nicki sommer principal sales consultant ncoaug, august 15, 2008 whats new in release 12...

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Nicki SommerPrincipal Sales ConsultantNCOAUG, August 15, 2008

What’s new in release 12 manufacturing?

CONFIDENTIAL: All capabilities and dates are for planning purposes only and may not be used in any contract

The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions.The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

Safe Harbor Statement


Service Parts Planning

Advanced Planning Command Center

Demand Signal Repository

Manufacturing Operations Center

CONFIDENTIAL: All capabilities and dates are for planning purposes only and may not be used in any contract 5

Changing Changing Supply Chain Supply Chain

Business ModelBusiness Model

Drivers For Success

Uncertainty

Virtualization

Chaos

Globalization

Volatility

Consolidation

Risk

Compliance

Continuous InnovationContinuous Innovation

Operational FlexibilityOperational Flexibility

Risk Management and Risk Management and ComplianceCompliance

New world: continuously adapting to changing supply chain business modelToday’s Supply Chain Executives’ Agenda

Increased Shareholder

Value and

Sustainable Growth

CEO’s Agenda

“What is required is a new type of decision support platform, one that integrates analytics and optimization. 15 years after the birth of Supply Chain Planning (SCP), we are now just starting to see analytics and optimization converge on a common platform”

AMR Research Report “How to measure your supply chain today “


The Great Information Divide Still Exists

• Typically, they don’t have access to correlated and aggregate planning data unless it is presented in a comprehensive spreadsheet or on paper

• Often, the decision is made to design and build a custom data warehouse that has no integration to the source of the data and that is a limited representation of the data

• Supply chain executives have no time to learn power user interfaces that were developed for purposed planning applications

How do the supply chain executives get access to actionable information?

Manual Co-ordination Across Functional Groups

UncertaintyVirtualization

Chaos

Globalization

Volatility

Consolidation

Risk

Compliance

Continuous Innovation

Operational Efficiency

Risk management and Compliance

Emails, Phone calls Spreadsheets, Reports

SNO ASCP DM PS IO DRP


Oracle Advanced Planning Command Center

• Planning analytics for key decision makers – Pre-built, self service, configurable dashboards

• Executive level business scenario planning – Planners and executives share accountability

• No separation between analytics and planning – Seamlessly drill down to lowest level of detail

• Rich content out-of-the-box – Get started immediately for fast ROI

Business insight for supply chain executives

BUSINESS INSIGHT BUSINESS DRIVERS

Preconfigured Analytics Model

Scenario, Activity and Process Management

Pre-built, self-service Dashboards

Drill downs to details


Oracle Advanced Planning Command Center

• Get the right answers• Self service, pre-built• Rich content and KPIs• Seamless integration

with planning apps

Key capabilities

Pre-Built Dashboards and Reports

Scenario andActivity Management

Plans and Archived Plans

An

alyz

eP

lan

Orc

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trat

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Analyze and compare scenarios and plans

Execute scenarios

Execute automated processes

Archive plans

Web Service enabled Planning Processes

Analytical Data

Forecasting Supply Planning

Planning Analytics for Supply Chain Decision Makers

Business scenario planning

• Decide which scenarios to plan

• Compare baseline to alternative scenarios

• Assign scenarios to planners for execution

Preconfigured Planning Processes

Planning process automation

• Notify constituents of assigned activities

• Link processes for manual or automated execution

• Auto-archive plans




Executive level business scenario planning

Planning analytics for supply chain decision makers

Planning process management automation


Role Based DashboardProcess – Executive Review

• Executive Review reports– Executive Summary

– Top Diff – Operating Plan and Budget by Category

– Consensus Change by Customer

– Consolidated Analysis

– Profit and Loss Statement

– Constrained Forecast Comparison

– Budget Analysis

– KPI reports: Forecast Accuracy; Customer Service; Inventory and Production


Translate Strategy to ActionsProblem ► Cause ► Alternative Solution Evaluation

Revenue below targetRevenue below target

Sales below targetSales below target

Supply shortagesSupply shortages

Competitorpromotion

Competitorpromotion

Sales selling wrong product mix

Sales selling wrong product mix

Pricing issuesPricing issues

Critical part shortageCritical part shortage

Lost productioncapacity

Lost productioncapacity

Lost sales due to lackof supply

Lost sales due to lackof supply

Change product mix

Launch promotion

Adjust pricing

Promote alternate product

Plan overtime

Outsource production

Change inventory levels

Hedge supply

Analysis Planning

What problem

do I have?

