ACHIEVING OUTCOMES WITH SCALABLE ANALYTICS · • Testing monitorin g & calibration • Monitor...

ACHIEVING OUTCOMES WITH SCALABLE ANALYTICS

Presented by : T Steffen

WERNERMN.comDiscover more

ACHIEVING ROI WITH ANALYTICS.• Session Objective:

Session Outcomes:Attendees will how to use a set of capabilities to grab vast amounts of data from any data source quickly organize that data, add context to give them the ability to add historical or real-time data source as needed. Which allows them to create an ecosystem of data sources for there company, That can now be used to rapidly build and deploy impactful applications to decision makers from the executive suite down to the plant floor operators.

Learn how having the right information at the device, system, and enterprise level can increase ROI by decreasing the time between insight and action. Utilize IOT Software Platform to enable industrial Internet of Things applications via a suite of end-to-end technology that allows production agility through its functionality & flexibility.

• Session Outcomes:Attendees will how to use a set of capabilities to grab vast amounts of data from any data source quickly organize that data, add context to give them the ability to add historical or real-time data source as needed. Which allows them to create an ecosystem of data sources for there company, That can now be used to rapidly build and deploy impactful applications to decision makers from the executive suite down to the plant floor operators.


AGENDA • Steps to being successful.

• How do you become an OutPerformer• Why is this important to your business.

• How to begin the Journey.

• Use Cases.

• Process of building Analytics

• Challenges

• What to do next.


Bringing Analyticsto Life.


Growth of the

middle class

Agingworkforce

IT-OTconvergence

Lower cost of computing & connectivity

Industrial upcycle remains strong

Equipment over 20

years old


Faster timeto market

Operationalproductivity

Asset management& reliability

Enterprise riskmanagement


FOCUSED USE CASES

Faster time to market

Operational productivity

Asset management

& reliability Enterprise risk management

• Digital process planning

• Factory design

• Digital Twin

• Design/Process Simulation

• 3D work instruction authoring

Operationsmanagement

Productionexecution

Maintenance &service

• Real-time production monitoring

• OEE

• Energy mgmt

• Process mgmt. & optimization

• Production order mgmt

• Genealogy / Traceability

• Paperless operations/EBR

• Inventory & material mgmt

• IT/OT Asset Identification

• Lifecycle analysis and planning

• System monitoring and predictive maintenance

• AR enabled training & troubleshooting

• Real-time quality KPIs

• Inline quality inspections

• Testing monitoring & calibration

• Monitor operating conditions to alert anomaly or risk

• Monitor & reduce safety events

• Health, safety, & training procedures

• Energy mgmt

• Risk based security assessments

• Real-time threat monitoring & alerts

• Firmware & patch monitoring/ administration

• Compliance mgmt

Design Quality & test

Health, environment & safety Security


DigitalThread

PredictiveAnalytics

UNDERSTAND

ADVANCE

OUTPERFORMPerformance

BenchmarkingSynchronized

Operations

AgileInnovation

AR EnabledOperations

TODAY

Unified Connectivity

Operational Intelligence

Descriptive Analytics

Supply ChainVisibility

Prescriptive Analytics

8

Continuously improved operational performance and flexibility through digital manufacturing, real-time intelligence and scalable analytics

The Digital Transformation


The discovery, interpretation, and communication of meaningful patterns in data.

Analytics relies on the application of statistics, computer programming and operations

research to quantify performance.

ANALYTICS


HOW MUCH IS TOO MUCH?

• It is easy to amass Big Data in industrial applications.• Because it’s possible, the thought right now is to gather every bit of

data from everywhere, store it in a data lake or database, and then utilize artificial intelligence (AI), machine learning and data science to extract actionable insights.

• The downside can be too much data and too little insight.• Data volumes can quickly get into petabytes (a petabyte is 1015 bytes or

1000 Terabytes). Here’s how quickly that adds up: An oil and gas company can collect 500 GB of data per day from a single compressor, and data volumes can easily exceed a petabyte in one year.

• If you’re downloading and playing one petabyte of MP3 encoded songs it will take about 2,000 years to play your entire list.


DOWNSIDE OF DATA• When there’s too much Big Data, the time to derive value and the cost

for storing and processing Big Data can be significant, and companies are discovering that unstructured Big Data is difficult to work with.

• For industrial IoT applications, we recommend a different approach:• First, identify the desired business outcomes from the data• Then, leverage the knowledge of domain experts to select the most likely data that drives

these business outcomes• Finally, match the appropriate data processing and analytics to processing data for

business value

• In this scenario, the role of domain experts in identifying and contextualizing data in industrial systems is as important as the role of data scientists in industrial IoT.


INDUSTRIAL IOT: BUSINESS VALUE LINKED TO SMART DATA

Big Data Analytics (Machine Learning, AI, etc.)

