View
216
Download
1
Category
Tags:
Preview:
Citation preview
Engineering Productivity Measurement
Engineering Productivity Measurement
Research Team
Engineering Productivity Measurement
Research Team
Bob ShoemakerBE&K
Bob ShoemakerBE&K
CPI Conference 2001
Engineering Productivity Measurement
Bob Shoemaker
BE&K
Bob Shoemaker
BE&K
CPI Conference 2001
Engineering Productivity Measurement Research Team
Engineering Productivity Measurement Research Team
Bob Shoemaker BE&K, ChairJohn Atwell BechtelBill Buss Air ProductsLuh-Maan Chang Purdue UniversityGlen Hoglund Ontario HydroDuane McCloud FPL EnergyDeb McNeil DowNavin Patel ChemtexJohn Rotroff U.S. SteelKen Walsh Arizona State UniversityDenny Weber Black & VeatchTom Zenge Procter & Gamble
Bob Shoemaker BE&K, ChairJohn Atwell BechtelBill Buss Air ProductsLuh-Maan Chang Purdue UniversityGlen Hoglund Ontario HydroDuane McCloud FPL EnergyDeb McNeil DowNavin Patel ChemtexJohn Rotroff U.S. SteelKen Walsh Arizona State UniversityDenny Weber Black & VeatchTom Zenge Procter & Gamble
Problem StatementProblem Statement
• Engineering productivity measurement is a critical element of project performance
• Present practices do not work well in driving the improvement that today's design tools offer
• Surprisingly little effort has been expended in the engineering productivity arena
• Engineering productivity measurement is a critical element of project performance
• Present practices do not work well in driving the improvement that today's design tools offer
• Surprisingly little effort has been expended in the engineering productivity arena
Research ObjectivesResearch Objectives
• Determine present practices and why they do not work well
• Find productivity improvement success stories in other industries and learn from them
• Develop an Engineering Productivity Model that addresses shortcomings of present methods
• Test new model with pilot study
• Develop implementation plan
• Determine present practices and why they do not work well
• Find productivity improvement success stories in other industries and learn from them
• Develop an Engineering Productivity Model that addresses shortcomings of present methods
• Test new model with pilot study
• Develop implementation plan
Productivity LiteratureProductivity Literature
• Focuses on manufacturing, construction
• Little on engineering profession
• Biased toward tools or techniques
• Abundance of conclusions; lack of data
• Service professions focus on profit-based measures
• The software industry approach has applicability to engineering
• Focuses on manufacturing, construction
• Little on engineering profession
• Biased toward tools or techniques
• Abundance of conclusions; lack of data
• Service professions focus on profit-based measures
• The software industry approach has applicability to engineering
Software IndustrySoftware Industry
Lines of Code/hour did not work well
• Defined clear starting point
• Adjusted for complexity
• Adjusted for defects
• Developed standardized scoring system
• This proven methodology has driven significant improvement in the software delivery process
Lines of Code/hour did not work well
• Defined clear starting point
• Adjusted for complexity
• Adjusted for defects
• Developed standardized scoring system
• This proven methodology has driven significant improvement in the software delivery process
Present PracticesPresent Practices
Most companies:
• Track production of drawings and specifications versus budget
• Use % TIC as target engineering budget
• Use earned value concept in some form
• Have no uniform system of measurement
Most companies:
• Track production of drawings and specifications versus budget
• Use % TIC as target engineering budget
• Use earned value concept in some form
• Have no uniform system of measurement
Problems with Present Practices
Problems with Present Practices
• Lack of standards for format and content
• Difficulty in tracking actual effort dedicated to each deliverable
• No correlation between number of deliverables and installed quantities or effectiveness
• Computer-based tools:- Schematics and specs from database
- Physical drawings replaced by models
• Lack of standards for format and content
• Difficulty in tracking actual effort dedicated to each deliverable
• No correlation between number of deliverables and installed quantities or effectiveness
• Computer-based tools:- Schematics and specs from database
- Physical drawings replaced by models
Levels of ProductivityLevels of Productivity
Company EPC Work Process
Project
Overall Engineering
Deliverable
Individual
Discipline
Levels of ProductivityLevels of Productivity
Company EPC Work Process
Project
Overall Engineering
Deliverable
Individual
Discipline
Levels of ProductivityLevels of Productivity
Company EPC Work Process
Project
Overall Engineering
Deliverable
Individual
Discipline
Levels of ProductivityLevels of Productivity
Discipline
Company EPC Work Process
Project
Overall Engineering
Deliverable
Individual
Company EPC Work Process
Project
Overall Engineering
Deliverable
Individual
DisciplinesDisciplines
1.Civil/Structural
2.Architectural
3.Project Management
4.Procurement
5.Mechanical
6.Piping
7.Chemical Process
8.Mechanical Process
9.Electrical
10. Instrument/Controls
1.Civil/Structural
2.Architectural
3.Project Management
4.Procurement
5.Mechanical
6.Piping
7.Chemical Process
8.Mechanical Process
9.Electrical
10. Instrument/Controls
Engineering Productivity Model
Engineering Productivity Model
Input Quality Factor
Input Quality Factor
Scope & Complexity
Factor
Scope & Complexity
FactorXX XX
Hours Installed Qty.
