Download What If Shewhard Had Built A Data Warehouse?

What If Shewhart Had Built
A Data Warehouse?
Robert N. Rodriguez
SAS Institute Quality Center
SAS Cary
Ian Cox
Programme Manager, Enterprise Quality
SAS EMEA
Copyright © 2000 SAS EMEA
Agenda
!
Introduction
The Value and Role of Process Centring
!
Process knowledge warehouse
Motivation
! Basic data warehouse concepts
! Process metadata enrichment
! Process metadata exploitation
!
!
Examples
SPC in semiconductor manufacturing
! strategic use of design of experiments
!
Copyright © 2000 SAS EMEA
Change is Both Predictable and
Unpredictable . . .
!
Companies organised by functions and managed
hierarchically can no longer respond adequately to
accelerating change and, sooner or later, will fail to be
viable.
Companies that have re-engineered some of their high
value business processes, and streamlined their
organisation for better operating effectiveness and
efficiency, will respond to predictable change.
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engineered all of theirrhigh
d value business processes
i
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for maximum
adaptability, and align their organisation
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around these, will respond to both predicable and
unpredictable change.
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Copyright © 2000 SAS EMEA
Change is Both Predictable and
Unpredictable . . .
!
!
!
Companies organised by functions and managed
hierarchically can no longer respond adequately to
accelerating change and, sooner or later, will fail to be
viable.
Companies that have re-engineered some of their high
value business processes, and streamlined their
organisation for better operating effectiveness and
efficiency, will respond to predictable change.
Only process-centred companies that have reengineered all of their high value business processes
for maximum adaptability, and align their organisation
around these, will respond to both predicable and
unpredictable change.
Copyright © 2000 SAS EMEA
Requirements for Process-Centring
!
Process Thinking
The process is the fundamental management construct.
!
Process Adaptability
The ability to respond to unexpected but detectable events by innovative
changes and enhancements to processes.
!
Management of Commitments
The essence of business is the negotiation and subsequent fulfilment of
commitments between suppliers and customers along the value chain.
!
Information Technology
The expediting and integrating effect of information technology is prerequisite for process adaptability.
!
Alignment
Organisation around processes based on their value contribution to business
performance.
Copyright © 2000 SAS EMEA
Process Adaptability
Process
Measure
Actual
Performance
Standards
Copyright © 2000 SAS EMEA
OK
Compare to
Standards Not
OK
Corrective
Action
Process Adaptability
The feedback learning loop is the means of
making the processProcess
adaptive.
! An “open process” has an effective
feedback loop, in which process activities
Measure
OK
can be modified whilst they are being
Actual
executed.
Performance
Compare to
Corrective
! A “closed process”Standards
has no Not
feedback
Actionloops
OK a procedure.
andStandards
is better thought of as
Once started, it cannot be modified until
completion.
!
Copyright © 2000 SAS EMEA
SAS Institute’s Value-Add
!
Process Management:
Codification of process performance requirements.
Intelligent process monitoring and exception reporting
through SPC and business rules.
Support for collaborative working.
!
Warehousing technology and an adaptive
Enterprise Computing architecture allow us
to respect the natural process scope.
Copyright © 2000 SAS EMEA
Manufacturers are asking
“How can we … ?”
!
!
!
!
Compare quality across products,
manufacturing lines, and plants
Use process measures to predict the quality of
the product before it reaches the customer
Improve yield, efficiency, and predictability of
high-tech manufacturing processes
Optimize manufacturing processes through a
strategy of experimentation
Copyright © 2000 SAS EMEA
Finding the answers requires
a strategy for
process knowledge discovery ...
Copyright © 2000 SAS EMEA
Process Data Analysis (1924)
Walter Shewhart, 1891-1967
Copyright © 2000 SAS EMEA
Shewhart Chart (1924)
Subgroup
Process
Measurement
Upper Control Limit
Lower Control Limit
Copyright © 2000 SAS EMEA
Shewhart’s Legacy
Control chart is basis for modern
statistical process control (SPC)
! Used to detect unusual patterns of
variation over time
! Pros and cons
!
easy to interpret
! applies to many types of processes
! difficult to apply to many processes
!
Copyright © 2000 SAS EMEA
What’s Different Today?
!
More data, more data sources
heavy investment in measurement systems
! highly complex processes and products
! multivariate data
!
!
!
Process management, not just process control
Higher-level questions
“Which of our processes contributed to yield loss?”
! “How many experiments optimized a process?”
!
Copyright © 2000 SAS EMEA
Barriers
Flood of data … not analysis-ready
! Multiple sources of transactional data
!
Statistical Process Control (SPC)
! Manufacturing Execution Systems (MES)
! Enterprise Resource Planning (ERP)
!
!
