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IBM Predictive Maintenance & Quality (PMQ) Overview
© 2013 IBM Corporation
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© 2013 IBM Corporation
Setting the Stage….
PMQ is an important product from IBM
that is made up of many components.
Participants will leave with an
understanding of the value of the
solution along with what is required to
build sales & services practices around
the offering.
David Zyla
Partner Technical Enablement Specialist
Business Analytics Division,
IBM Software Group
Anuj Marfatia
Program Director
Business Analytics Division,
IBM Software Group
Why this is Important to Know… Speaking to you today…
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Agenda
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Background & Value
Case Studies
Solution Stack
Positioning
ROI
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Success of PMQ will be based on Team selling
What is it?
A cross-SWG, packaged solution with its own PID
Utilizes technologies from SPSS, Cognos, DB2, Websphere, Infosphere, and integration to Maximo
Why should I care?
Market size of $8B
Key industry targets: Manufacturing, E&U, and Chem & Petro
Direct integration to Maximo
$325,000 avg. deal size for software only; minimum 1:1 software to services ratio
PMQ + Maximo is a key differentiator
Partners are a key channel
Several upcoming focused events in 2013 (Chicago-Oct.9, Cleveland-Oct. 15, Calgary-Oct.22, Toronto-Oct.2?, IOD (Vegas)-Nov.3-7)
What are the primary use cases?
Primary use cases
Predict asset failure
Determine anomalistic characteristics that lead to poor product or component quality
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Background & Value
Organizations forced to reduce operational costs to remain competitive
Impacts manufacturers & organizations managing field level assets
Challenge: organizations reacting and not predicting
What is the impact when …
– a manufacturer encounters a machine failure during a production run?
– a heavy machinery operator performs unscheduled repair on a bucket wheel excavator?
– a water main breaks?
– A transformer fails causing a power outage in an electrical grid?
Aberdeen study - #1 risk to operations was failure of critical physical assets
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Assets are more than just manufacturing machinery
1. Manufacturing process
Manufacturing machinery utilized to create a product
2. Field-level assets
Consumer Appliances o Washers, dryers, hot water heaters, furnaces, HVAC
Vending Machines o Food, drinks, cigarettes, electrical products, videos, money
Connected Transportation o Planes, trains, ships, tanks, buses, passenger automobiles, fleets, electric vehicles, gas
powered autos, motorcycles, snow mobiles, lift trucks
Heavy Equipment Machinery o Earth movers, mining equipment, cranes, wind/gas turbines, nuclear plants, solar panel
arrays, oil drills, oil rigs
Networks o Electrical grids, water/sewage infrastructure, IT systems, telecom lines/cables, security
systems
Buildings o Property, real estate, universities, stadiums, corporate offices, headquarters, field offices
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Predictive Maintenance is the next step towards Maintenance Excellence
Reactive Maintenance (machine fails, then fix)
Preventive Maintenance (based on manufacturers’ schedules, time, or operational observations)
Condition-based Maintenance (based on monitoring to assess condition of assets)
Predictive Maintenance (based on models of evolution of the condition of assets)
Source: Gartner
Maintenance Maturity Model
Managing budget costs while improving reliability and safety
Predictive Maintenance uses analytics to model foreseeable evolutions of the characteristics of individual systems or assets
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New Offering!
IBM Predictive Maintenance and Quality •Reduce operational costs •Improve asset productivity •Increase process efficiency
Accelerate Time-to-Value
Real-time capabilities
Big data, predictive, and advanced analytics
Quick and accurate decisioning
Maximo integration
Open architecture
Business intelligence
Singular software capabilities
(SPSS, Cognos)
Customizable, cross-IBM, software and services solution
(Analytics with real-time data integration)
Packaged, cross-IBM, software product
(Analytics with real-time data integration)
2012
Q1 2013
TODAY!
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Severity Factors
•Health and Safety Issues
•Asset Damage / Repair Costs
•Loss of Revenue
Predictive Maintenance and Quality delivers significant value where both the impact of failure and the probability of failure are high
Greatest need for Predictive Asset Optimization
Lower need for Predictive Asset Optimization
© 2013 IBM Corporation
• 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
IBM Predictive Maintenance and Quality reduces operational costs, improves asset productivity and increases process efficiency
Combined with out-of-box models, dashboards, reports and source connectors
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Business Use Case Business Value
Predictive Maintenance and Quality generates business value for organizations
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
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
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Where are my opportunities?
