© 2015, fiatech increasing productivity through integrated dimensional change detection and control
TRANSCRIPT
![Page 1: © 2015, Fiatech Increasing Productivity through Integrated Dimensional Change Detection and Control](https://reader036.vdocuments.us/reader036/viewer/2022081603/5697bfa31a28abf838c96b03/html5/thumbnails/1.jpg)
© 2015, Fiatech
Increasing Productivity through Integrated
Dimensional Change Detection and Control 0.100m ~ 0.120m
0.080m ~ 0.100m
0.200m ~ 0.220m>0.220m
0.180m ~ 0.200m
Position change
BIM
Point cloud
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© 2015, Fiatech
Presentation Flow
Presentation Takeaways/Deliverables
Opportunities Being Addressed
Constraints & Barriers
Approach & Benefits Realized
Future Work & Industry Adoption
Contact & More Information
Pres
enta
tion
Flow
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© 2015, FiatechPres
enta
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Take
away
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Presentation Takeaways/Deliverables
• Importance of coordinating field dimensional changes and model changes
• Cost, safety, and productivity implications of changes
• Limitations of current methods of dimensional change management
• Methods for automating dimensional change analysis
• Potential value of automatic change analysis (ACA)
• Risks, barriers and further development
Owner
Contractor
DesignerVirtual World: Models
Physical World
Control
Data
Changes, deviations!
(Gordon et al., 2006)
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© 2015, Fiatech
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Change Management and Productivity Problem:• Change management and verification is tedious
and error-prone, causing delays, wastes, and compromise performance
Challenges: • Interconnected dimensional changes• Interwoven objects in small spaces• “Cascading effects” of changes• Verification, validation, and avoidance of cost and
productivity impactsQuestions:• Which changes have higher impacts on the
downstream productivity and costs? • Which changes are more risky?• Could we anticipate changes?
(vision-systems.com)
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© 2015, Fiatech
Existing Change Analysis ToolsCurrent Approach:• Automatic data-model registration• Automatic comparing “nearest neighbors”
in images and as-designed models to get “deviation maps”
Limitations:• Incorrect data-model associations• Requires extensive engineering resources
to manually review and classify changes • Difficult to anticipate how local
deformations interact to drive global displacements
Cons
trai
nts
& B
arrie
rs
(Turkan, Bosche, & Haas, 2010)
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© 2015, Fiatech
Overcoming Incorrect Data-Model AssociationsProblem:• Matching data against model: which parts
in data and model have similar spatial contexts?
Spatial Context Matching:• Spatial relationships with neighboring
objects• Spatial contexts change less than absolute
geometriesVerification Study:• Preliminary studies prove the
effectiveness of spatial context matching on real data and model of ductworks
Appr
oach
& B
enefi
ts R
ealiz
ed
X
Y
Z
Duct 6
Duct 3
Duct 4
Duct 1
Duct 2
Duct 5
Context of duct 5: • Above four ducts• Intersecting with a duct• Parallel to two ducts• Perpendicular to three ducts
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© 2015, Fiatech
Automated Change Classification Approach
• Different spatial changes cause different patterns in spatial deviations
• Use computer vision algorithms to classify patterns of spatial deviations
Appr
oach
& B
enefi
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ealiz
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Spatial Change
Correspondence
Position Change
Dislocation Rotation
Shape Change
Elongation/
ShorteningCross-
Section Expanding/Shrinking
Concave/Convex
Missing Objects
Additional Objects
Wall rotation error
Building wing orientation error
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© 2015, Fiatech
Automatically Recognizing How Local Dimensional Changes will Impact Global Displacements
• Data-model association• Align data parts against models parts, and
obtain translation, rotation values• “Lock-in” registered data and model parts
for local dimensional change analysis• Clustering dimensional changes that occur
together and locate in proximity• Identify combinations of changes that
occur in many cases as “change patterns”• Follow the paths of change propagation• Anticipate potential rework and cost
related to changes
Appr
oach
& B
enefi
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SEG 2 (0.12)
SEG 3 (-0.05)
SEG 1 (0)SEG 6 (0.06)
SEG 14 (-0.06)
SEG 4 (-0.04)
SEG 9 (-0.09)
SEG 8 (-0.21)
SEG 11 (-0.14)
SEG 5 (-0.06)
SEG 7 (-0.05)
SEG 12 (-0.08)
SEG 10 (0.05)
SEG 13 (-0.13)
JOINT 5
JOINT 2
JOINT 4
JOINT 9
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© 2015, Fiatech
Automatic Change Analysis (ACA): Underway
• Large-scale testing of data-model association and change detection methods
• Developing more reliable change classification algorithms
• Developing robust “local” registration method for separating local and global changes
• Quantifying “cascading effects” of changes in terms of productivity and costs