Why do I have this problem?

What actions should I

evaluate?


Scenario Management

• Supply chain decision makers define business planning scenarios

– Unlimited number of baseline scenarios– Unlimited number of alternative scenarios

• Assign scenarios and tasks to planners for execution

– Shared accountability for supply chain planning metrics

– Planners execute plans using Planner

Workbenches

• Attach key documents– Financial analysis– External market data and industry reports

Decide what baseline and alternative scenarios to run to make decisions

Assign and monitorscenario activities

Execute and assign supply plans to scenarios

Execute and assign inventory plans to scenarios

Execute and assign demand plans to scenarios

PersonalActivity List



Demand Planner Inventory Analyst Supply Planner


Compare Scenarios – Cut across Planning360 degree visibility to demand, supply, capacity, finance, and exceptions

Pre-built self-service dashboards for plan health and S&OP analysis


Compare Scenarios – Cut across Planning

Demantra Demand Management

Advanced SupplyChain Planning

Inventory Optimization

Demand from DM

Supply from ASCP or SNO

Inventory from IO

Enable holistic view of supply chain performance and drill down to details



Advanced SupplyChain Planning

Inventory Optimization

Demand from DM

Supply from ASCP or SNO

Inventory from IO

Compare Scenarios – Cut across Planning


Drilldown to details

Enable holistic view of supply chain performance and drill down to details


Compare Scenarios to Make Decisions

Compare baseline to alternate

Compare current to previous


Pre-seeded Rich Content – KPIsRich content out-of-the-box:100+ pre-seeded dimensions and perf. metrics


Pre-seeded Rich Content – ReportsRich content out-of-the-box: 100+ pre-seeded reports


Planning Process Management AutomationWeb service enabled planning processes

• All key planning processes are web service enabled– Collections– Forecasting– Plan runs– Plan name creation

• Approval and review steps can be modeled and inserted into the process


Planning Process Management AutomationAutomate planning process execution via BPEL

• Assign owners to top level process notes

• Optionally skip steps when resubmitting


Planning Process Management Automation

• Archive scenarios directly from Scenario Management, via concurrent program or web service

– Automatically archives KPIs and facts for plans that are linked to the scenario Archives Demantra Demand facts published to

EBS– Creates a new scenario version that can be used for

comparison in the dashboards– Purge scenarios as they become obsolete (will not

purge plans shares across multiple scenarios)

• Archive plans directly from plan runs (optional) or Publish profile (SNO, Demantra)

– All facts, KPIs, and summaries for the plan are archived in a new plan version

– Compare plan versions in the dashboards– Purge plan versions as they become obsolete– ASCP/IO Purge plan: purges all plan versions

Automatically archive scenarios plans for historical analysis

Plans and Archived Plans

Archive plans

Archive scenarios


Service Parts Planning


• Centralized• Few locations• Few products• Planners manage few parts• Shorter lead times• Few suppliers • Sales forecast• Deterministic• Build or buy supply

• Decentralized• Many locations• Many service parts• Planners manage many parts• Longer lead times• Many suppliers• Myriad of demands• Probabilistic• Move, repair, or new buy

MANUFACTURING SERVICE

Why Service requires different approaches and systems

Two Different Worlds


Service Supply Chain

Regional DCsServicetechnicians

Central DC

Repair depot

Customers

Supplier (Repair)

Supplier (New Buy)

On-hand Consigned

Repaired In repair

Material flow of good spares

Material flow of defective spares

Must manage both forward and reverse material flows


Oracle’s Service Management Solution

Customers Service Providersand Suppliers

Service Execution

Service Parts Planning Solution

ExternalExternal

In-houseIn-house

Self-Service

Email

Phone

Messaging(XML/EDI)