Data owners, data analysts, and business
users speak different languages
Copyright © 2000 SAS EMEA
Process Knowledge Warehouse
Copyright © 2000 SAS EMEA
Data Warehouse Basics
Introduced in early 1990s
! Recognized distinct requirements of
!
on-line transaction processing systems,
which bring data in
! decision support systems,
which get information out
!
Copyright © 2000 SAS EMEA
Data Warehouse Basics
Data warehousing is the process of
gathering, transforming, loading OLTP
data into a repository that is optimized
for decision-making
! Data warehouse is
!
subject-oriented
! time dependent
! read-only
! integrated
!
Copyright © 2000 SAS EMEA
Process Knowledge Warehouse
Stores process data in analysis-ready format
! Integrates supplier, process, quality, and
customer data
! Contains pre-generated analysis of important
findings using model-based exception
reporting
! Supports statistical modeling, data mining
!
Copyright © 2000 SAS EMEA
Process Knowledge Warehouse
!
Maintains history of process changes and
abnormal product variation
deviations from target
! out-of-control points
! capability indices
!
!
Provides
trends, predictions
! traceability
! answers to hierarchy of questions
!
Copyright © 2000 SAS EMEA
Building on Metadata
!
Metadata are data about data
publish origin and content
! describe roles of variables in analysis
!
Well-structured metadata simplify and
validate analysis
! Enriched metadata are data about processes
!
derive from basic process analysis
! describe results stored in warehouse
! answer higher-level questions
!
Copyright © 2000 SAS EMEA
Metadata Spectrum
Administration
Copyright © 2000 SAS EMEA
Analysis
Metadata Spectrum
Administration
Where did this data originate?
Copyright © 2000 SAS EMEA
Analysis
Metadata Spectrum
Administration
Analysis
Do I have all the data I need?
Copyright © 2000 SAS EMEA
Metadata Spectrum
Administration
Analysis
What chart should be used?
What control limits were in effect?
Is the process in control for this capability analysis?
Copyright © 2000 SAS EMEA
Metadata Spectrum
Administration
Analysis
Which process steps are critical?
What should we work on first?
Which activities maximize cost-benefits?
Copyright © 2000 SAS EMEA
What is Metadata Enrichment?
!
Process of
obtaining a chunk of raw data from the
warehouse
! performing a sound statistical analysis on
that data
! saving the metadata results of the analysis
in a traceable and usable structure
!
Copyright © 2000 SAS EMEA
Experimental Design
Metadata Enrichment
Copyright © 2000 SAS EMEA
Experimental Design
Metadata Enrichment
Copyright © 2000 SAS EMEA
Experimental Design
Metadata Enrichment
Copyright © 2000 SAS EMEA
Data Model With Enriched
Experimental Metadata
Copyright © 2000 SAS EMEA
Process Knowledge Warehouse
Exploitation
!
Shift in analytical focus
!
!
!
from one control chart to questions about all processes
from individual experiment to questions about
enterprise experimentation strategy
Process scorecard
Copyright © 2000 SAS EMEA
Example:
Semiconductor Yield Loss
Copyright © 2000 SAS EMEA
Example:
Semiconductor Yield Loss
!
Cost of yield lost at wafer probe
= wafer material cost x wafer volume x
(1 - model-adjusted yield)
!
Hierarchical exploitation
high-level views published by SAS/WA with
references in analytically enriched
metadata
! detailed views generated by SAS/Intrnet
calls with data in warehouse
!
Copyright © 2000 SAS EMEA
Enterprise-Level Process
Knowledge Warehouse
Copyright © 2000 SAS EMEA
Benefits of a Process
Knowledge Warehouse
!
Raw data integration
integrates raw data from many processes
! stores data in analysis-ready structure
described by data model
!
!
Metadata enrichment
generates process metadata via analysis
! creates data tables, GIF, HTML
!
!
Metadata exploitation
!
Copyright © 2000 SAS EMEA
answers global questions
Links . . .
Wednesday, 1315, Technology Centre, Booth 5, Data Mining and Applied
Analysis
Enhancements to ADX in Release 8e
Wednesday, 1545 - Mainstream SAS Presentation, Business Solutions
Stream, Pavilion 2
What if Shewhart Had Built A Data Warehouse?
Thursday, 0945, Technology Centre, Booth 5, Data Mining and Applied
Analysis
Enhancements to ADX in Release 8e
Thursday 1700, Business Applications of Data Mining, Theatre 2
Building a Data Warehouse For Process Knowledge
Management
Copyright © 2000 SAS EMEA
What If Shewhart Had Built
A Data Warehouse?
Robert N. Rodriguez
SAS Institute Quality Center
SAS Cary
Ian Cox
Programme Manager, Enterprise Quality
SAS EMEA
Copyright © 2000 SAS EMEA