Industry
PMQ Categories
Key Opportunities by
Region Manufacturing Consumer
Appliances
Vending
Machines
Connected
Transportation
Heavy
Equipment
Machinery
Networks Buildings
Automotive X X X -North
America
-Japan
-Western
Europe
-Eastern
Europe
-South Korea
-India
-Brazil
-Russia
Aerospace and
Defense X X X -North
America
-Brazil
-China
-Middle East
-Western
Europe
-Sweden
Chemical &
Petroleum X X X -Middle East
-Russia
-North
America
-Brazil
-Venezuela
-Nigeria
-Nordics
Consumer
Packaged
Goods X X X X
-US
-Japan
-China
-South Korea
-Western
Europe
Electronics X X -Japan
-South Korea
-US
-Germany
-China
Energy &
Utilities X X X -Western
Europe
-US
-India
-China
Mining /
Construction X -Australia
-Western
Europe
-Brazil
-North America
-China
-South Africa
-Sweden
Government X X X -North
America
-Western
Europe
-Japan
Travel &
Transportation X X -US
-Japan
-Canada
-China
-India
-Denmark
-Switzerland
-Germany
Telco X -China
-Western
Europe
-India
-Mexico
-US
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Case Studies – Predict Asset Failure / Life
• 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
• 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
Environment Enterprise Asset Mgmt
• A regional utility company needed to maintain an aging infrastructure
• IBM delivered an industry-specific solution to detect potential problems before they occur
Outcomes: • Improved asset maintenance
identification • 20% productivity gains for
service trucks • Up to 20% reduction of fuel
costs due to fewer truck rolls
Extend Life
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Case Studies – Predict Quality
• A global manufacturing company wanted to more quickly detect part defects
• IBM implemented an early detection model to detect part defects earlier and respond in the most optimal way
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
Global manufacturing company
Global auto manufacturer
• 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
Predict Production Quality Predict Part Quality
• 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%)
Predict Part Quality: Anomalies
Not for profit company
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Solution Stack
Integration Bus (Message Broker)
End User Reports, Dashboards, Drill Downs
High volume streaming data
Telematics, Manufacturing Execution Systems,
Legacy Databases, Distributed Control
Systems
Enterprise Asset Management Systems
Analytic Datastore (Pre-built data schema for storing quality, select machine and prod data, configuration)
Predictive Analytics
Decision Management
Business Intelligence
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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
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Predictive Maintenance and Quality analyzes data from multiple sources and provides recommended actions, enabling informed decisions
Asset Maintenance Asset Performance Process Integration
Collect & Integrate Data Structured, Unstructured,
Streaming
Generate Predictive & Statistical Models
Conduct Root Cause Analysis
Display Alerts and Recommended Actions
Act upon Insights
Predictive Maintenance and
Quality
• Data agnostic • User-friendly
model creation • Interactive
dashboards • Quickly make
decisions
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Predictive Maintenance and Quality provides several key features
Accelerated Time-to-Value
Big Data, Predictive and Advanced Analytics
Open Architecture
Business Intelligence
Real-time capabilities
Quick and Accurate Decisioning
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Maximo integration
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IBM PMQ contains adapters for IBM Maximo, which allow data integration
IBM PMQ uses existing Maximo infrastructure for data integration
Maximo Upstream Module (Master Data Loading)
– IBM PMQ can consume master data residing in IBM Maximo
– IBM PMQ mirrors the asset data that is managed in IBM Maximo.
– An automated process can be designed to synchronize data between IBM PMQ
and IBM Maximo
– Data that comes from IBM Maximo must be updated and maintained in IBM
Maximo. It is not possible for changes that are made in IBM PMQ to be propagated
back to IBM Maximo
Maximo Downstream Module (Work Order Creation)
– IBM PMQ generates recommended actions which can be passed to IBM Maximo
– IBM PMQ can be customized to import IBM Maximo work orders as events to
record activities such as inspections and repairs.
Maximo Integration Overview
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Positioning
Targeting and Qualifying the right customer with the right problems
– Operating high cost, high value assets OR sufficient quantities of lower cost assets with recurring
failures that could be predicted and prevented
– Sufficient investment or desire for asset instrumentation and maintenance / asset history to
populate models
– Reasonably mature maintenance processes
– Primarily enterprise organizations
– Pricing based on fixed price (by asset type) and a variable data point price
Not a technology sale
– Selling better maintenance outcomes to maintenance professionals
– We must be very focused on Return on Investment and Operational Improvements
– Optimizing all aspects of asset operations, not just predicting failure
Not a technology sale….however
– Embedded technology justifies the higher investment and competitive distinction
– Leverage the Industrial Internet of intelligent devices, assets, and content/data sources
– Applying principles of Big Data Analytics to a maintenance setting
– Closed Loop Integration with Maximo
– Integrated Rules-Based Decision Making
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Positioning for joint Maximo and Business Analytics value
Maximo Install Base
– Helps to justify investment or solidify ROI of Maximo implementation
– Strengthens overall commitment to value of IBM solution
– Re-energizes relationships