Contracts Install base& Engineering

Spares Mgt Field scheduling

Call center CMRO &Depot repair

Spare parts and returns

forecast

Inventorypostponement

plan

Spare parts replenishment

plan

Deployment plan

Workflow based exceptions

Parts usage

Repair Repair ordersorders

Contracts & renewals

Parts life cycle &

failure ratesSelf-Service

Self-Service

Poweruser

Replenishmentorders

Spare parts order promising

Service supply chain

design

Complete and integrated solution


Oracle Service Parts Planning• Simultaneously forecast, replenish and

redistribute your service parts across your service supply chain

• More accurately forecast your service parts– Demantra statistical forecasting engine inside for highest

accuracy– Account for intermittent, seasonal, and fast moving demand

patterns– Leverage composite forecasting (shipments, usages, returns)– Use service failure rates

• Optimize the replenishment and redistribution of parts across the extended service network, integrated with Service Execution

• Integrate with other Advanced Planning products for additional business processes

– Manage spare parts at customer locations (via CP)– Manage service contract customer demand (via Dem DM)– Manage targeted service levels and budgets (via IO)– Produce parts in manufacturing facilities (via ASCP)

Key capabilities


Regional DCsServicetechnicians

Central DC

Repair depot

Customers

Supplier (Repair)

Supplier (New Buy)

On-hand Consigned

Repaired In repair

• Spares Management plans field service engineer trunk stock replenishment• Service Parts Planning plans supply network (up-to trunk stock locations)

– Recognizes usages from field service

Oracle Service Parts Planning

Spares Management Service Parts Planning


Oracle’s Service Parts Planning Solution

Enabling profitable reverse logistics at higher service levels

Simultaneously forecast, replenish and redistribute your service parts across your service supply chain

More accurately forecast your service parts

Optimize the replenishment and redistribution of parts across the extended service network, integrated with Service Execution

Integrate with other Advanced Planning products for additional business processes


Simultaneously Forecast, Replenish and Distribute

Comments Exceptions

Supply-Demand

Forecast

Worksheet

Preferences

Graphs

Items, Failure Rates,

Supersession Chain

Single planning process and UI for highest productivity and fastest analysis


More Accurately Forecast Service Parts

• Accurately statistically forecast the complex demand patterns found in service parts

– Key forecast methods specific to service part demand patterns– Data transformations for intermittent or sporadic patterns– Expert mode: automatically select best blended statistical method for every service part

• Forecast for service parts without adequate shipment history– Forecast based on composite of shipments, usages, returns, failure rates, and product

population

• Forecast for changing replacement parts and revisions– Forecast entire supersession chain and chain history of multiple revisions

• Scale to handle large volumes of parts– Selectively re-forecast: use specific forecast methods, parameters, and forecasting

frequency as needed based on criticality

Demantra Bayesian statistical engine “inside” for highest forecast accuracy


• Support for key forecasting methods – Moving average

– Single exponential smoothing

– Holt

– Integrated causal exponential model (Winters enhanced)

– Regression with seasonal causal

– Croston’s for intermittent

– Regression with seasonal causal for intermittent

– Multiplicative Monte Carlo regression with seasonal causal for intermittent

– Optionally, use 100+ advanced parameters for fine tuning

• Baysian weighted forecasting - blend multiple forecast methods instead of picking one method

J F M A M J J A S O N D J F M A M J

Intermittent demand – Printer Heads

M A M J J A S O N D J F M A M J J A

Seasonal Demand – Air Conditioning Parts

Demantra Bayesian statistical engine “inside” for highest forecast accuracy

Intermittent, Seasonal and Fast Moving Demand


Optimize Replenishment and Redistribution

• Consider key service planning constraints – Part supersession, condition, and criticality– Sourcing of repair-at and buy-from– Repair resources (internal)– Purchasing, repair, transportation lead times– Supplier capacity (for new buy)

• Minimize inventory and purchasing cost, and out-of-stock impacts

– Dynamically reallocate and reposition parts – Replenish to optimized safety stock levels– Use up superseded parts; repair before new buy

• Out-of-the-box integration with Execution– Release recommendations for new buy, repair, and

transfers

Operate more profitable Service chain by saving inventory and purchasing costs


Model Key Service Constraints

• Model how your supply chain changes over time

– Time phased sourcing rules

– Include sources such as Transfer From, Repair At, Return To, Make At, and Buy From

• Use unlimited assignment sets for what-if sourcing scenarios

• Rebalancing between organizations (circular sourcing)