• Leverage laser-based measurement technologies
Futu
re W
ork
& In
dust
ry A
dopti
on
Data-Model Association
Spatial Change Classification
Spatial Change Correlation
• Segmentation of 3D data• Geometric primitive extraction• Local spatial context generation• Local spatial context matching
• Spatial change taxonomy• 3D pattern classification
• Spatial change clustering• Statistical correlation analysis
Outputs• Relational graphs extracted from data and
the as-designed model• Spatial contexts of each object (duct) in the
data and the as-designed model• Matches between data and a-designed
objects
Outputs• Classified changes
Duct 1
Duct 2
Duct 3
Duct 4
Duct 5
Duct 6
Parallel
Perpendicular
PerpendicularPerpendicular
Parallel
Perpendicular
Perpendicular
Parallel
Perpendicular
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© 2015, Fiatech
Industry Adoption: ProposedDefine and launch a Fiatech project:• Capitalize on a $0.5M NSF research grant• Interviews and surveys for potential barriers
of adopting automatic change analysis• Pilot studies: field data collection along with
relevant productivity and cost data of projects
• Cost-benefit analysis based on pilot studies• Diversifying the types of projects: building
construction, civil infrastructures• User-interface design: help from human-
computer interface scientists & engineers
Futu
re W
ork
& In
dust
ry A
dopti
on
Data-Model Association
Spatial Change Classification
Spatial Change Correlation
• Segmentation of 3D data• Geometric primitive extraction• Local spatial context generation• Local spatial context matching
• Spatial change taxonomy• 3D pattern classification
• Spatial change clustering• Statistical correlation analysis
Outputs• Relational graphs extracted from data and
the as-designed model• Spatial contexts of each object (duct) in the
data and the as-designed model• Matches between data and a-designed
objects
Outputs• Classified changes
Duct 1
Duct 2
Duct 3
Duct 4
Duct 5
Duct 6
Parallel
Perpendicular
PerpendicularPerpendicular
Parallel
Perpendicular
Perpendicular
Parallel
Perpendicular
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© 2015, Fiatech
Thank You… Are There Any Questions?
Name: Pingbo TangTitle: Assistant ProfessorCompany: Arizona State UniversityEmail: [email protected] Links: https://sites.google.com/site/tangpingbo/ Office: 480-727-8105Fax: 480-965-1769
Cont
act &
Mor
e In
form
ation
Increasing Productivity through Integrated
Dimensional Change Detection and Control
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© 2015, Fiatech
Increasing Design Efficiency
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© 2015, Fiatech
Increasing Design Efficiency
Presentation Takeaways/Deliverables
Opportunities Being Addressed
Constraints & Barriers
Approach & Benefits Realized
Future Work & Industry Adoption
Contact & More Information
Pres
enta
tion
Flow
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© 2015, FiatechPres
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Take
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GENERATIVE DESIGN
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© 2015, FiatechPres
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Take
away
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Key Topics & Takeaways
1. Paradox of design2. Lean design technique – Set-Based Design3. Choice overload4. Application of the Generative Design PROCESS
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© 2015, Fiatech
Presentation Flow
Presentation Takeaways/Deliverables
Opportunities Being Addressed
Constraints & Barriers
Approach & Benefits Realized
Future Work & Industry Adoption
Contact & More Information
Pres
enta
tion
Flow
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© 2015, Fiatech
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54%
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Title in Calibri 32pt
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© 2015, Fiatech
Opp
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WASTE
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© 2015, Fiatech
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Paradox of DesignWe can’t make correct
decisions without knowing what the results will be…
…You can’t know the results without making decisions.
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© 2015, Fiatech
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Paradox of Design
Design Validation
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© 2015, Fiatech
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Stop ValidatingStart Simulating
Break the Paradox
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© 2015, Fiatech
Presentation Flow
Presentation Takeaways/Deliverables
Opportunities Being Addressed
Constraints & Barriers
Approach & Benefits Realized
Future Work & Industry Adoption
Contact & More Information
Pres
enta
tion
Flow
![Page 24: © 2015, Fiatech Increasing Productivity through Integrated Dimensional Change Detection and Control](https://reader036.vdocuments.us/reader036/viewer/2022081603/5697bfa31a28abf838c96b03/html5/thumbnails/24.jpg)
© 2015, Fiatech
Linear Design ProcessCo
nstr
aint
s &
Bar
riers
Collect Info.