Hours Installed Qty.
Effectiveness Factor
Effectiveness Factor
ProjectDefinitio
nRatingIndex
ProjectDefinitio
nRatingIndex
Project Characteristic
s
Project Characteristic
s
% Field Rework% Field Rework
Focus of Piping Pilot
XXRaw
Productivity
RawProductivit
y
ProjectDefinitio
nRatingIndex
ProjectDefinitio
nRatingIndex
Engineering Productivity Model
Engineering Productivity Model
Input Quality Factor
Input Quality Factor
Scope & Complexity
Factor
Scope & Complexity
FactorXX XX XX
RawProductivit
y
RawProductivit
y
Hours Installed Qty.
Hours Installed Qty.
Effectiveness Factor
Effectiveness Factor
Project Characteristic
s
Project Characteristic
s
% Field Rework% Field Rework
Engineering Productivity Model
Engineering Productivity Model
Input Quality Factor
Input Quality Factor
Scope & Complexity
Factor
Scope & Complexity
FactorXX XX XX
RawProductivit
y
RawProductivit
y
Hours Installed Qty.
Hours Installed Qty.
Effectiveness Factor
Effectiveness Factor
Project Characteristic
s
Project Characteristic
s
% Field Rework% Field Rework
ProjectDefinitio
nRatingIndex
ProjectDefinitio
nRatingIndex
Hours Installed Qty.
Hours Installed Qty.
Engineering Productivity Model
Engineering Productivity Model
Input Quality Factor
Input Quality Factor
Scope & Complexity
Factor
Scope & Complexity
FactorXX XX XX
RawProductivit
y
RawProductivit
y
Effectiveness Factor
Effectiveness Factor
Project Characteristic
s
Project Characteristic
s
% Field Rework% Field Rework
ProjectDefinitio
nRatingIndex
ProjectDefinitio
nRatingIndex
Hours Installed Qty.
Hours Installed Qty.
Engineering Productivity Model
Engineering Productivity Model
Input Quality Factor
Input Quality Factor
Scope & Complexity
Factor
Scope & Complexity
FactorXX XX XX
Effectiveness Factor
Effectiveness Factor
Project Characteristic
s
Project Characteristic
s
% Field Rework% Field Rework
ProjectDefinitio
nRatingIndex
ProjectDefinitio
nRatingIndex
RawProductivit
y
RawProductivit
y
Testing the Modelfor Piping DisciplineTesting the Model
for Piping Discipline
Projects analyzed: 40
Objectives- Screen for dominant influence factors- Verify input/output correlation for hrs/ft
Results- Established number of equipment pieces as a
dominant scope/complexity variable- Established good correlation between hrs/ft
and dominant variable
Learning- Valuable data is being ignored in detail
design phase of projects
Projects analyzed: 40
Objectives- Screen for dominant influence factors- Verify input/output correlation for hrs/ft
Results- Established number of equipment pieces as a
dominant scope/complexity variable- Established good correlation between hrs/ft
and dominant variable
Learning- Valuable data is being ignored in detail
design phase of projects
SummarySummary
This quantity-based model:
• Addresses shortcomings of present methods
• Allows progress tracking with present engineering tools
• Engineering and Construction on same project control basis
• Focuses engineering effort on capital investment
• Uses data already collected for construction productivity
• Is applicable to all industries and project types.
• Will continuously improve with use
This quantity-based model:
• Addresses shortcomings of present methods
• Allows progress tracking with present engineering tools
• Engineering and Construction on same project control basis
• Focuses engineering effort on capital investment
• Uses data already collected for construction productivity
• Is applicable to all industries and project types.
• Will continuously improve with use
What’s NextWhat’s Next
• Call to companies with expertise and interest in this previously neglected arena
• Develop detailed models for each discipline
• Implement on projects
• Industry use of standardized system for internal improvement and external benchmarking
Stake goes well beyond engineering cost
• Call to companies with expertise and interest in this previously neglected arena
• Develop detailed models for each discipline
• Implement on projects
• Industry use of standardized system for internal improvement and external benchmarking
Stake goes well beyond engineering cost
Implementation Session Panel
Implementation Session Panel
Deb McNeil Dow, Moderator
John Atwell Bechtel
Ken Walsh Arizona State
Tom Zenge Procter & Gamble
Deb McNeil Dow, Moderator
John Atwell Bechtel
Ken Walsh Arizona State
Tom Zenge Procter & Gamble
Implementation SessionImplementation Session
• Learn how the software industries’ experience validates the approach
• See what benefits to effective project delivery the future holds
• Learn the many different ways you can contribute to a significant improvement step in the EPC industry
• Learn how the software industries’ experience validates the approach
• See what benefits to effective project delivery the future holds
• Learn the many different ways you can contribute to a significant improvement step in the EPC industry
Recommended