1 data quality management: successes in transferring configuration data from suppliers to owner...
TRANSCRIPT
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Data Quality Management:Successes in Transferring
Configuration Data from Suppliers to Owner Operators
Presented By:John B. Whitmire
Bentley Systems, Inc.
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Process Industry Drivers
• Data Handover – typically inefficient and costly
• Proprietary data systems no longer acceptable
• Operations demands clean, consistent and complete information
• Having intelligent data is not enough, we must be able to support our business processes with it or it becomes ‘just another database’.
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Asset Lifecycle Information Management Why Invest?
‘An average of 40% of engineering time is dedicated to finding and validating information from disparate systems’ – “Cost Analysis of Inadequate Interoperability in the U.S. Capital Facilities Industry”, National Institute of Standards and Technology, Office of Applied Economics.
– Avoidance Costs – money spent to prevent interoperability problems from occurring. Often realized in redundant systems and increased use of bandwidth and training costs to maintain legacy systems.
– Mitigation Costs – money spent to correct problems once they occur. Primarily visible in the data reentry and validation requirements that results in redundant labor. As a consequence, no matter the phase of the project, time must be spent ensuring all parties have the same information via manual intervention.
– Delay Costs – money lost due to schedule slippage . The consequence of the impacts of avoidance and mitigation costs.
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Why Data Quality Management?
• Defined ontology– Specifies expected Objects, Attributes and Associations for each
class of information
• Defined requirements for Suppliers• Progress Measurement at a granular level
– Measurable compliance with the data needs of our organization– Measurable completeness to the data handover specification
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Interfacing with Client’s Environment
Data Quality Management• Allows clients to use tools of choice• Can receive data from any
application• Can publish data to any accepting
application• Data qualified at time of receipt• Qualification rules driven by client’s
business requirements – not software limitations
• Enables the evaluation of data prior to publishing the information to the user community (Management of Change)
AutoPLANT
PlantSpaceSmartplant®
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Configurable Business Process Automation
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Example System MapKey
Data Exist and has been successfully loaded
Data exists but is not loaded
Data exists but has issues
Data not provided
Data not required
Instrumentation
Tags
Doc References
Attributes
Connections
Parent Tag
Mechanical
Tags
Doc References
Attributes
Connections
Parent Tag
Electrical
Tags
Doc References
Attributes
Connections
Parent Tag
Telecomms
Tags
Doc References
Attributes
Connections
Parent Tag
Codings
Instruments
Fire & Gas
Telecomms
Electrical
Mechanical
Lines
Cables
Valves
Documents
Facilities
Systems
Sub Systems
Locations
Sub Locations
PR Tag Cable
PR Document Tags
PR Tag Lighting and Small Power
PR Tag Junction Box
Pr Tag Equipment List
PR Document Tags
PR Assembly Tagged Items
PR Line Connections
PR Document Lines
PR :Lines
PR Document Tags
PR Tag Instrumentation
PR Tag Fire and Gas
Equipment Numbering
Scheme
DocumentNumbering
Scheme
Fire & Gas
Tags
Doc References
Attributes
Connections
Parent Tag
Valves
Tags
Doc References
Attributes
Connections
Parent Tag
Cables
Tags
Doc References
Attributes
Connections
Parent Tag
Lines
Tags
Doc References
Attributes
Connections
Parent Tag
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Facility Code (see 2.1)
Instrument identifier code(2-4 char’s, see 2.2.9)
System Number (see 2.3)
Train/Sub-system Identifier (see 2.7)
Sequence Number (000-999)
Suffix (see below)
AA(AA)-AA(AA) NN A NNN (A)
Consolidated Master Tag List• Tag Parsing
– Split tag into specific parts based on Tagging Scheme definition
• Tag validation– Lookups on Facility, Class, System
Back
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Your QA criteria…
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Data AnalysisData Source Number of Tags Number of Attributes Unpopulated Attributes % Populated
Alstom 1,013 72,619 19,273 26.54%Boustead 269 12,540 4,009 31.97%Burgess Manning 10 252 90 35.71%Copa 1,291 60,681 13,635 22.47%Genergy 63,913 4,793,484 880,563 18.37%Nuovo Pignone 578 14,471 6,632 45.83%Prosernat 8,045 370,100 70,615 19.08%Rolls-Royce 16,002 736,126 147,078 19.98%
SAFT-AEG Industrial 369 9,231 3,649 39.53%Wellinan 478 10,532 2,773 26.33%
Flowserv Pumps Limited 1,328 55,804 21,267 38.11%
Attribute Name Attribute Value Count PercentageCross Sectional Area 0.58 mm 203 10.00%
0.5 mm 475 23.41%0.75 mm 781 38.49%0.8 mm 202 9.96%1.5 mm 349 17.20%
TBA 15 0.74%15 mm 4 0.20%
Total 2029 100%
Low occurrence of a particular value may indicate
erroneous data
Low occurrence of a particular value may
indicate erroneous data
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Deployments in the Process Industry
• Houston• Singapore• Leatherhead (UK)• Agbami FPSO• Kashagan Project• Shell GTL Project• Gorgon
• In Salah Gas• In Amenas Gas• Azerbaijan ACG1• Azerbaijan Gunashli• Azerbaijan Shah Deniz• Clair (North Sea)• CIS Gas (ETAP)• BP Harding Area Gas• BP Skarv (Norway)• BP Alaska North Slope• BP Tangguh Indonesia• BP BTC Pipeline• BP South Caucasus Gas Pipeline SCP
• Alaska North Slope
•Edmonton Refinery
• Standard AutoPLANT environment• Lifecycle Server Base Configuration
• Houston• Aberdeen• Singapore• Agbami Project Nigeria• Gulf of Mexico (ACES)• Tahiti Project• Angola LNG Project• Gorgon Project• Wheatstone Project• Sanhua / Nemba Projects• Blind Faith Platform• TengizChevroil(TCO)
A Chevron/ConocoPhillips Joint Venture
•BritSats Platforms
Power Division – ISO 15926 / DQS Integration with PowerTrak
• London• Perth
• Global rollout• London (2010)
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