Transcript PPT Template

Slide 1
Aggregate, Contextualize and
Visualize Your Operations Metrics
with Wonderware Intelligence
(WW OPS-16)
Michael Schwarz
Product Marketing Manager-MES, EMI
Christian-Marc Pouyez
Product Manager – Intelligence & CEM
© 2012 Invensys. All Rights Reserved. The names, logos, and taglines identifying the products and services of Invensys are proprietary marks of
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Agenda
EMI problem statement & definition
Metrics & KPIs for Business improvement
Wonderware Intelligence
EMI for everyone, Use your own device, Mobile EMI
Demo
• Pre-defined content, value in minutes
• Mobile
• Integrated demo, expand with workflow
Business cases: Intelligence in action
Roadmap
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Many Industries Use Analytics (Intelligence)
to Manage Key Business Challenges
Many Industries Use Business Intelligence
to Manage Key Business Challenges
• Sales & Marketing
• Financial Performance
More Data and “big Data” enabled more Knowledge & Benefits
• Customer Data –what they buy, where they buy, what products…
• On-line Sales and web visit analyses – what products, what features
New technology drives new value
• New storage solutions - faster analysis of large data
• Analytics for the Masses – casual users
• Mobile Analytics – more use
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Plants already have “big Data” – but a
desire for information
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Manufacturing Performance Gaps
In a 2006 AMR Research analysis of more than 200 manufacturers on
manufacturing performance gaps, the following issues were rated as
extremely important:
• Multisite visibility of production key performance indicators (75% of
respondents)
• Enterprise visibility into production site financial performance (76%)
• Information integration between plant-floor applications and ERP (81%)
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What does that Mean for the Shop Floor?
The value of Intelligence approaches has been
proven for improving sales, marketing, and
financial performance
• This is driving the market for solutions that can
take Analytics to the masses
• Industrial organizations have Big Data about their internal
operations and a willing set of workers
The time is now to empower operations with a new level of
Industrial Intelligence and analytics and unleash their ability
to drive performance to higher levels

Slide 7
Enterprise Manufacturing Intelligence (EMI)
EMI vs BI
EMI bridges the
transactional world
with the real-time
world to provide
both a high level
view as well as
detailed, drill down
views of your
processes.
BI—Business
Intelligence—offers
similar functionality,
but its timeframe is
not real/near time
and its focus can be
marketing, sales, vs
operational
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What drives the desire for more
Intelligence, even for the Enterprise
Reduced costs & improved profits
• Leads to operational excellence
Integration of Operations Management
• Link information from the shop floor to the business
Collaboration
• Supports & enforces standards & best practices
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Wonderware Intelligence
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Wonderware EMI Strategy
Configuration &
Administration
Production/Process
Information Model
Wonderware &
Non-Wonderware
Data sources
Slide 11
Share content
& Collaborate
Incremental approach
Self-service access
to information &
content authoring
Corporate Management req’s:
• Compare metrics by site
• Approved metrics definition
• Granularity: month, site
Plant Management req’s:
• Track metrics by CI project
• Granularity: week, line
Engineering req’s:
• Root-cause analysis by equipment,
product, quality, downtime, etc.
• Granularity: minutes, equipment
Shift Supervisor req’s:
• Track metrics by shift/team
• Granularity: shift, line
Operator req’s:
• Track metrics variables during shift
• Granularity: minutes, equipment
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Role-Based Information
∑
Put in context
data from
various
sources and
compute
metrics
Slide 13
Flexible,
near-real time
dashboards
Ad-hoc
analysis,
drill-down,
drill-through
Consolidated
reports,
comparison
across sites
How does Wonderware Intelligence work
Dashboards
Analytics
Reports
Easily analyze, report and visualize:
Quality by Product or Equipment
Energy consumption by Equipment
Energy Consumption by Product type
Material cons. deviation by Product
Information
Wonderware Intelligence Software
Energy consumption Product X
Energy
Data
Corporate Energy
Management
Application
MES
Data
Batch
Data
Equipment used
Manufacturing
Execution
System
System Platform
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EMI
Data
Material flow
Process
Data
Historians,
Alarm Logs
Aggregation of Flow
over production time
Quality check
CMMS
Data
LIMS
Data
Peer Systems
LIMS, CMMS
Mobile
IntelaTrac
Node
ERP
System Architecture
View Dashboards
Create Dashboards & Analytics
3rd Party Clients
Wonderware Intelligence
Standard Clients
Microsoft Office
Reporting Services
SharePoint Portal
Published to
Intelligence
Server
Wonderware
Intelligence
Analytics Clients
Launched
from IDE
Click once deployment
Wonderware Intelligence Server
Wonderware Intelligence Data Services
Runtime
Services
Adapter
Services
ArchestrA IDE
Dashboard Server
Data Store
Published
Dashboards
Information
Model
Manager
SQL Server
Databases
Slide 15
Oracle
Databases
CSV Files via
OLE DB
WW
Historian
OSIsoft
PI ServerTM
Application
Galaxy
Server
Repository
Runtime
Advantages of Intelligence Data Store
•
Metrics and KPIs often need data elements from several sources
(MES, Historian, Lab, etc.)
 Data Store provides a unified schema with all required information
•
Contextualizing/Aggregating data sources can be very resource
intensive
 Data Store isolates transactional systems from the additional load of endusers running reports and analysis
•
End-users often have to wait minutes for reports to generate
 Data Store is optimized for retrieval and provides quick response times
Historian
•Profile
temperatures
•Production
counts
•Energy
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MES
Intelligence
•Type of product
running
•Line selected
•Material
selected
•Throughput
•Downtimes
•Efficiencies by
site
•Efficiencies by
line
•Yields vs
environmental
factors (heat,
temp, etc.)
