Predictive Asset Optimization - Advanced Analytics

2014 IBM Proprietary

Predictive Asset Optimization

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Agenda

Part 1: Introduction to Predictive Asset Optimization (PAO) ! Smart Products Defined

! What is Predictive Asset Optimization?

Part 2: The Value of Predictive Asset Optimization

! Value Proposition & Benefit Cases

! Case Studies

Part 3: The PAO Solution

! Solution Architecture

!  IBM’s PAO-enabling Products & Capabilities



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Predictive Analytics SMEs

Paul Brody VP & Partner - Electronics Global Industry Leader

Leonard Lee Associate Partner Electronics CoC



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Smart Products – What are they?

Internet of Things Internet of People

Intelligent

Instrumented

Interconnected

Usage & Interaction

The devices and people are directly talking now…

…generating massive amounts of data.

!  Warranty information !  Purchasing history

!  User preferences !  Content viewing and

listening histories !  Usage history !  Demographics and

psychographic data !  Point-of-event feedback !  Product and service

feedback via social networking sites

Insight

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Market Trends

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Smart Products – They are changing the world as we know it!

213 549 1,042 1,6592,444

3,440

275600

978

1,402

1,839

2,288

0

1000

2000

3000

4000

5000

6000

7000

2010 2011 2012 2013 2014 2015

Non-Entertainment Install Base (MMs)

Entertainment Install Base (MMs)

Annual Sales

Install Base

0

500

1000

1500

2000

2500

3000

3500

4000

2010 2011 2012 2013 2014 2015

Worldwide IP-Connected Devices – Sales & Install Base

IP-Connected Device Install Base – Devices and Beyond

Source: Gartner, IBM analysis

488M in 2010

5.7Bn in 2015

213M devices in 2010

3.4BN devices in 2015

MM

s of

dev

ices

By 2015 - over 5 billion Internet connected consumer

products to be sold!

IP-connected products will proliferate worldwide

Products will become increasingly self-aware

IP-connected products will generate massive amounts of condition data

Business analytics will provide companies with deep customer insight



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As the number of smart products grows, companies are under increasing pressure to evolve their business focus from being product-centric to product + service minded.

Business Strategy & Model

Smart Devices

Connected Devices

Analytics

Big Data

Competitive Opportunities

Trends & Technologies



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The combination of condition data gathered from connected, smart products and predictive analytics is creating new opportunities for electronics companies to drive product and service innovations.

Big data: unstructured, semi-structured and structured

Review & rating Click-through Feedbacks via pads/phones

Sales records Consumer master data

Product master data

Monitoring & maintenance

logs

Big data: unstructured, semi-structured and structured

Online data Offline data Connected data

Data Types

Social media� Call center records�

B2C$e&commerce$

Forum,$Microblog,$Facebook…$

ERP$ CRM$ Connected$devices$

Data sources Sensors$

User 360 Product 360 •  Demographic •  Geographic

•  Socialgraphic •  Behavioral

•  Psychological

•  R&D •  Production

•  Transactional •  In-use

•  Maintenance

Indexed information

Voice of Customer

(VoC)

Targeted Marketing &

Sales Optimization

Preventive Maintenance

R&D Marketing and Sales After Sales Service

Front Office Applications



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Predictive Asset Optimization (PAO) finds synergy between Product Engineering and Predictive Analytics that enables companies to create new services around their products.

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What if you could accurately predict which characteristics tend to lead to a greater amount or frequency of failures?

What if, when an asset is scheduled for maintenance, you could predict what parts are likely to fail in the near future?

What if you could identify the characteristics that tend to increase ownership cost and downtime over the life of a system?

What if you could replace those parts that have not yet failed and avoid further unscheduled downtime?

What if you could quickly mine the thousands of logs that describe the maintenance performed on a system and determine what important observations are being logged by the maintenance team?



• Use a predefined lifetime for replacement

• Frequent unexpected failures leading to customers’ frustration

• Adaptively raise alert based on the actual condition of the product

• Precise condition monitoring is technically challenging in general

PREDICTIVE ASSET OPTIMIZATION 1.  Anomaly detection: How to classify the

present condition into good and bad

2.  Change-point detection: How to recognize change-points of the system

Predictive Asset Optimization enables the transition from static maintenance models to dynamic, condition-based maintenance models.

Time-Based Maintenance

Condition-Based Maintenance

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Sense and Measure Quality

Metrics

Monitor & Track Critical Information

Identify and Share Critical

Issues

Measure & Decide on

Actions

Propose Corrective Action

& Collaborate

Implement Corrective

Action

Models, Metrics, Algorithms

& Techniques

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Reducing maintenance & warranty costs while improving

product quality starts with a streamlined approach

"  Integration of business data sources "  Sensing of abnormal behavior "  Providing visibility on dashboards "  Analysis of leading and lagging

indicators "  Correlation/Clustering of failure

information "  Prediction models on emerging issues "  Collaborative decision-making "  Delivery of corrective measures

Predictive Asset Optimization analyzes data from multiple sources and provides recommended actions, enabling informed decisions.

