AVEVA World Conference NA - Jeyoung Woo, University of Texas at Austin

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Presentation Overview
The quality and completeness of engineering design
deliverables have a significant impact on overall project
performance. Thus, project stakeholders should pay close
attention to such issues, with a particular focus on problematic
engineering design deliverables.
This presentation summarizes the findings of the Construction
Industry Institute (CII) Research Team (RT) 320, Definition and
Measurement of Engineering/Design Deliverable Quality,
including the 11 most problematic deliverables and their
significant defects, causal factors, leading/lagging metrics, and
two implementation tools.

Houston, TX.
February 14, 2018
James T. O’Connor, P.E., Ph.D.
Jeyoung Woo, P.E.
Eliminating Quality Defects
on Problematic Engineering
Design Deliverables

~ $75 billion/year
5.4% of total construction cost
Leading cause = Design Errors/Omissions!
14.2 % of Contract value
Direct + Indirect
Case for Action (1/2)
Direct Cost of Rework (CII 2004)
Cost of Rework (Hwang et al. 2009)
Average Cost of Design Errors (Love et al. 2014)

Case for Action (2/2)
Impact of Design Quality
Poor quality
deliverables
Design
Phase
Construction
Phase
Rework
Project
Performance
(Burati et al. 1992; Eldin 1991; Gransberg and Molenaar 2004; Haydl and Nikiel 2000)

Dale C. Allen Shell
Ronald August, Jr. AECOM
Robert Beskow Chevron
Lin Budlong General Electric
Daniel C. Chabot Cargill, Inc.
Michael T. Cleary DuPont
Kim Crovetto Hargrove
John Hyland Lauren
Oscar L. Monagas ConocoPhillips
Donald L. Myers U.S. Department of VA
CII Research Team (RT) 320
Period: 2014/09 – 2016/08
21 Members
Dr. James T. O'Connor UT-Austin
Jason Phillips ArcelorMittal
Glenn Raz OXY
Matt Rouse CDI
Hulya Schwimmbeck CB&I
Joel K. Strang Fluor
Gilberto Teixeira Jr. Petrobras
Kelly Watson OXY
Nancy E. Wilkie U.S. DoS
Jeyoung Woo UT-Austin
Carlton Wright Technip

Research Objectives
• Identify problematic design deliverables,
their defects & causes, and metrics that
facilitate proactive, preventive actions
(O’Connor and Woo 2016)

IN-Scope Design deliverable completeness & correctness
Design errors and omissions
OUT-of-scope Cost of design efforts
Cost estimate based on engineering deliverables
Research Scope
Detailed design phase of industrial projects
Concept Detailed scope
Procurement
Fabrication/
Delivery
Construction
Detailed Design
Project Funding Approval IFC (Issued for Construction)

Design Quality Essentials
Essential criteria of design quality
Timely
Quality
(Andi and Minato 2003; O’Connor et al. 2007; Tilley et al. 1997)

Research Flow: Facilitating Action
Team
Action
Quality
Detailed
Design
53 Detailed
Design
Deliverables
11
Problematic
Deliverables
Causal
Factors
(n=351)
Leading/Lagging
Metrics (n=141)
& Definitions
TWO Tools
- Leading Metrics Tool
- Completeness Checklist
Usage:
Awareness
Deliverable
Quality
Threats
Validation:
Application
Demonstration
(798 Defects)
3 Defect
Categories
Priorities
Defect
Impacts
Frequency Severity

Research Methodology
53
DELIVERABLES
11 Problematic
Deliverables
798
DEFECTS
145
UNIQUE
DEFECTS
73 Significant Defects 349 Causal Factors
23 Lagging Metrics 118 Leading Metrics
Frequency
Consolidation
Impact priority
Two Implementation Tools (DDQA / CDDC)

53 Engineering Design Deliverables (1/2)
No. Deliverable No. Deliverable
1 Front-End Engineering Design (FEED) Validation 14 3D Model
2 Piping material classes 15 Standard piping details
3 Process data sheets 16 Standard civil details
4 Mechanical data sheets 17 Standard site details
5 Instrument data sheets 18 Standard architecture details
6 Piping & Instrumentation Diagrams (P&IDs) 19 Standard electrical details
7 Stress critical line list 20 Vendor data
8 Line list requiring hydraulic check 21 Equipment list
9 Plot plan 22 Mechanical equipment model volumes
10 Safety review 23 Duct model volumes
11 Constructability Inputs 24 Single line routing
12 Maintainability Inputs 25 Cable/ cable tray routing
13 Level 3 Baseline Schedule 26 Cathodic protection