• Use different ship methods w/ diff lead times attached to sourcing rule

• Flexible assignment of sourcing rules minimizes setup maintenance

Accurately model your service supply chain


Model Key Service ConstraintsPart Supersession and Part Condition


Minimize Inventory and Purchasing Cost, and Out-of-Stock Impacts

• Service-specific business logic– Repair before new buy– Consider returns supply– Use up superseded parts

• Dynamically reallocate and reposition parts

• Replenish to optimized safety stock levels


Enable Additional Business ProcessesLeverage additional key capabilities provided by Oracle Advanced Planning

DEMANTRA DEMAND MANAGEMENT

INVENTORY OPTIMIZATION

SERVICE PARTS PLANNING

Forecast and Demand Variability

Time-phased Safety Stock Levels

• Verify ability to uptake new SLAs• Determine inventory budget required for SLAs• Optimally deploy inventory to meet SLAs• Analyze inventory policy recommendations

• Advanced forecasting methods• Forecast at additional levels (customer, …)• Forecast leveraging causal factors• Forecast new product introductions

Replenishment and

RedistributionForecasting

Spare Parts Forecast (Highest Rev)

Spare Parts Forecast (Highest Rev)

and Demand Variability (optional)

COLLABORATIVE PLANNING

• Manage spare parts at cust. locations• Get visibility to new buy supplier

capacity

New buy supplier capacity


Demand Signal Repository


Demand Signal Repository Overview

Business Problem

• Limited visibility to store/SKU level inventory location and performance data contributes to suboptimal forecasting, allocation and replenishment capabilities

• Retailers are starting to rely more on category captains and have begun to share daily store level POS and inventory data directly with their CG suppliers

• Unlocking the value of downstream data is a challenge due to high complexity, variability and volume

Solution Overview

• Oracle Demand Signal Repository (DSR) helps CG manufacturers capture, manage, analyze and ultimately drive value from downstream demand data

• Oracle DSR leverages OBIEE to provide a powerful BI/reporting platform to analyze the external data, including a set of pre-built dashboards and reports

• Oracle DSR integrates aggregated demand data with Demantra and offers standards-based integration to other applications via AIA/Oracle SOA Suite


Convergence of Retail and Consumer Goods

ConsumerGoods

Mfg.Retailer

Traditional View of Relationship

• Category & Space Planning• Demand Management• Trade Promotion Management

Aligned Priorities• Jointly managed store/SKU-level

merchandise plans• Optimized promotion & merchandising

decisions• Total supply chain logistics &

transportation cost reduction• Item & price data synchronized to reduce

deductions

CG Mfg

Retailer

Sh

ared

Sh

ared

Emerging Relationship

• Transportation & Logistics • Retail Execution• Vendor Managed Inventory

Retailer Facing Applications


DSR Solution Capabilities

Capture

Manage

Analyze

Integrate

• Adaptors to capture a variety of data types and sources• Data cleansing tools to address data quality issues

• Extensible, retailer-based data model to maintain external data at the store/SKU level

• Routines to to harmonize data across multiple data aggregation levels and hierarchies

• Pre-built category management, key account management and scorecarding dashboards and reports

• Flexible, robust business intelligence and reporting capabilities

• Pre-built integration with key Oracle applications such as Demantra, Siebel, Agile and G-Log

• Pre-built SOA integration with other external applications via Oracle Application Integration Architecture

Respond• Rules-based exception management dashboard• Automated workflow to facilitate resolution of exceptions• User-defined, event-based triggers to initiate transactions in

external applications and enable “sense & respond” capabilities


Data Integration Today

Retailer 1 POS

Retailer 2 POS

IRI

ACN

Distrib. 1

Distrib. 2

Other

Capture + Cleanse

Capture + Cleanse

Capture + Cleanse

Capture + Cleanse

Capture + Cleanse

Capture + Cleanse

Capture + Cleanse

• High latency of demand data

• Significant manual effort and cost

• Increased probability of inconsistencies across applications

Downstream Demand DataTPM

TPO

APS

S&OP

DRP

SNO

PLM

Data sources cleansed and managed independently


Data Integration With Oracle DSR

TPM

TPO

APS

S&OP

DRP

SNO

PLM

• More timely data to better sense, shape and respond to demand

• Reduced manual effort and cost

• Consistent data more easily leveraged across teams and applications

– S

OA

Mes

sag

es –

Ag

gre

gat

ed D

eman

d S

ign

als

• Data sources centrally cleansed, harmonized and aggregated

• Pre-built dashboards and reports• Powerful BI capabilities • “Sense & Respond” event management