– Potentially justifies expansion of Maximo solution into other areas of the business
Maximo and PMQ White Space
– Maximo and PMQ together strengthens overall solution in competitive situations
– PMQ may offer a Trojan horse scenario for competitive take-outs
– PMQ can introduce an IBM Maintenance solution into a competitive installation/site
• May offer a Trojan Horse scenario for competitive take-outs
– Business Analytics / PMQ have a LOT of sellers, expanding the potential reach of IBM’s
Maintenance Solution conversation
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Partner Strategy
Traditional Maximo implementation and resale partners
– Critical to expand deployment options beyond IBM
– Leverage their existing customer relationships
– Partners want to be able to add more value and differentiated solutions
– Partners to provide industry focus/customization
Large System Integrators, OEMs and Maintenance Outsourcers
– Introduce PMQ to become part of their “tool kit”
– Use Maximo and PMQ combined to enable more compelling and cost effective maintenance
contracts
– Enhance profitability of fixed price maintenance outsourcing agreements
– Embed PMQ as part maintenance support contracts for manufactured or re-manufactured assets
Skill set required
– SPSS Enterprise certification
– Partners with expertise in Business Analytics or Maximo will find most value
– Software will need to be configured to customers’ data
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ROI that Organizations are Seeing
Auto manufacturer
– Reduction in warranty claims from 1.1 to 0.85 per vehicle
– 5% reduction in warranty claims
– Reducing the reject rate within 15 months by 80% by the specific attachment of heating elements and other measures
– Production loss of 3 days at 2 machines could be prevented in 35 minutes (€ 200,000 savings)
Office appliance manufacturer
– Increases revenue by USD104.93 million in the first year
– Production up to four times more efficient
– Lets thousands of employees optimize production line variables to support low-cost, standardized production of high-quality products
HVAC manufacturer
– Reduced warranty claim processing times by 20 to 30 percent, increasing internal efficiency and boosting customer satisfaction
– Enabled the company to identify fraudulent claims prior to payment and minimize financial losses
– Reduced support personnel required to maintain multiple warranty systems by 5 to 10 percent, eliminating duplicate efforts and lowering
costs
Energy provider
– Reduced costs by up to 20% by avoiding the need to restart turbines after an outage – an expensive process.
– Saved approximately USD 75,000 in fuel costs per turbine by identifying inefficient fuel usage.
– Increased the efficiency of maintenance schedules, costs and resources, resulting in fewer outages and higher customer satisfaction.
– Provides early warning of certain types of failure up to 30 hours before they occur, instead of 30 minutes.
Water utilities – 36 percent reduction in customer calls through increased preventive maintenance and implementation of automated meter readings
– Increased percentage of emergency investigations dispatched within 10 minutes from 49 percent to 93 percent
– Ability to generate reports for regulatory compliance and management review in seconds versus days
– Significant reduction in asset downtime
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Revenue
Growth
Operating
Margin Shareholder
Value
Capital
Efficiency
Improved
revenue growth
Improved
Cost position
Improved Working
capital position Fixed Asset
Improved
efficiency of capital
outlays
Cost per Ton
Higher
Productivity
Increased Up Time
Mechanical Availability
% scheduled
Component Life
Component Rebuild Cost
Mean Time Between Stops
Mean Time to Repair
Tons per Hour
Fewer Spares
Number of Spares
TCO Per Spare
Maintenance cost
Maintenance
Key Performance Indicators Value Drivers Financial Impact
Inventory Fewer Spare Parts
/ Components Average Spare Parts /
Components Inventory
Renewal Cost
Risk
Mitigation
Reduced Risk
Safety /
Compliance
Infrastructure Dedicated Shop space
Labor resources
Parts consumption
% field repairs
% improvement / ton
Availability Index
% scheduled Maintenance
Comp Life Target Achieved
Comp replacement cost
MTBS
MTTR
% improvement / Hour
Average Inventory value,
major components
Average inventory value
Spare Parts / Components
Inventory
Maintenance Ratio
Parts Ratio
Predictive Maintenance Value
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Resources and Final Thoughts
Sales kit exists on PartnerWorld
– Business Analytics/SPSS section or just type in Searchbox
Predictive Maintenance collateral exists on ibm.com
Business Analytics Partner Channel Contacts
– BA Software Sales North America
• Craig Wacaser [email protected]
– BUE Business Partner Solutions and Growth Strategy
• Brad Jeffers [email protected]
– BUE WW BI/AA Channels
• Michael Bigenwald [email protected]
© 2013 IBM Corporation
1. the value of PMQ and which organizations would benefit from it
2. which IM and BA components are included in the solution
3. what’s required to build sales & services practices around PMQ
After attending this session, you should have an understanding of…
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Questions
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Resources
Business Analytics area on PartnerWorld
Business Analytics Web Seminars
Business Analytics events
Business Partner Learning Center
Demand Generation Programs
Demonstration content
BA Demomate Interactive Demos
Business Analytics competitive resources
Self Paced Virtual Classroom Program for Business Partners
You Pass, We Pay
IBM Business Partner Locater Tool
IBM Business Partner Communities
Follow us on twitter ibm_ba_partner
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Replays of this session
This session is being recorded and can be downloaded for replay from the the Web
Seminar Schedule
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