53 Engineering Design Deliverables (2/2)
No. Deliverable No. Deliverable
27 Structure modeling 40 Underground services
28 Electrical equipment/building envelopes 41 Piping routing and isometrics
29 Control equipment/building envelopes 42 Stress analysis
30
Nozzles, ladders, and platforms for
towers/vessels/tanks
43 Hydraulic checks
44 Model updates
31 3D model reviews 45 Bulk material takeoff
32 Structural stress loads 46 Equipment specifications
33 Structure design 47 Inline instrument data
34 Fire protection study 48 Miscellaneous pipe supports drawings
35 Earthwork 49 Electrical design
36 Roads 50 Junction box location
37 Piling 51 Instrumentation design
38 Foundations 52 Lighting
39 Fencing 53 Clash detection

Survey questionnaire
Relative frequency of quality problematic deliverables
Survey respondents
Problematic Deliverables
Survey Design
Option Very Rarely Sometimes Too Often Don’t know
Point value 1.0 3.0 5.0 0.0
Owner Contractor Total
Number of respondents 34 33 67
Industry
Experience
Total years 861 1,063 1,924
Average years 25.3 32.2 28.7

Distribution of Results
46. Equipment Specifications & Data Sheets
6. P&IDs (Piping & Instrumentation Diagrams)
11. Constructability Inputs
13. Level 3 Baseline Schedule
20. Vendor Data
30. Nozzles, Ladders, and Platform for Towers/Vessels/Tanks
48. Miscellaneous Pipe Support Drawings
41. Piping Routing and Isometrics
1. FEED (Front-End Engineering Design) Validation Deliverables
12. Maintainability Inputs
14. 3D Model & 53. Clash Detection

Survey Results
Scale: 1.0 = Very Rarely 3.0 = Sometimes 5.0 = Too Often
41 (77%)
10 (19%)
2 (4%)
0
5
10
15
20
25
30
35
40
45
Less than 3.0 3.0 - 3.5 Greater than 3.5
NumberofDeliverables
(n=53)
Most Problematic

Validation: Statistical Analysis (t-Test)
Problematic vs. Non-Problematic Deliverables: Very Different
Owners vs. Contractors (11 Prob. Deliverables): Very Similar
Problematic
Deliverables
(n=11)
Other
Deliverables
(n=41)
Mean St.Dev. Mean St.Dev. t-score df p-value
Relative Frequency of
Design Quality Problems
3.22 0.28 1.92 0.49 11.43 29
<.001
(Sig.)
Owners
(n=34)
Contractors
(n=33)
Mean St.Dev. Mean St.Dev. t-score df p-value
Relative Frequency of
Design Quality Problems
3.25 0.09 3.19 0.11 0.68 10
0.50
(N.S)

Impact Screening
Type: Completeness, Correctness, and Timeliness
Data Analysis
Defects
Causal Factors
Leading Metrics
Lagging Metrics
Identified by using “5-Whys” approach
Associated with 349 causal factors
Associated with 73 significant defects

Data Analysis
Example (1/4)
Deliverable:
Constructability
Inputs
Defects
Failure to develop and
incorporate standard
design elements

Data Analysis
Example (2/4)
Deliverable:
Constructability
Inputs
Defects Defect Impacts
design elements
Design and
construction
productivity losses

Data Analysis
Example (3/4)
Deliverable:
Constructability
Inputs
DefectsCausal Factors Defect Impacts
design elements
Failure to recognize
the beneficial tradeoffs
from standardization
Design and
construction
productivity losses

Data Analysis
Example (4/4)
Deliverable:
Constructability
Inputs
DefectsCausal Factors Defect Impacts
Leading Metrics Lagging Metrics
Did the project owner and/or contractor
utilize standardization resources during
the design (e.g., PIP.org or its equivalent
in other industry sectors)?
Field rework hours resulting
from inadequate
constructability input/reviews