Revise Decisions
Develop Design
VALIDATE one option
Make INTUITIVE Decision
1 2 3 4 5
RE-WORK
Multiple Iterations, minimal data
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© 2015, Fiatech
Cons
trai
nts
& B
arrie
rs
How to Lean Design?
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© 2015, Fiatech
Set-Based Design (SBD)Co
nstr
aint
s &
Bar
riers
Shape / massing
Orientation
Structural System
Envelope Systems
Lighting System
HVAC System
SINGLE SET
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© 2015, Fiatech
Cons
trai
nts
& B
arrie
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3
+ 3
+ 3
+ 3
+ 3
+ 3
Shape / massing
Orientation
Structural System
Envelope Systems
Lighting System
HVAC System
SINGLE SET
SBD – Technical Challenge
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© 2015, Fiatech
Cons
trai
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& B
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3
x 3
x 3
x 3
x 3
x 3
Shape / massing
Orientation
Structural System
Envelope Systems
Lighting System
HVAC System
= 729
SBD – Technical Challenge
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© 2015, Fiatech
SBD – Technical ChallengeCo
nstr
aint
s &
Bar
riers
3 = 3
3 x 3 = 9
9 x 3 = 27
27 x 3 = 81
81 x 3 = 243
243 x 3 = 729
Shape / massing
Orientation
Structural System
Envelope Systems
Lighting System
HVAC System
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© 2015, Fiatech
What if?Co
nstr
aint
s &
Bar
riers
Image courtesy of Beck Technologies
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© 2015, Fiatech
SBD – Behavioral ChallengeCo
nstr
aint
s &
Bar
riers
CHOICE OVERLOAD
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© 2015, Fiatech
Cons
trai
nts
& B
arrie
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30% 3%
SBD – Behavioral Challenge
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© 2015, Fiatech
Set Based Design ChallengesCo
nstr
aint
s &
Bar
riers
Need to simulate more optionsHOWEVER
More options lead to difficult decision making
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© 2015, Fiatech
Presentation Takeaways/Deliverables
Opportunities Being Addressed
Constraints & Barriers
Approach & Benefits Realized
Future Work & Industry Adoption
Contact & More Information
Pres
enta
tion
Flow
Presentation Flow
![Page 35: © 2015, Fiatech Increasing Productivity through Integrated Dimensional Change Detection and Control](https://reader036.vdocuments.us/reader036/viewer/2022081603/5697bfa31a28abf838c96b03/html5/thumbnails/35.jpg)
© 2015, Fiatech
Linear Design ProcessAp
proa
ch &
Ben
efits
Rea
lized
Collect Info.
Revise Decisions
Develop Design
VALIDATE one option
Make INTUITIVE Decision
1 2 3 4 5
RE-WORK
Multiple Iterations, minimal data
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© 2015, Fiatech
Rapid Virtual PrototypingAp
proa
ch &
Ben
efits
Rea
lized
Collect Info.
Simulate & Analyze
Develop ONE time
Make INFORMED
Decision
1 32
4Next
Decision Set
ONE iteration, more data
Simulate & Analyze
2
Simulate & Analyze
2
Multiple data sets
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© 2015, Fiatech
AEC Application: Rapid Trade-off AnalysisAp
proa
ch &
Ben
efits
Rea
lized First cost
vs. Life-cycle energy
1
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Simulation ToolkitAp
proa
ch &
Ben
efits
Rea
lized
MODELENER
GY COSTImage courtesy of Sefaira
2
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Collect Glazing InformationAp
proa
ch &
Ben
efits
Rea
lized
~60 min
2
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Tools: ModelingAp
proa
ch &
Ben
efits
Rea
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~45 min
2
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© 2015, Fiatech
Rapid Energy SimulationAp
proa
ch &
Ben
efits
Rea
lized
~60 min
2
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Data AggregationAp
proa
ch &
Ben
efits
Rea
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~15 min
2
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Graphic AnalysisAp
proa
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Ben
efits
Rea
lized
~90 min
2
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© 2015, Fiatech
Simulation AnalysisAp
proa
ch &
Ben
efits
Rea
lized
2
36 glazing options1 scheme4.5 hours
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Opp
ortu
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s Be
ing
Addr
esse
d
WASTE
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© 2015, Fiatech
Presentation Takeaways/Deliverables
Opportunities Being Addressed
Constraints & Barriers
Approach & Benefits Realized
Future Work & Industry Adoption
Contact & More Information
Pres
enta
tion
Flow
Presentation Flow
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© 2015, Fiatech
Solution to SBD ChallengesAp
proa
ch &
Ben
efits
Rea
lized
Outside the
AEC Box
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Penn State Applied Research LabAp
proa
ch &
Ben
efits
Rea
lized
Image courtesy of Penn State Applied Research Lab
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Penn State Applied Research LabAp
proa
ch &
Ben
efits
Rea
lized
