

Food, drinks, cigarettes, electrical products, videos, money
Connected Transportation
o

Washers, dryers, hot water heaters, furnaces, HVAC
Property, real estate, universities, stadiums, corporate offices, headquarters, field offices
© 2013 IBM Corporation
New Offering!
IBM Predictive Maintenance and Quality
•Reduce operational costs
•Improve asset productivity
•Increase process efficiency
TODAY!
Q1 2013
2012
Singular
software
capabilities
(SPSS, Cognos)
5
Customizable,
cross-IBM,
software and
services
solution
(Analytics with
real-time data
integration)
Packaged,
cross-IBM,
software
product
(Analytics
with real-time
data
integration)
Accelerate
Time-to-Value
 Real-time capabilities
 Big data, predictive, and advanced
analytics
 Quick and accurate decisioning
 Maximo integration
 Open architecture
 Business intelligence
© 2013 IBM Corporation
IBM Predictive Maintenance and Quality reduces operational costs,
improves asset productivity and increases process efficiency
• Monitor, maintain and optimize assets for
better availability, utilization and performance
• Predict asset failure to optimize quality and
supply chain processes
• Remove guesswork from the decision-making
process
Combined with out-of-box models, dashboards, reports and source connectors
6
© 2013 IBM Corporation
Predictive Maintenance and Quality generates business value for
organizations
Business Use Case
Business Value
Predict Asset Failure/Extend Life
 Determine failure based on usage and
wear characteristics
Estimate and extend component
life
 Utilize individual component and/or
environmental information
Increase return on assets
 Identify conditions that lead to high
failure
Optimize maintenance, inventory
and resource schedules
Predict Part Quality
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 Detect anomalies within process
Improve quality and reduce
recalls
 Compare parts against master
Reduce time to identify issues
 Conduct in-depth root cause analysis
Improve customer service
© 2013 IBM Corporation
Case Studies
Predict Asset Failure/Life:
Enterprise Asset Mgmt
• A city government wanted to boost city
services and address infrastructure
sustainability
• IBM combines asset management
innovations, predictive modeling, and
geospatial and business analytics to
help the city improve planning,
operations and services
Outcomes:
• Anticipates saving $100,000 per year
in staff time spent on capital plan
forecasting
• Expects to reduce costs related to
project coordination, operations and
capital expenditures
8
Predict Asset Failure/Life:
Environment
• A global petroleum company
wanted to increase asset utilization
and reliability in a remote
environment
• IBM helps predict where and when
ice presents a threat to existing
drilling platforms
Outcomes:
• Produces real-time visualization of
ice floe positions and trajectory
cone forecasts
• Predictions determine whether to
move platforms — providing cost
savings
Predict Part Quality:
Anomalies
• A not-for-profit marine society dedicated
to ensuring safety and pollution
• IBM helps the company detect
anomalies in vessel monitoring systems
even under dynamic changes of ocean
conditions
Outcomes:
• Significant reduction of the cost for
detection rule construction (~1/10)
• Significant increase of detection
coverage (~ x 2-3)
• Reduction of overall maintenance cost
(demonstrated at least 10%)
© 2013 IBM Corporation
Case Studies
Global auto manufacturer
Predict Production Quality
• A vehicle manufacturer wanted to
improve its production quality
• IBM’s solution helped use real-time
data to monitor the production
quality and more quickly identify
and resolve issues
Outcomes:
• Reduced the defect rate by 50% in
16 weeks in the production of
cylinder heads
• Increased customer satisfaction
9
Global manufacturing
company
Predict Part Quality
Regional utility company
Predict Asset Failure/Life:
Extend Life
• A global manufacturing company
wanted to more quickly detect part
defects
• A regional utility company
needed to maintain an aging
infrastructure
• IBM implemented an early detection
model to detect part defects earlier
and respond in the most optimal
way
• IBM delivered an industryspecific solution to detect
potential problems before they
occur
Outcomes:
Outcomes:
• Early identification and mitigation of
enterprise component and quality
issues
• Provide insight to the health and
probability of failure for in-service
equipment maximizing uptime
• Improved asset maintenance
identification
• 20% productivity gains for
service trucks
• Up to 20% reduction of fuel
costs due to fewer truck rolls
© 2013 IBM Corporation
Predictive Maintenance and Quality analyzes data from multiple
sources and provides recommended actions, enabling informed
decisions
3
2
1
Generate Predictive
& Statistical Models
Collect & Integrate Data
Structured, Unstructured,
Streaming
Conduct Root Cause
Analysis
Predictive
Maintenance and
Quality
• Data agnostic
• User-friendly
model creation
• Interactive
dashboards
• Quickly make
decisions
Asset Performance
10
4
5
Display Alerts and
Recommended Actions
Act upon Insights
Asset Maintenance
Process
Integration
© 2013 IBM Corporation
A proven architecture based on best practices underlies Predictive
Maintenance and Quality
End User Reports,
Dashboards, Drill
Downs
Predictive
Analytics
Decision
Management
Business
Intelligence

