2014 software global client conference -...

2014 Software Global Client Conference

Drive Operational

Improvements With

Self-Service Analysis:

Wonderware

Intelligence

WW INFO-02

Christian-Marc Pouyez

Product Manager – Intelligence & CEM

Schneider Electric - Wonderware – 2014-05-06

Why do we need Intelligence?


It’s all about metrics!

Overall Equipment Effectiveness

Total Effective Equipment Performance

Energy Intensity

Performance

Quality

Availability

Loading

Good Production

Total Production

Unplanned downtime

Standard Production

Production Time

Energy Consumption

Daily Contribution

Manufacturing Cycle Time

Yield

Changeover Time

Schedule Attainment

Standard Costs


Metric decomposition

OEE

TEEP

Energy Intensity

Performance

Quality

Availability

Loading

Good Production

Total Production

Unplanned downtime

Standard Production

Scheduled Time

Energy Consumption

Calendar Time

MES

Performance

Wonderware

Historian

Wonderware

CEM TEEP: Total Effective Equipment Performance

OEE: Overall Equipment Effectiveness


Metric context

OEE

Product

Shift

Batch/Process Order

Team

Production Line

MES

database

Wonderware

Historian


A few other requirements…

• Metrics must be computed in near real-time

• Metrics must be recalculated for adjustments (often very late after the fact):

• Shift duration

• Production Count adjustments

• Downtime reason codes

• Upload of offline energy data

• Using customized efficiency calculation

• Reports must be quick to generate

• Minimize the impact on the source (transactional) systems


End-user information requirements

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


Major challenge!

Metrics

•Near real-time

•Equation

•Versioning

•Recalculation

Schneider Electric - Wonderware – Date

How to solve this challenge?

●Create spreadsheets manually

●Use IT to create custom reports and dashboards

●Use standard Business Intelligence tools

●Use Wonderware Intelligence


Comparison of options Spreadsheets IT custom

content

Standard BI WW Intelligence

Near real-time No, often daily Can be Typically daily Yes

Relate time-series

data to production Manual process

Requires significant

work

Requires custom

coding/scripting Native

Self-reliant users Widespread knowledge Requires IT Depends on tool Most user-friendly

IT involvement Minimal Very high; required For Info. Model For Info. Model

Single version of

the truth Several versions Well controlled by IT Controlled by model Controlled by model

Impact on source

systems High; each spreadsheet

impacts source Typically each report

Minimal if using data

store Minimal, only data store

Recalculations Manual Needs to be planned Depends on tool and

model Native

Schneider Electric - Wonderware – 6-May-2014

Solution: Wonderware Intelligence Server

MES

database

Wonderware

CEM

Wonderware

Historian Metrics

Energy Usage

Production

Runtime

Energy Targets

Intensity

Equipment Product

Time/Shifts Batch

Wonderware

Intelligence

Server


Metrics in Context

Metrics

Consumption

Production

Downtime

Quality

Specifications

…

Equipment Materials

Time/Shifts Work Order

Intelligence

Service

Native support for

namespace:

• Wonderware Historian

• OSIsoft PI Server

Native support for:

• Time slicing

• Inferred relationships

Native support for:

• Multiple sources

• Incremental refresh

• Recalculations upon

source or context

changes

Native support for:

• Multiple sources

• Incremental refresh


Metrics in Context

Equipment Materials

Time/Shifts Work Order

Energy Type Lots

Source Location

Metrics

Consumption

Production

Downtime

Quality

Specifications

…

Inventory

Used

Lost

Quality

…

Energy

Consumption

Demand

Target

Rate

…


Metrics in Context

Intelligence

Service Data Store

Intelligence Clients

SmartGlance

Information Server


Intelligence Clients Powered by Tableau Software

Analytics Client enables end users to:

• Quickly answer questions

• Build their own visualizations

• Publish and share results and findings

• Be self-reliant in information needs

• Have fun working with data!

Dashboard Server enables to:

• Interact with visualizations in any browser

• Modify visualizations within the browser

• View the same viz on mobile devices

• Cache data for increased performance

• Brings life to production meetings!

Schneider Electric 17 - Invensys – Wonderware Intelligence – February 2014

Quick start with Pre-defined content From installation to value in minutes!!!

Pre-defined content for Invensys/Wonderware sources:

• MES Performance

• InBatch History

• Alarms database (wwalmdb)

• Corporate Energy Management

• ROMeo

Installation process:

• Import Intelligence Model in IDE

• Set source location and credentials. Set Backfill date.

• Deploy Model

• View dashboards in Analytics Client!


Wonderware Intelligence vs. Business Intelligence

Wonderware Intelligence Business Intelligence tools Business Value

Relates time-series data to

production transactions

Typically requires complex

scripting for time-series data

Historian data has no direct

relationship to production

transactions

Natively supports Wonderware

Historian and OSIsoft PI Server

namespaces

No support for namespaces Easier configuration and

maintenance of solution

Real-time computation of

metrics

Typically historical data

computed daily

Real-time metrics enable

immediate correction of plans

Model-driven configuration Configuration driven by data

transformations

Easier configuration and

maintenance of solution

Pre-defined models for

Wonderware data sources

(MES, Alarms, InBatch, CEM,...)

Not available Pre-defined content hides

complexity of data source

structures.


DEMO


Intelligence Status & Roadmap


Next release: Intelligence 2014 R2

● Immediate value after deployment

●Major performance improvements for big data

●Latest version of Tableau Software, with direct access to underlying

data sources (MES, Alarms, etc.)

●Technology Update:

●System Platform 2014 R2

● Latest available Windows and SQL Server support

Beta period in Q1 2015. Your participation would be greatly appreciated!

22 Confidential Property of Schneider Electric

Related Support, Services, Training & Expo Demos

> Intelligence

Support

Training

> Intelligence Classroom Training

> EMI Delivery group, lead by Alok Pathak

[email protected]

Services

Expo Demos

> Analytics & Energy Management booth

2014 software global client conference -...

Documents