Business Outcomes

Source 1Source 2

Source n

IoT or “Cloud” Approach

Smart DataIdentify, Contextualize, Model

Analytics Machine Learning, AI, etc.

Identify Business Value

Industrial IoT Approach

Preselected data

sources

Business Outcomes

+


MANUFACTURERS SEE THE VALUE IN DIGITAL TRANSFORMATION

•

of the 2000 largest manufacturers…will rely on digital platforms as the foundation for their industrial ecosystemsby 2020

60%of use cases that require human-to-machine interactions…will use immersive interfaces like augmented reality by 2030

80% of industrial companies are investing in creating digital factories

91%US$3.7T

IoT Total Potential Economic impact for Factories (including operations & equipment optimization) by 2025

- McKinsey

- IDC - PWC - Gartner


The ‘haves’ and the ‘have-nots’

Source: LNS Research

28%Where digital

transformation programs are concerned, the TOP

28% OF COMPANIES ARE REAPING REWARDS in terms of business benefit

and speed of program impact, or have made

progress that’s delivering tangible value


Source: LNS Research

Leaders are actively leveraging these proven technologies or upgrades – now.

FOLLOWERS LEADERS

INDUSTRIAL TRANSFORMATION LEADERS VERSUS FOLLOWERS


TRANSFORMATION DRIVES COMPETITIVE OUTCOMES

Smart Connected PeopleMake Workforce

Productivity and Safety Soar

Smart Connected Assets Drive Step-

change Improvements in Utilization &

Reliability

Smart Connected Processes Enable Breakthroughs inOperational Effectiveness

PROCESSESASSETS PEOPLE


CONNECT MANAGE VALIDATE OPTIMIZEPLANT

EQUIPMENT & ERP SYSTEMS

Available TechnologiesScalable

& Flexible

Secure

MATERIALS & EQUIPMENT

MaterialOrderin

g

RecipeSpecificatio

n

Provide Clear Workflows

ORDER QUALITY

Personnel Approvals

Track Material Usage

Ensure QualityOrders & Recipes

PRODUCTIONWORKFLOW

Maximize Plant Workflow

Qualitative Analysis

THE ON-PREMISE IMPACT OF BECOMING DIGITALLY TRANSFORMED


LEVERAGEThe investments you have made

CHOOSEA partner for the

journey

CONTINUEto build out apps

for more valueFOCUS

On the apps with immediate value

1

23

4

YOUR ANALYTICSJOURNEY


Enabling smarter manufacturing through digital transformation is a journey that starts with pragmatic strategy development that involves analyzing, planning and understanding business needs, available technologies and commercial opportunities

Digital Roadmap

Technical Architectu

re

Business Architectu

re

Business Case

Corporate Alignmen

t

Operational

Assessment

| Strategy Development

| Deploymen

t

| Detailed Design

IT’S NOT ROCKET SCIENCE


COST ESTIMATES

• Develop initial cost estimate for the sample facilities

• Costs are extrapolated for the enterprise to understand and plan for a multi-year implementation

STRATEGY REVIEW

• Understand future operating vision

• Review current operating strategy

• Understand stakeholder needs

• Create alignment around a single vision for The Connected Enterprise

OPPORTUNITY IDENTIFICATION

• Identify sample facilities to review and understand operating practices

• Review plant performance to identify improvement areas

• Identify improvement projects and estimate potential savings

BUSINESS CASE

• Develop project ROI based on savings from the identified opportunities and estimated costs

• Identify operational improvements that meet investment requirement

• Bundle individual projects that rely on common costs elements

ROADMAP

• Projects that meet investment requirements are sequenced

• Initiative can be sequenced with other major projects

• Project timing and resources are estimated to allow effective planning

Leadership Interview Plant Visits, Performance Data Review Analysis, Workshops Working Sessions,

Leadership Review

IT’S JUST A PROCESS


HOW ANALYTICS ARE DEVELOPED

DESCRIBE | DIAGNOSE

DISCOVEROPPORTUNITIES

INTERPRETDATA

Motor Faulted Motor Fault – Over Current

Fuse data sources and self service dashboards

Mine data to identify correlations and causality

COMMUNICATERESULTS

Notify other systems, predictive KPIs, control

the process closed loop…

EXAMPLE


HOW ANALYTICS ARE DEVELOPED

P R E D I C T | P R E S C R I B E

DISCOVEROPPORTUNITIES

INTERPRETDATA

COMMUNICATERESULTS

Fuse data sources and self service dashboards

Mine data to identify correlations and causality

Notify other systems, predictive KPIs, control

the process closed loop…

DEVELOP MACHINELEARNING

Leverage machine learning tools. Data

Driven, Interactive, Open Source

DEPLOYDATA MODELS

Integrate models with data and desired result,

execute model and transforms

Motor will Fault Decrease Load

EXAMPLE

• Understand the performance of physical assets and digital systems through one consolidated source of information