Advanced analytics
powered by IBM SPSS
and Cognos

Data integration
provided by Websphere
Message Broker and
Infosphere Master Data
Management
Collaborative Edition,
which feeds a pre-built,
DB2-based data schema

Process Integration with
Maximo – automatic
work order generation

Includes data models,
message flows, reports,
dashboards, business
rules, adapters, and
KPIs
Analytic Datastore
(Pre-built data schema for storing quality, select machine and prod data, configuration)
Integration Bus
(Message Broker)
Telematics, Manufacturing
Execution Systems,
Legacy Databases,
Distributed Control
Systems
11
High volume streaming
data
Enterprise Asset
Management Systems
© 2013 IBM Corporation
Predictive Maintenance and Quality provides several key features
Real-time
capabilities
Quick and Accurate
Decisioning
Maximo
integration
Business
Intelligence
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Big Data, Predictive and
Advanced Analytics
Open Architecture
Accelerated
Time-to-Value
© 2013 IBM Corporation
Real-time Capabilities
Features

Conduct real-time monitoring of
assets and processes

Collect, integrate, analyze, and
report streaming information

Orchestration of events and
services for efficient processing

Connect to sensors, PLCs,
SCADA systems, databases,
maintenance logs, Big Data
streaming sources
13
© 2013 IBM Corporation
Big Data, Predictive and Advanced Analytics
Features
Leverage
descriptive, predictive, and
prescriptive analytics, as well as data
and text mining
Utilize
menu-driven interfaces
without the need for any
programming to create predictive
models
Asset
health modeling based on
real-time event data –
measurements, logs, alarms, repair
history
Product
anomaly detection detects
product uniformity issues, and outliers
providing lot inspection
recommendations
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© 2013 IBM Corporation
Quick and Accurate Decisioning
Features

Utilize the Decision Management
methodology and optimize
decisions at the point of impact,
balancing resource and costs
constraints

Combine asset and process
business rules of the organization
to enhance decisions

Conduct “what-if” simulations to
accommodate changing operational
conditions

Provide optimized decisions directly
to decision-makers
15
© 2013 IBM Corporation
Maximo Integration
Features

Integrate directly with Enterprise
Asset Management systems
such as IBM Maximo

PMQ leverages asset master
data from Maximo

Master data is synchronized
between Maximo and PMQ

PMQ generates work orders
based on analytic insight and
business rules

Act upon predictive insights
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© 2013 IBM Corporation
Open Architecture
Features

Stream data from many sources
for data aggregation

APIs for integration and
customization

Quickly expand included content
for specific industry and business
applications

Integrate directly with Enterprise
Asset Management systems
Business Process Management
or other services
17
© 2013 IBM Corporation
Business Intelligence
Features
 Monitor status and quickly address
areas of concern
 Conduct self-service query,
reporting and analysis from virtually
any data source
 Leverage the drag-and-drop studio
environment to provide real-time
views
 Experience insight wherever needed
with mobile capabilities
 Drill-down into data for additional
insight
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© 2013 IBM Corporation
Accelerated Time-to-Value
Features
 Business user interface for master data
entry and modification
 Leverage easy-to-install, pre-configured
software and content stack
 Utilize out-of-the-box data source
connectors and models, dashboards,
and reports to reduce the need for
additional services
 Quickly expand included content for
specific industry and business
applications
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© 2013 IBM Corporation
Predictive Maintenance and Quality converges Enterprise Asset
Management (EAM) and Analytics capabilities
Enterprise Asset
Management
Predictive
Maintenance and
Quality
+
 Asset maintenance history
=
 Optimized maintenance
windows to reduce operating
expense
Asset
Lifecycle
Mgmt
 Condition monitoring and
historical meter readings
 Efficient assignment of labor
resources
 Inventory and purchasing
transactions
 Labor, craft, skills, certifications
and calendars
Supply
Chain
Processes
Analytical
insights
Facilities
Operation
 Enhanced capital forecasting
plans
 Optimized spare parts inventory
 Automated analytical
techniques, including anomaly
detection for assets and sensors
 Safety and regulatory
Requirements
Staff
Planning
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Better Outcomes
 Improved reliability and uptime
of assets
© 2013 IBM Corporation
IBM offers a comprehensive end-to-end solution with Predictive
Maintenance and Quality
Infrastructure Activities
 Program and Project
Management
 Setup / installation
 Hardware
 Software
 Specialists
 Hosting
IBM
Services
+
Analytical Activities
 Solution Impact
Assessment
 Business Case
Development
 Use Case Definition
 Data Integration
 Information Modeling
 Predictive Modeling
Specialized Skills