Cap

ture

Man

age

An

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Res

po

nd

Oracle Demand Signal Repository

Inte

gra

te

• POS sales• Price• Store inventory• Promotional plans• Store replen. rules• Store forecasts

Retail Store Data

• DC shipments• DC inventory• DC replen. rules

Retail DC/ Distributor Data

• Retail loyalty• IRI/AC Nielsen• 3rd party

demographic• Causal

(weather,etc.)• RFID/EPC• IMS, NDC, EDI

(867, 852), Scripts, Pedigree

• Unstructured text

Other External Data


DSR Data Integration Scenarios

Store/Distr.On-hand

Sales

Returns/Unsaleables

ConsumerEvents

StoreOrders

TradePromotion

Mgmt

PredictiveTrade

Planning

DemandManagement

DistributionRequirements

Planning

ProductLifecycle

Management

RetailExecution

Retailer

Distributor

Syndicated

Store/Distr.On-hand

Sales

Returns/Unsaleables

ConsumerEvents

StoreOrders

TradePromotion

Mgmt

PredictiveTrade

Planning

DemandManagement


Planning

ProductLifecycle

Management

RetailExecution

Retailer

Distributor

Syndicated

Oracle DSR

Monitor sell-through of in-flight

promotions

Incorporate impactof consumer events in

promotion forecasts

Forecast based oncleansed, detailedpoint-of-sale data

Incorporateretailer inventory

in order plans

Address qualityissues in design

and packaging

Base deliveryand merchandising

on current sales

Store/Distr.On-hand

Sales

Returns/Unsaleables

ConsumerEvents

StoreOrders

TradePromotion

Mgmt

PredictiveTrade

Planning

DemandManagement


Planning

ProductLifecycle

Management

RetailExecution

Retailer

Distributor

Syndicated

Store/Distr.On-hand

Sales

Returns/Unsaleables

ConsumerEvents

StoreOrders

TradePromotion

Mgmt

PredictiveTrade

Planning

DemandManagement


Planning

ProductLifecycle

Management

RetailExecution

Retailer

Distributor

Syndicated

Oracle DSR

Monitor sell-through of in-flight

promotions

Incorporate impactof consumer events in

promotion forecasts

Forecast based oncleansed, detailedpoint-of-sale data

Incorporateretailer inventory

in order plans

Address qualityissues in design

and packaging

Base deliveryand merchandising

on current sales

“Consumer products companies that take responsibility for the supply chain all the way to the retail shelf can see a 2% to 15% improvement in sales”

AMR Research, “Shouldn’t You Be Minding the Store?” (May 2007)


DSR Integration Scenario:Demand Management & S&OP

More timely and accurate visibility to downstream demand signals

–Forecast based on store level visibility

–Accurately predict demand based on store level visibility

–Forecast based on attribute-level granularity


DSR Integration Scenario:PLM and Innovation

• ~10,700 new CPG products introduced• ~3% of food and beverage introductions and 1%

of non-food introductions achieved $50M sales Source: IRI, “2006 New Product Pacesetters, New CPG Brand Leaders” (March 2007); McKinsey Quarterly, “Reinventing Innovation at Consumer Goods Companies” (November 2006)

Improve both NPD and NPI capabilities

• Improved NPD by matching shopper and consumer insight to product attributes to enable attribute-based NPD and demand forecasting

• Improved NPI by providing more accurate visibility to channel inventory and event execution

• Improved PLM by providing more timely store/SKU level performance data


Scorecard DashboardLeverages New Ways of Working Together Pilot

• Monitor results vs. goals over time

• Drill-down to view supporting data

• View score by retailer and overall

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Category Management Dashboard

• Multiple KPIs in a single dashboard

• Track performance relative to pre-defined thresholds

• Drill-down to view supporting data

• All reports viewable in retailer hierarchy or manufacturer hierarchy

• Reports can be automatically delivered via MS Office tools

Illustrative

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Example Category Management Reports

Top Performers by Sales

Category Sales Value by Type

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Manufacturing Operations Center


What is MOC..?