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Group cases that exhibit similar characteristics.

Which parts tend to fail most often? At what rate do they fail?

Predict or Classify behavior & characteristics.

What are the characteristics of parts that perform well versus parts that fail often?

What events occur together?

Given a series of part failures, which parts are likely to fail in the future?

Associate Classify

Cluster

Data Mining

Data Mining & Predictive Modeling are the core of PAO.

Modelling unearths insights not visible to the naked eye & helps dispel myths that may have settled in over time.

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Optimization is the final piece to the Predictive Asset Optimization process.

•  Once the issue is identified, what is the next best course of action?

•  Optimization helps the business make complex decisions and trade-offs.

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UK Utility Company

In Production Line • Pro-active detection rate

increased by 90-100% • Sustained 41% reduction

in production incidents and unscheduled downtime

• Reduced liability damage by 30.23% in 2 years

PAO has delivered value to companies that have invested in developing preventative maintenance capabilities for their products and operations.

Japanese Manufacturer

In Field Services • Save $1 million in repair

costs in under 2 weeks • 12-14 times return on

investment in just 4 months

German Auto Manufacturer

In Warranty Services • Proactive identification of

systematic error patterns and their dependencies

• Reduced warranty cases from 1.1 to 0.85 per vehicle

• 5% reduction in warranty cases

• Annual savings of €30m

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!  Utilize predictive analytics to identify when equipment or complex engineering assets installed at customer sites are likely to fail

!  To predict maintenance needs in order to maximize uptime/in-service time for equipment sold to customers

!  Tie to product development to improve designs and overall product quality

!  Utilize predictive analytics to identify when internally used production machinery, equipment, and assets are likely to fail or need service

!  Perform preventive maintenance in order to maximize production uptime and minimize disruptive, costly unscheduled downtime

!  Utilize predictive analytics to identify when goods and equipment sold to customers is likely to fail in order to identify root cause for problem correction

!  To proactively address issues to reduce warranty cost and improve customer satisfaction

Predictive Asset Optimization Solution can address business needs of electronics product manufacturers at different points in the lifecycle.

Operation & Maintenance of Complex Engineering Assets

Asset Optimization of Production Lines

Asset Optimization for Field and Service Warranty

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!  Utilize predictive analytics to identify when equipment or complex engineering assets installed at customer sites are likely to fail

!  To predict maintenance needs in order to maximize uptime/in-service time for equipment sold to customers

!  Tie to product development to improve designs and overall product quality

Operations and Maintenance of Complex Engineering Assets

Operation & Maintenance of Complex Engineering Assets

!  Customers complain because of downtime due to unscheduled maintenance

!  Waste of resources and downtime due to unnecessary maintenance

!  High collateral damage expenses due to failures

!  Customer complaints due to product failures

!  High pressure on SLAs with customers

Challenges Addressed Benefits Delivered

!  Reduce machine/appliance/asset downtime due to failure in complex engineering assets

!  Improved productivity of maintenance resources

!  Avoid costs of machine/appliance/asset failure

!  Improved customer satisfaction due to improved service levels

!  Improved and more efficient root-cause analysis leading to better designs

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!  Supporting Manufacturing operations within a Manufacturing Framework

!  High costs due to downtime for unscheduled maintenance.

!  Waste of resources and downtime due to unnecessary maintenance.

!  High collateral damage costs due to failures.

!  High levels of MRO inventory.

!  Unreliable Maintenance Cost forecasts


!  Reduce machine/appliance/asset downtime due to (parts) failure resulting in increased yields and through-puts.

!  Higher quality finished goods due to reduced production variability.

!  Reduced MRO Inventories.

!  Reduce cost of machine/appliance/asset failure.

!  Reduce the environmental impact of production failures resulting in lower potential regulatory fees.

!  Improved cost forecasting

!  Improved supply chain predictability through increased reliability

!  Utilize predictive analytics to identify when internally used production machinery, equipment, and assets are likely to fail or need service

!  Perform preventive maintenance in order to maximize production uptime and minimize disruptive, costly unscheduled downtime


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Asset Optimization for Field Service and Warranty

!  High services costs due to late product issue identification

!  Customer complaints due to product failures

!  Product recalls due to late product issue identification

!  Bad press because of product issues

!  Lost sales because of bad image

!  Supply Chain issues because of product issues

!  Financial estimates of potential warranty claims

!  Structuring warranty terms for the appropriate time frame


!  Improved customer satisfaction due to improved service levels

!  Reduced services costs

!  Greater levels of financial transparency

!  Understanding part failure timing to set bounds for warranty terms

!  Identifying and resolving issues earlier in the product lifecycle process resulting in fewer warranty claims

!  Create a continuous feedback loop of previous learning from the reliability modeling process that improves quality and reduces warranty costs

!  Utilize predictive analytics to identify when goods and equipment sold to customers is likely to fail in order to identify root cause for problem correction

!  To proactively address issues to reduce warranty cost and improve customer satisfaction

Asset Optimization for Field And Service Warranty

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Business Value

• Reduce the occurrence of device failure under the scope of six-sigma standard by preventive maintenance.