Defects Analysis Table
No. 3. Constructability Inputs
No. Significant Defect
Defect
Type
Impact
Type
Relative
Freq.
Relative
ImpactSev.
Priority
Score
Causal Factor
Metric
Leading
Lagging
10
Constructability
reviews are
conducted too late
Timeliness
- Late or additional
changes
- Redesign
- Schedule impacts
- Increased cost
H H 9
- Not involving knowledgeable resources at the right
time
- Not scheduling constructability reviews at the right
time (sufficiently in advance)
- Low schedule priority of constructability reviews
- Late contractor involvement in constructability
- Disincentives for contractors to participate in
Constructability
- Lack of contractor interest in pre-construction
services
1) At least one constructability review meeting is conducted in early FEED/ Design Development or
before?
2) The second constructability review meeting is conducted at or before the end of FEED/ Design
Development?
3) The third constructability review meeting is conducted at or before the 60% design complete?
4) Were the constructability reviews conducted too late to incorporate comments into the design?
Leading
Leading
Leading
Lagging

Timing of Metrics
Concept Detailed scope
Procurement
Fabrication/
Delivery
Construction
Detailed Design
FV 1 30% 2 60% 2 90% 2 IFC 3 IFP 4
Leading Indicators
Lagging Indicators
1 FV: FEED Validation
2 30%, 60%, 90%: Detailed Design Progress
2 IFC: Issued for Construction
3 IFP: Issued for Procurement

Helps assess current levels of deliverable quality
Helps identify associated potential defects
Facilitates planning/documentation of defect mitigation
strategies
Two Implementation Tools
Design Deliverable Quality Assessment (DDQA) Tool
Completeness of Design Deliverable Checklist (CDDC) Tool
Helps assess current level of deliverable completeness
Helps identify content inclusion items that need to be
completed

DDQA Tool
Input
- Targeted Design Deliverables
- Targeted Design Progress
- Leading Metrics

DDQA Tool
Output
- Design Quality Indices - List of Potential Defects
(Prompting discussion)

CDDC Tool
Input
- Targeted Design Deliverables - Completeness of Checklist Items

CDDC Tool
Output
- Completeness Index - List of Incomplete Items

Recommended Timing of
Completeness Assessment
No. Deliverable
Detailed Design Progress
FV1 30%2 60%2 90%2 IFC3
1 Front-End Engineering Design (FEED) Validation X
2 Level 3 Baseline Schedule X
3 Constructability Inputs X X
4 Piping & Instrumentation Diagrams (P&IDs) X
5 Equipment Specifications & Data Sheets X X
6 Maintainability Inputs X X
7 Vendor Data X X
8 3D Model & Clash Detection X X
9 Piping Routing & Isometrics X X
10 Nozzles, Ladders, Platforms for Towers/Vessels/Tanks X X
11 Miscellaneous Pipe Support Drawings X1 FV: FEED Validation
2 30%, 60%, 90%: Detailed Design Progress
3 IFC: Issued for Construction

Tool-related Responsibilities
Responsibility Job Titles
Sponsor
• Business Unit Engineering Director
• Business Unit Quality Director
Accountable
• Project Managers (Owner and/or Contractor)
• Project Design/Engineering Manager
Responsible
• Design Discipline Leads
• Project Engineer/Coordinator
Consult
• Construction Managers
• Maintenance Representatives
• Operations Representatives
• Project Controls Representatives

Tool Validation
18+ yrs. experience each
18 External Reviewers
215 Feedback Comments
18 External Reviewers
Mostly Compliments
Most others Already Addressed, Minor, or Out-of-Scope
“Effective” in contributing to Project Design Quality
“Likely” to be used on future project

Conclusions
• Identified 11 most problematic deliverables
• Identified 73 significant defects for problematic deliverables
• Identified 118 leading metrics associated with causal factors
• Identified 23 lagging metrics associated with 73 defects
• Developed Two implementation tools (DDQA / CDDC)