Pre-Defined Content
Intelligence Model and pre-defined dashboards for:
•
•
•
•
•
MES
InBatch
Alarms
Corporate Energy Management
ROMeo
Process:
1.
2.
3.
4.
Install Intelligence
Import desired Intelligence Model package
Edit data sources, and start time. Deploy
Open Pre-defined dashboards and view data!
Up and running within minutes!!!
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Mobile Wonderware Intelligence
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Mobile Devices are Everywhere Today…
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Mobile Trends
Smartphones are Taking Over
the Mobile Phone Market
[Source: Ehud Gelblum, Morgan Stanley Research]
Slide 20
Mobile “Bring Your Own” Phenomenon
Many companies are finding that the widespread adoption of
increasingly sophisticated end-user computing and communication
devices is forcing them to accept and support devices of the user's
choosing.
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Demo
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Business Cases: Intelligence in action
Intelligence is applied in several industrial sectors:
Slide 23
•
Food & Beverage
•
Metals
•
Mining
•
Pharmaceuticals
•
Oil & Gas
•
Energy Management
•
Rail
•
Electronics
Food & Beverage
Intelligence Data Store
Process
data
Wonderware
Historian
•
Wonderware
•
MES
•
•
LIMS
Production
Calendar
Slide 24
Dimensions:
Reports:
- Work Orders
• Inventory Usage
- Jobs
• Genealogy Report
- ShiftBenefits
• Batch Log Report
Work orders
Equipment
Faster Operational Decisions with end-users empowered
with
• Shift Report
& Jobs
Product
Self-Service access to information
• Downtime Report
Downtime
- Inventory Lots
Scrap Reduction by knowledge of most important issues
- Downtime Reasons
Dashboards
Better Quality by early awareness of issues and visibility
• OEE by Shift,
through
Quality genealogyMeasures:
Equipment, Product
ResultsCustomer Service
- Production
Better
by quickcounts
identification of complain
• Quality by Shift,
Lab
Data
issues and proactive notification of issues
Equipment, Product
- Process Data
• Process Data
- Downtime
Summaries
Shifts
Mining
Wonderware
Historian or
OSISoft PI
•
•
•
Stock Piles
LIMS
•
Alarms
Downtime
Specifications
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Intelligence Data Store
Dimensions:
Process data
- Stock Piles
- Ore type
Dashboards/Analysis
- ShiftBenefits
• Tonnage movement
- Equipment
• Conveyer Speeds
Stock Piles
Faster Operational-Decisions
with end-users empowered
with
Alarm Definitions
by Equipment,
Shift
Self-Service access- toDowntime
information
Reasons
Stock Pile, Ore, …
Downtime
• Alarm Summary
Optimization of ore movements
Measures:
• Downtime
by
Optimization
Alarms
of stock
pile selection/movement according
to
- Tonnage moved
Equipment, Shift,
quality
- Conveyers Speed
Ore Type,…
Assay
Resultsin downtime with better understanding of root
Reduction
- Assay Data
• Quality by Stock
causes
- Process Data
Pile details
- Downtime
- Alarm Counts
Specifications
Energy Management
Intelligence Data Store
Wonderware
Historian
Process
data
Reports:
Dimensions:
• Billing
Benefits
- Meter
Definitions
• Energy Manager
Rate
Structure
• Faster Operational Decisions with end-users empowered
with
• Consumption
Building/Assets
Self-Service access to information
Energy
Dashboards
• Consumption
Energy cost reduction by wiser energy usage in peak
periods
Measures:
• performers
Intensity by
Wonderware • Definition of best practices by identification of best
- Consumption
CEM
Weather, Building,
- Costwith respect to weather conditions
• Definition of benchmarks
Asset
- Weather conditions
• Consumption/Cost
- Intensity
by Rate, Building,
Weather
Asset
Weather Data
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Intelligence Release Plan
(subject to change)
• Concurrent Licensing
(pending agreement with
Tableau Software)
• Multi-language support
in Tableau Clients
Q1 2013
Slide 27
• Flexible & Managed ETL,
using SSIS
• Visual design time
experience
• Faster, incremental
back-filling of data
• Pass-through access to
data via Overview Client
• More content
• Unified EMI Experience
(Design & Visualization)
• Metrics & Calculation
Engine
• Integration with System
Platform, Next Gen
Visualization
• More content
Q2 2013
2014
What we intend to deliver in Intelligence 2.0
(subject to change)
Accelerate time to success by delivering a library of defined Information
Transformation Scenarios for the Industrial Space
Extraction of data from a wider variety of sources, including stored procedures
Definition of measures based on aggregated and/or detailed data
Definition of the execution order for measures and dimensions
Incremental, reverse(?) back-fill of measures and dimensions
Control of update rules for slowly changing dimension
Simpler configuration of transformations from historian data sources
New visual configuration environment
ETL Monitoring and diagnostics tools
More Pre-Defined content on Wonderware sources
Dimensional Model easily recognized by client tools
Time-Slicing of Event data
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Complementary Solutions
Right tool for the right role and need
Wonderware Historian
Client
• Trending of
Historian data
Slide 29
Wonderware
Intelligence
• Trending of
Historian data
• Dashboards
• Analytics
Wonderware
Information Server
• Trending of
Historian data
For more information on Intelligence
• Product Website:
http://global.wonderware.com/EN/Pages/WonderwareIntelligence.aspx
• Local Distributor
• Product Manager: [email protected]
• Product Marketing Manager: [email protected]
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