Image courtesy of Penn State Applied Research Lab
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Penn State Applied Research LabAp
proa
ch &
Ben
efits
Rea
lized
Image courtesy of Penn State Applied Research Lab
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Jet Propulsion Laboratory (JPL)Ap
proa
ch &
Ben
efits
Rea
lized
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Appr
oach
& B
enefi
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ealiz
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VTCC Case Study: Cost Optimization
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VTCC Case Study: East FacadeAp
proa
ch &
Ben
efits
Rea
lized
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VTCC Case Study: Energy OptimizationAp
proa
ch &
Ben
efits
Rea
lized
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Appr
oach
& B
enefi
ts R
ealiz
ed
VTCC Case Study: Cost Optimization
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Appr
oach
& B
enefi
ts R
ealiz
ed
Potential of Removing the Rework Loop
Team = 6-7 people @ $120/hr
Average of 40 hours each= $33,600
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Appr
oach
& B
enefi
ts R
ealiz
ed
Removing the Rework Loop
x 24 major decisions
= $806,000
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Appr
oach
& B
enefi
ts R
ealiz
ed
Methodology Benefits
Cut design duration in half or more?Solve more problems in the same time?
Do more with less?
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Process ChangeFu
ture
Wor
k &
Indu
stry
Ado
ption
Develop many solutions Analyze options
Prioritize decisions
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© 2015, Fiatech
Thank You… Are There Any Questions?
Jason A. ReeceTechnology Innovation & ImprovementBalfour Beatty [email protected]/in/jar321
Cont
act &
Mor
e In
form
ation Increasing Design
Efficiency
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Knowledge Mining: Experience Capture & Sharing
- Not important – Who cares??- Coming Soon to a Project Near You??- Utopian Dream??- Distant Future??
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Presentation Flow
Construction’s Incredible Knowledge Intensity
Where Knowledge Lives
Mating: How Problems Find Knowledge
Possible Approach & Benefits Realized
Barriers
Contact info
Pres
enta
tion
Flow
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Pres
enta
tion
Take
away
s/D
eliv
erab
les
Extraordinary Density of Embedded Knowledge
• Not obvious to those at arm’s length
• Complexity reduced in a well-defined system
• Each material has its own complexities
• Each interface between materials • Requires situation-specific knowledge • Small ignorance may = big problem
• Procedural vs. situational knowledge• Bid system adds cost optimization to the
knowledge embedded in a particular prototype
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© 2015, Fiatech
Opp
ortu
nitie
s Be
ing
Addr
esse
d
How do problems meet up with knowledge?
• IF the problem is common & mastered• Then it’s not a problem anymore
• IF the problem is highly specific Then • Narrow specialists with knowledge or• Bungled task (partly or fully)
• To avoid problem (e.g. at left) • Find and read an academic paper?• Search online (and pay for info?)?• Use a deep specialist
• Informally transmit knowledge collegially
• How can more people learn from others?
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Benefits and Possible Approach• Effective sharing of knowledge => reduced
project costs and risks.
• Software (non-trivial) + social change (very very large challenge) is required
• Must engage and incentivize knowledge holders (big challenge).
• Users must engage and love using it
• Involve many trade associations (are incumbent orgs. “owning” knowledge)
• Find various interested companies
• Create a committed eco-system
Cons
trai
nts
& B
arrie
rs
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Barriers In ascending order of importance:
• Legal – fully indemnify contributors
• $ Cost to create software and participation
• Needs exquisitely usable software
• Maintenance of data
• Get a wide range of committed sponsors
• Vetting of contributions and contributors
• Getting contributors
• Getting users
• Getting Creating the virtuous circle of use and contribution (Wikipedia and eBay, sim.)
Appr
oach
& B
enefi
ts R
ealiz
ed
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© 2015, Fiatech
Thank You… Are There Any Questions?
Leo SchlosbergCary Concrete Products, Inc. Email: [email protected]: www.caryconcrete.comBlog: www.planetcommercialconstruction.wordpress.com
An earlier and more detailed version of this presentationcan be found at: http://www.caryconcrete.com/writings/index.php?page=writings
Cont
act &
Mor
e In
form
ation Sharing knowledge
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Achieving Effective Information Specifications
Management
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Integrated Design Practices
Objective:To provide clarity on the process to document the Information Specifications Management strategy to meet & exceed Customer “Data Centric” project Information Handover Specification requirements.