Integration Skills
Business Consulting
Industry Skills
Maintenance Experts
Maximo Specialists
Industry Expertise
Scientists and
Mathematicians
IBM
Software
IBM
Research
Client
Value
+
+
=
IBM Systems and Technology
21
© 2013 IBM Corporation
For example, IBM has specific accelerators for the Natural Resources
Industry
Predictive Asset Maintenance for
High Value Assets (PAM)
Predictive Operations Performance
(POP)
Predictive Energy Optimization
(PEO)
Business Drivers
Business Drivers
Business Drivers
 Ensuring Production Line Continuity in Mining
(Oil & Gas in roadmap)
 Significant new constraints and operational
challenges
 Continual increase in Energy Consumption
 Improvements & Warranty Claim Cost
Reduction
 Allowing SLA models for major OEM's
 Achieving operational efficiencies in Field
Operations
 Optimizing production ;Complying with regulations
Solution
 Industry standards based (PPDM)
 Aggregates key performance criteria to optimize
operations for Oil & Gas production environments
 Leverages performance information for
process/product quality based on SPC/SQC criteria
 Provides Event and Incident management
capabilities
 Industry standards based (CCOM)
 Provides a customized information model
relevant to the industry, that will be used for
reporting and analytics
 Provides a base library of advanced analytics
specific to the industry equipment types
 Provides extension services for data
onboarding from input data sources
Benefits
 Reduced machine/appliance/asset downtime
due to (parts) failure
 Improved productivity of maintenance
resources
 Avoid costs of machine/appliance/asset
failure
 Improved customer satisfaction due to
improved service levels
 Reduced environmental impact of production
failures resulting in lower potential regulatory
fees
 Managing HSE risks, people skills and environment
issues
Solution
Benefits
 Drive optimal performance with knowledge
management and control that comes from effective
information capture ,analysis and alerting
 Support better decision making with data mining
and trend analysis
 Maximize uptime and lifting capabilities with nearreal-time monitoring and analysis of reservoir
drilling and production information
 Optimize field force efficiency by providing
collaboration automation tools
 Unify company systems for integrated upstream
operational information across the extended
enterprise
 Continual increase in Energy price trends
 Pressures of global energy policies
 Environment regulations
Solution
 Industry standards based (ISA SP95)
 Integrated energy management system
including energy generation & consumption
monitoring, prediction, forecast demand &
supply, and plan & schedule for optimized
energy use
 Provides energy optimization models based on
demand forecast from production domain
 Provides energy monitoring for
generation/usage/consumption of different types
of energy.
 Provides energy prediction based on historical
trends allowing for optimal generation
Benefits
 Provides an understanding of energy load
profiles ; Improves the management of usage,
leading to reduced costs
 Facilitates lower rate negotiations with energy
suppliers & Improves forecasting of future
energy usage and costs
 Provide business intelligence that drives phases
of energy efficiency program
Built on Predictive Maintenance and Quality Platform utilizing its core product suite and programming model
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© 2013 IBM Corporation
Why Choose IBM Predictive Maintenance and Quality?
Industry Expertise
Predictive models for a number of specific
industry use cases
Big Data, Predictive & Advanced Analytics
 An enhanced advanced analytics methodology,
tailored to the needs of the predictive
asset/maintenance space
Accelerators
 Pre-configured dashboard and visualization
templates
 Pre-integrated software tools, with connectors to a
variety of asset management solutions
Talent
A resource pool of highly talented analytic Subject
Matter Experts and Industry experts with predictive
maintenance experience
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© 2013 IBM Corporation
Next Steps
24
1
Identify which business problems are
ripe for asset optimization and cost
containment
2
Determine capability gaps regarding
infrastructure, information, and
decision-makers
3
Map a course for rapid value creation
© 2013 IBM Corporation