Acknowledgements
Construction Industry Institute (CII)
CII Research Team 320
103 Survey Respondents
67 respondents for problematic deliverables survey
36 respondents for deliverable defects survey
Dale C. Allen Shell
Ronald August, Jr. AECOM
Robert Beskow Chevron
Lin Budlong General Electric
Daniel C. Chabot Cargill, Inc.
Michael T. Cleary DuPont
Kim Crovetto Hargrove
John Hyland Lauren
Oscar L. Monagas ConocoPhillips
Donald L. Myers U.S. Department of VA
Dr. James T. O'Connor UT-Austin
Jason Phillips ArcelorMittal
Glenn Raz OXY
Matt Rouse CDI
Hulya Schwimmbeck CB&I
Joel K. Strang Fluor
Gilberto Teixeira Jr. Petrobras
Kelly Watson OXY
Nancy E. Wilkie U.S. DoS
Jeyoung Woo UT-Austin
Carlton Wright Technip

References
Andi and Minato, T. (2003) “Design documents quality in the Japanese construction industry.” Int’l J. Project Management, 21. 537-546.
Burati, J.L, Farrington, J.J., and Ledbetter, W.B. (1992). “Causes of Quality Deviations in Design and Construction.” J. Construction
Engineering and Management, 118(1), 34-49.
Construction Industry Institute (CII) (2004). “Making Zero Rework a Reality.” Research Summary 203-1. Austin, TX.
East, E.W., Kirby, J.G. and Perez, G. (2004). “Improved Design Review through Web Collaboration.” J. Management in Engineering, 20 (2),
51-55.
Eldin, N. N. (1991). “Management of Engineering/Design Phase.” J. Construction Engineering and Management, 117 (1), 163-175.
Gransberg, D.D., and Molenaar, K. (2004). “Analysis of Owner’s Design and Construction Quality Management Approaches in
Design/Build Projects.” J. Management in Engineering, 20 (4), 162-169.
Haydl, H.M. and Nikiel, A.W. (2000). “Design and Construction Errors – Case Studies.” Practice Periodical on Structural Design and
Construction, 5 (3), 126-130.
Hwang, B., Thomas, S., Haas, C., and Caldas, C. (2009). “Measuring the Impact of Rework on Construction Cost Performance.” J.
Construction Engineering and Management, 135(3), 187-198.
Love, P., Lopez, R., Kim, J., and Kim, M. (2014). “Probabilistic Assessment of Design Error Costs.” J. Performance of Constructed Facility,
28(3), 518-527
Nigro, W. T. (2013). “RediCheck Interdisciplinary Coordination.” 4th Edition, Peachtree City, GA.
O’Connor, J.T., O'Brien, W.J., Jarrah, R.T., and Wallner, B. (2007). “Planning for facilitating, and evaluating design effectiveness”
Research Report 233-11, Construction Industry Institute, The University of Texas at Austin, Austin, TX.
O’Connor, J.T., and Woo, J. (2016). “Study of Engineering/Design Deliverable Quality.” Research Report 320-11, Construction Industry
Institute, The University of Texas at Austin, Austin, TX.
Soibelman, L., Liu, L. Y., Kirby, J.G., East, E.W., Caldas, C.H., and Lin, K. (2003). “Design Review Checking System with Corporate
Lessons Learned.” J. Construction Engineering and Management, 129 (5), 475-484.
Tilley, P., Wyatt A., and Mohamed, S.. (1997) "Indicators of design and documentation deficiency." IGLC-5: Proceedings of the Fifth
Annual Conference of the International Group for Lean Construction, 16-17 July, 1997, Gold Coast, Australia.

Jeyoung Woo / P.E., P.M.P
Ph.D. Candidate
The University of Texas at Austin
woo.jeyoung@utexas.edu

This presentation may include predictions, estimates, intentions, beliefs
and other statements that are or may be construed as being forward-
looking. While these forward-looking statements represent our current
judgment on what the future holds, they are subject to risks and
uncertainties that could result in actual outcomes differing materially from
those projected in these statements. No statement contained herein
constitutes a commitment by AVEVA to perform any particular action or to
deliver any particular product or product features. Readers are cautioned
not to place undue reliance on these forward-looking statements, which
reflect our opinions only as of the date of this presentation. The Company
shall not be obliged to disclose any revision to these forward-looking
statements to reflect events or circumstances occurring after the date on
which they are made or to reflect the occurrence of future events.

AVEVA World Conference NA - Jeyoung Woo, University of Texas at Austin

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