• Mfg Ops Center is the same as…– Manufacturing Hub– Manufacturing Data Hub– Manufacturing Transaction Hub– Enterprise Manufacturing Intelligence (EMI)

Operational Intelligence Shop Floor Integration Solution Real-time Intelligence

• Mfg Ops Center is not…– MES– A Substitute for Corporate Business Intelligence (BI) solution– Data Historian (OSI Pi, Wonderware….)– Middleware


Operational ChallengesZero Manufacturing Agility to Respond to Changing Demand

Multiple sources of truth

Poor production performance visibility

Knowledge not shared across resources

Rigid, disconnected & disparate systems

Real-Time, Exception Prone Environment Dominated by Older Legacy Systems

Multiple Plants w/ Different Systems

FactoryAutomation

Homegrown /3rd Party MES

Quality/ SPC

Maintenance/ Service

Multiple Contract Mfgrs

Corporate

CustomerRelationship Mgmt

Supply ChainManagement

BusinessIntelligence

EnterpriseResource Planning

Relatively Stable Environment

Planning andSchedule-Driven

Standard Systems

DisconnectedDisconnected


A Need for ChangeLeading Business Trends

• Shift from Periodic Reporting to Real-Time Performance Management

• Leverage Consistent Performance Metrics Across the Enterprise

• Plan and Schedule to Realistic Equipment Capacity and Adjust Operations in Real-Time

• Utilize an Enterprise Approach to Managing Manufacturing Operations Systems


Oracle Manufacturing Operations Center

The Foundation for Continuous Improvement in Manufacturing

Operations

Automation& Process

ControlSystems

ERPSystems

Users

PLC CNCMachines

DCS SCADASystems

AdvancedProcessControl

HumanMachineInterface

- MES- Quality- Cost Mgmt…

ManufacturingOperationsData Model

ManufacturingOperationsData Model

Role-BasedDashboards

Contextual-izationEngine

Corporate BI

Cross-PlantKPIs

HistoricalTrends

Plant-SpecificKPIs

Real-TimeUpdates

Device-Generated Data

Production ActualsSchedules

Item Master Data

ProductionManager

Plant Mgr /VP of Mfg

MES Shop Floor Communication Drivers



Contextualize Plant Floor Data and Synchronize with ERP

Provide Real-Time Intelligence for Plant Operations

Leverage Next Generation Manufacturing Operations Architecture

Enables you to…



Single Repository for Mfg Operations DataProvide Consistent Information for All Manufacturing Users

• Generic data model supports hierarchical structure for reporting or building KPIs and metrics

- Support for industry standardssuch as S-95

- Out-of-the-box hierarchical dimensions: time, product, and equipment

- Flexible and configurable

• Open and extensible to meet the requirements of different industries

- Capture process variables

- Capture additional parameters for Item, Equipment, and Work Orders

Manufacturing

Operations

Data Model

Manufacturing

Operations

Data Model

Gra

nula

rity

Enterprise Level- Products- Orders- Plans / Schedules

Plant Level- Work Orders- Batches- Mfg Routing

Equipment Level- Availability- Status- Output- Quality- Parameters

Device Level- I/O Tags- Sensor ID


Integration with Manufacturing Equipment and Distributed Plant SystemsGather High Resolution Data Directly from Source

PLC CNCMachines

DCS SCADASystems

AdvancedProcessControl

HumanMachineInterface

Mfg Operations Ctr

Error Handling

OPC Servers

MESShop Floor

Communication Drivers

Adapters

OtherConnectors

3rd PartyOPC Client

• Support adapters for 3rd party systems, like data historians

• Build additional adapters using Fusion Middleware

• Tag data mapping

• Data filteringrules engine

Capture and process errors at every stage of data collection

Support broad range of devices


Integration with ERPEnable Seamless Information Flow

• Simplify integration to ERP -- rely on Manufacturing Operations Center for data cleansing, error handing, etc.