• Enterprise data visibility and plant benchmarking

• Real-time quality KPIs

PRODUCTION & PERFORMANCE MONITORING

USE CASE


PRODUCTION AND PERFORMANCE MONITORING

• Wraps and extends existing user interfaces and technology

• Single workforce sign-on

• Role based Access

• Anticipate and resolve issues before they happen

• Robust digital representation of your assets combined with big data capabilities, allows applications to become more predictive

PREDICTIVE AND PRESCRIPTIVE MAINTENANCE

USE CASE


NOZZLE MONITORING EXAMPLE AT ROCKWELL AUTOMATION1 OF 59 NOZZLES CAUSING 92% OF MACHINE REJECTS

• The game is productivity, but the winner is a happy employee

• Digital work instructions (replacing paper or PDF based)

• Knowledge sharing and collaboration

• Machine set up and change over instructions

DIGITAL WORKERUSE CASE


DIGITAL WORKER• Modernize service and work order instructions for

workforce productivity• Workforce Instructions are visualized with 3D

animations • Can be specific to the situation • Reduced potential for Workforce error • Enables flexible manufacturing • Visual instead of textual eliminates the need for

global translation• Provides a more engaging experience for workforce

training• Additional Data with Reduced Data Entry Effort• Automatically signals the start of an Workforce Action

through AR • Workforce “walking away” signals the end of the

Workforce Action • Provides additional data automatically without the

user having to key in values

• Easily connect and model new equipment into your information infrastructure.

• Leverages the premier integration with Rockwell Automation systems, devices, and services.

EQUIPMENT / MACHINE ANALYTICS INTEGRATION

USE CASE

AUTOMATE COMPLEX ANALYTICS

• Native connectivity to hundreds of different protocols and device types

• Reduced cost of deployment and support for total system (from 2 systems to 1, from 2 vendors to 1)

• Easier to locate and investigate devices “buried deep” in the architecture for analytics

• Removes data integration, collection, and “cleansing” burden from the end-user to enable analytics. Analytics vendors often require pre-populated databases, formats, and sources

IIoT connectivity built-in


TOP USE CASES

3

3

4

4

4

6

7

8

8

9

9

10

15

16

27

0 5 10 15 20 25 30

Continuous Improvement

Capacity Management

Condition based monitoring

AR guided assembly work instructions

Predictive Quality

Asset Tracking

Inline quality inspection

Machine / Process monitoring

Ubiquitous Machine & device connectivity

Real time alert & fault identification

Digital Instructions (Assembly & machining)

Unified Operator Screen

Predictive Maintenance

Real time production monitoring

OEE & Performance Metrics (KPI's)

# OF USE CASES


Connect• Integrate all of your systems together

Context• Put data in context

Platform

• Your Application Enablement Platform• Highly reusable

Scalable• Solution can scale to meeting all sizes of Plants

Customize

• Customizable solution to meet exact needs

Foundation

• Add AR and ML


THE CHALLENGES OF DIGITAL ANALYTICS IN FACTORY

• Widespread adoption of 4th Industrial Revolution technology at scale can lead to a sizeable increase in global wealth production, benefiting people throughout society … However, most companies appear to be stuck in “pilot purgatory”

Because the challenges with

Complexity Connectivity Agility Scalability


CONSUMER LIFE SCIENCES TRANSPORTATION OIL & GAS, CHEMICAL MINING & CEMENT

Analytics INITIATIVES EXAMPLESANALYTICS INITIATIVES EXAMPLES


CAPEX: 30% in Capital Avoidance

Inventory: 120 days to 82 days

On time delivery: 82% to 96%

Lead times: reduced by 50%

Quality: 40% RTYL improvement

VALUE REALIZATION• Significant improvements have been documented by the early adopters of digitalization as reflected in

both research and individual use case outcomes

15% 13.7%

8.6%

17%

7.8%

QualityMESA/LNS


THE CONNECTED ENTERPRISE & DIGITIZATIONBest Practices

• Big Data → Contextualized / Structured Data – Relevance of domain experts

• Analytics, Machine Learning, AI → by Business Outcomes– Matched to business value and data

• Simulation/Emulation → Multivendor Solutions– Encapsulate complex simulation/emulation in digital twins

• Cloud → Scalable Compute– Leverage device-machine-cloud compute surface

• Security → End-end Defense in Depth – Regulations and standards

End-end digitization requires an ecosystem of partners


• Harden strategy and align to business drivers, initiatives, value• Prioritize high, quick time-to-value use cases• Align solutions & technology • Define scope for priority solutions

• Think Big, Start Small, with the end game in mind

Objectives

WorkshopExec Alignment

RECOMMENDED NEXT STEPS – WORKSHOP


DIGITAL TRANSFORMATIONEnabling…

Faster time to market

Lower total costof ownership

Improved assetutilization

Enterprise riskmanagement


DISCOVER MOREChallenge us

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