• Greatly lift customer satisfaction, intimacy and loyalty with good after-sales service.

• Help R&D track operation status of launched products, and avoid the next-generation of products from falling into the same problem.

Failure Mode Analysis� Maintenance Strategy Optimization� Anomaly Detection�

Technologies: 1. Survival curve analysis 2. Cox Model 3. Gaussian distribution estimation

Technologies: 1. Non-linear mathematical optimization

model 2. Gradient decent algorithm 3. Branch-and-Cut algorithm

Technologies: 1. Sparse structure learning technique 2. Graphical Gaussian Model 3. IoT-based tech

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Predictive Asset Optimization provides proactive inspection, detection, and correction of incipient failures before they actually occur.



The Predictive Asset Optimization Solution Framework

Financial Data

Performance Log Data

Capture Predict Next Best Action

Analytics

Prescribe

Predictive Analytics Engine

Event Rules Work Flows Models

Data Consolidation Structured & Unstructured

Dashboards

Alerts

Reports & Analysis

Advanced Visual

Features

Visualization & Messaging

In-Store

Mobile

Email

Call-Center

Social Networks

Web Portals

Social Networks

Monitor

Statistical Analytics Decision Management

Business Analytics

Condition/ Sensor Data

Incident Log Data

Environmental Data

Maintenance Log Data

Customer Data

Devices

Business Systems

Data Sources

Analytical Data Store

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Predictive Analytics – The Core of Predictive Asset Management

Statistical Analytics Decision Management Business Analytics

Analytic Data Store

Service Bus/Message Broker

Product Info/ Sensor

Warranty History

Incident Data

Financial Data

Maintenance Logs

Environmental Data

Performance Logs

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IBM offers a comprehensive suite of products and services that can help our clients realize the benefits of Predictive Asset Optimization.

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Predictive Analytics System

Analytics for ‘through the windscreen’ view . Predictive insights improve Management and refine business rules

BI System

For dashboarding from Maintenance Mgt system and for distribution of predictive analytics results

IBM SPSS

IBM Cognos

IBM Maximo

Actionable Insights

Actionable Insights

IBM GBS Enablement

Services Asset Management System

A powerful ‘rear view mirror’ view for Monitoring, Reporting & Managing based on past and very recent events



Business Intelligence Predictive Analytics Optimization Data Consolidation

IBM Research has collaborated with our clients to integrate our products in delivering robust Predictive Asset Optimization capabilities.

Business Analytics Services

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Alg

orith

ms Fram

eworks

ADAM (Analytics Driven Asset Mgmt.)

Anaconda Change Point Logic

IBM Research has also developed a portfolio of analytics and logical frameworks that address a wide range of PAO scenarios.

IBM Compute and Storage Cloud

Water Utilities Solution

ADAM Solutions

Common Cloud Management Platform

Maximo Integration Framework / SAFE / IIF / Infosphere Information Server

Analytics Solution Engines

Web Services APIs

Maximo Metering Sensors CMMS

Rail Operations

Solution

Oil Platform Solution

Electric Utilities Solution

Building Energy Solution

Maintenance Planning

Maintenance Scheduling

Failure Analysis

Usage Analysis

Condition Monitoring

Custom Analytics Engine

ADAM Repository

Anomaly Detection

feature 1

feature 3

feat

ure

2

Outlier Normal

Sensor'data'Change.points'

0'0'0'0'0'0'0'0'0'0'1'0'0'0'0'0'0'0'0'1'0'0'0''...'Label!

0'0'0'0'0'0'1'1'1'1'1'0'0'0'1'1'1'1'1'0'0'0'0''...' ...'

k! k!

Predic9on'intervals'

...'

Label'

Replicate'the'original'data'by'modifying'the'labels'

sensor A

sensor B

sensor C . . .

Noise Reduction


Customer Detected Issue

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The predicted model identified 85 percent of failure states correctly.

Predictive Asset Optimization has delivered results.

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Talent'A"resource"pool"of"highly"talented"analy4c"Subject"Ma9er"Experts"and"Industry"experts"with"predic4ve"asset"op4miza4on"experience""

Industry'Exper1se'Predic4ve"models"for"a"number"of"specific"industry"use"cases"

Accelerators''• PreCconfigured"dashboard"and"visualiza4on"templates"• PreCintegrated"soDware"tools,"with"connectors"to"a"variety"of"asset"management"solu4ons"

Predic1ve'and'Advanced'Analy1cs'An"enhanced"advanced"analy4cs"methodology,"tailored"to"the"needs"of"the"predic4ve"asset/maintenance"space"

Why IBM for Predictive Asset Optimization?

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