• Reduce the cost of ERP integration -- eliminate one-to-one integrations

Mfg Operations Center

Oracle EBS Discrete Mfgor Other ERP

Leverage…

- Metadata-driven integration toOracle EBS

- Fusion Middleware for SOA-based integration with other ERP

Shop floor transactions

Master data, plans,and schedules

ERP Adaptor


Shop Floor Data ContextualizationConvert Raw Data into Useful Business Information

• Define data transformation rules - Rules by tag type- Business-oriented aliases for tags- Additional tag attributes like rollover

values

• Use pre-built rules or create new rules

• Apply context to time series data- Work Order- WO Segment

• Apply out-of-the-box rules ordefine new rules

- Product- Shift

Automation& Process

Control Systems

Transform

Business Events

BuildContext

AnalyzableBusiness

Data

PLC

DCS

SCADA

…

IntelligenceSystems

CorporateBI

Ops CenterDashboards

Business ContextData

ERPSystems CRM SCM ERP

High ResolutionTag Data






Enables you to…



Role-Based Dashboards and KPIsDeliver Performance Measures by Responsibility

• Pre-built role-specific dashboards, reports, and alerts

• Graphical views

- Trend charts- Graphs- Tables

• Embedded best-practice calculations and KPIs

• Analytic workflows to drive actions

• Drill-downs into details forroot-cause analysis

• Leverages OBIEE+

• Configurable and customizable

Are we achieving our costand productivity targets?

What is happening now?What happened last shift?

How is the machine performing?

VP of Operations

Plant Manager

Production Manager

Production Supervisor

Operator

QA Engineer

- Red-yellow-greenindicators


Extensible Analytical Engine and Dashboarding Tool

Most standard Most standard KPIs availableKPIs availableout-of-the-boxout-of-the-box

• Accelerate deploymentand adoption

• Easily adapt dashboards and metrics

• Provides a comprehensive Operational Intelligence framework

Easily identify, select, modify, Easily identify, select, modify, and format relevant KPIsand format relevant KPIs

Build a Decision Support System Unique to Your Environment


Click to view Click to view alert detailsalert details

Production Manager DashboardLine-Level Status


Production Throughput Analysis Track Production and Identify Potential Bottlenecks

• Track against targets for shift, day, week, or month

• Monitor backlogs by individual equipment

Supervisors,Line Managers

Plant Managers,VP of Manufacturing

• View throughput by product, plant, line,and equipment

• Analyze monthly trends to ensure aggregate performance

Click to Click to view alert view alert

detailsdetails

Visual cues Visual cues quickly indicate quickly indicate

production production status status

Determine Determine equipment statusequipment status

Monitor production Monitor production volumes & throughput from volumes & throughput from anywhere in the enterpriseanywhere in the enterprise






Enables you to…



What is Next-Generation Manufacturing Operations Architecture?

“It is often more expedient to install an abstraction layer built on a plant-level data store than to reengineer the plethora of existing applications to achieve normalization. We see this approach rapidly emerging as a best practice.” -- Alison Smith, February 2008

• Built on a common abstraction layerof production / equipment data

• Leverage existing investments in plant IT infrastructure – no rip & replace

• Allows for gradual upgrade of plant systems

Next-Generation Architecture

AbstractionLayer

ERP

Distributed Plant Systems

Automation & Control

Mfg Operations CtrMfg Operations Ctr



The Foundation for Continuous Improvement in Manufacturing Operations

Contextualize Plant Floor Data and

Synchronize with ERP

Contextualize Plant Floor Data and

Synchronize with ERP

Provide Real-Time Intelligence for

Plant Operations

Provide Real-Time Intelligence for

Plant Operations

Leverage Next Generation Manufacturing

Operations Architecture

Leverage Next Generation Manufacturing

Operations Architecture

• Consistent mfg information for all users

• Convert equipment data into useful business info

• Ensure rapid response to manufacturing issues

• Leverage existing plant IT infrastructure

• Enable gradual upgrade of plant systems

• Simplify IT support for your core mfg strategy

• Deliver performance metrics & trends by role

• Easily build dashboards to your unique needs

• Identify performance improvement opportunities

nicki sommer principal sales consultant ncoaug, august 15, 2008 whats new in release 12...

Documents

planning purposes

aggregate planning data

purposed planning applications

data supply chain executives

information purposes

contract role

analytics model scenario

process management prebuilt