• What systems are being utilised?• What data is being produced, consumed,
reused and turned over?• What are the applicable data standards? • What are the applicable data QA &
validation rules?
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Presentation Flow
Information Governance – Class Library
Standards Driven – Data Management
Project & Customer specific Class Library Management
Approach & Benefits Realized
Future Work & Industry Adoption
Contact & More Information
Pres
enta
tion
Flow
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© 2015, FiatechInfo
rmati
on G
over
nanc
e –
Clas
s Li
brar
y
Engineering Data Warehouse (EDW)
Information Governance – Class Library
Tag and Document Numbering Specifications
Customer ‘Data Centric’ Information Handover Spec.
Industry Standards i.e. ISO 15926, BIM etc.
Data Validation Rules
Customer and Project Specific Configuration
Project Delivery Systems
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© 2015, FiatechStan
dard
s D
riven
– D
ata
Man
agem
ent
Data Validation Rules (Standards Conformance)
Customer specific ‘Data Centric’ information handover specifications
WorleyParsons Standard Class Library
Stan
dard
Del
ivery
Con
figur
atio
n
Engineering Data Warehouse (EDW)(Consolidated & Validated) Pr
ojec
t & C
usto
mer
spe
cific
Conf
igur
atio
n
Customer Specified Configuration
Project Delivery Systems(Authoring Applications)
Tag & Document No. SpecificationsNaming Rules
Functional / Physical Classes & AttributesValidation RulesLife Cycle Rules
Industry Standard MappingsAuthoring Application Data Mappings
Class LibraryTag & Document No. Specifications Information Handover Specification
Validation RulesIndustry Standards
Publish & Compare
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© 2015, Fiatech
Proj
ect &
Cus
tom
er s
peci
fic C
lass
Lib
rary
Man
agem
ent
Customer specific ‘Data Centric’ Information Handover
Electrical
EDMS
Customer/Project
Specific
Class Library(Layer 3)
Project
Configuration
SupplierContent
Project
Configuration
3D Modeling
Project
Configuration
Project
Configuration
Inst. & Control
Project
Configuration
P&IDProject
Configuration
Mechanical
Datasheets
Project
Configuration
MTR
Engineering Data Warehouse
Project
Configuration
Electrical
EDMSProject
Configuration
SupplierContent
Project
Configuration
3D Modeling
Project
Configuration
Project
Configuration
Inst. & Control
Project
Configuration
P&IDProject
Configuration
Mechanical
Datasheets
Project
Configuration
MTR
Engineering Data WarehouseGoal: To meet & exceed Customer information handover expectations
Project
Configuration
Project Specific Configuration
ProjectSpecific
Class Library(Layer 2)
ProjectSpecific
Class Library(Layer 2)
CustomerSpecific
Class Library(Layer 1)
Tag, Document
NamingStandards(Layer 0)
Industry Standards
i.e. ISO 15926(Layer 0)
WorleyParsons
Standard Class
Library(Layer 0)
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Appr
oach
& B
enefi
ts R
ealiz
ed
Physical ClassesNo. of Physical Attributes
mapped to Project Delivery Systems.
Functional Document Types
No. of Functional Document Types Mapped.
ISO 15926 StandardNo. of Physical Attributes
mapped to ISO 15926 RDL
Engineering Data Warehouse
No. of integrated Project Delivery Systems mapped to
Class Library
ISO 15926 StandardNo. of Functional Classes
mapped to ISO 15926 RDL in Class Library
Units of Measure Classes
No. of Units of Measure Classes
39%156
435%
11
200
55
Life Cycle TypesNo. of Life Cycle data types across Define, Execute and
Operate phases.
10
Functional AttributesNo. of Functional Attributes mapped to Project Delivery
Systems
400
Equipment Function Codes
No. of Equipment Function Codes Mapped (Excluding
Piping Line Numbers)
613
Instrument Function Codes
No. of ANSI/ISA Instrument Function Codes Mapped
391
Physical Document
TypesNo. of Physical Document
Types Mapped.
98
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Futu
re W
ork
& In
dust
ry A
dopti
on
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© 2015, Fiatech
Thank You… Are There Any Questions?
Cormac RyanManager, Project Data [email protected]
Photo
Cont
act &
Mor
e In
form
ation Achieving Effective Information
Specifications Management