SlideShare ist ein Scribd-Unternehmen logo
1 von 13
Downloaden Sie, um offline zu lesen
Bridge Data Guidelines for Asset
   Management of Road Bridges
                    Simon Bush: Opus Consultants
          Piotr Omenzetter: University of Auckland
       Theuns F. P. Henning: University of Auckland
                Peter McCarten: Opus Consultants
Our role as asset managers
• How do you prove you are contributing to national strategic
  outcomes?
• How do you prove you are achieving value from money from
  bridge management funding?
• Why? Our role is to ensure the assets we manage provide for
  the nations needs and therefore support the economy
• How? Through the use of an advanced asset management
  approach
It is important to get it right
• Close to 18000 bridges nationally (circa 4500 on state
  highways and 13500 on Local roads).
• On average a bridge every 5km nationally and every 2.5km
  on state Highways. New Zealand therefore functions on its
  bridges.
• Aging local bridge stock
New Zealand bridge asset management
• NZGAO 2003: Limited evidence of an advanced asset
  management approach
• USGAO 2008: The bridge program does not fully align with GAO’s
  principles… …in that the program lacks focus, performance
  measures. For example, the program’s statutory goals are not
  focused on a clearly identified federal or national interest.
• NZGAO 2010: As asset information improves over time, there is a
  need to ensure the information is cost-effective to collect, and is
  as complete and up to date as possible, and remains useful.
New Zealand benchmark survey
• Areas of innovation
   • Risk based inspections
   • Changes to the visual inspection programme
• Areas of good practice
   • Compliance with standards/expectations
   • Good level of inventory data
• Area for improvement
   • Understanding of bridge performance and strategic outcomes
   • Performance data collected, but not generally stored
   • Data management
   • Reliance on visual inspections
   • Knowledge and use of other forms of data collection
The underlying framework
Data
Collection     Core Asset Management                Advanced Asset Management
Level
               Basic functionality of asset
               management achieved including        Core data may be insufficient for
Core
               valuations and prioritisation of     advanced asset management
               annual budget

               Core asset management may be         Used for network level analysis,
Intermediate   insufficient for as long term        forecasting condition/risk and
               planning cannot be undertaken        investment level scenario analysis

               Core asset management may be         Used for further analyses/ at a
               insufficient as long-term planning   detailed level, such as diagnostics.
Advanced
               and detailed analysis cannot be      Used in the development of more
               undertaken                           accurate intervention measures/costs
Outcome: criticality and risk diagram
 40.0


 35.0         Risk Rating

 30.0


 25.0
                     Core         Intermediate                            Advanced
 20.0                                                                                              AHB, 3.0, 20.6

                                                                 GB, 2.0, 16.6                     WRB, 3.0, 17.2
 15.0                                                                             MH, 2.0, 15.6


 10.0                                                                             SC, 2.0, 10.6
                             TSSR, 1.0, 8.8                                                            NM, 3.0, 8.2
                                                SBNS, 1.0, 7.4
                             LCNS, 1.0, 5.9
  5.0                                           MSLN, 1.0, 4.8
                                                                                             Criticality Rating
  0.0
        0.0                 0.5   Data collection tools available to bridge asset2.0
                                             1.0               1.5                managers       2.5              3.0

                                                 Risk – and criticality-diagram
Bridge data detailed in guideline




                                               Governance/Policy Directives: Government Strategic
                                                                  Objectives
             Recommended data for collection
Collection methods detailed in guideline




          Data collection tools available to bridge asset managers
Strategy application: example




         a) Auckland Harbour Bridge b) Newmarket Viaduct c)
           Small culvert on SH1 d) Small rural timber bridge
Strategy application: example
                                 Culvert           Timber Bridge                AHB        Newmarket
Performance criteria
                            Risk       Cons.      Risk       Cons.      Risk     Cons.    Risk    Cons.

Structural safety            10.0                    7.5                  27.0             11.3
                                           2                      1                   3             3
Hydraulic/geotech. safety    10.0                    5.0                  22.5             3.8
Serviceability                5.0          1         5.0          1       12.0        2    7.5      2
Functionality                15.0          2         5.0          1       18.0        2    7.5      2
Aggregate: risk (RMS) /
                             10.6          2         5.7          1       20.6        3    8.0      3
criticality (max cons.)

Data collection regime       Intermediate                  Core             Advanced        Advanced

Asset management level         Advanced                    Core             Advanced        Advanced

                          a) Auckland Harbour Bridge b) Newmarket Viaduct c)
                            Small culvert on SH1 d) Small rural timber bridge
Conclusion
• Asset managers have new challenges going forwards
• Have to adopt new technology
• Have to start to understand their asset in greater detail
• They have to do this if the bridges are to last 100 years and
  economically sustainable outcome is to be achieved
Questions?
More Information?
See NZTA website for the data
collection and monitoring strategy
Simon.bush@opus.co.nz

Weitere ähnliche Inhalte

Andere mochten auch

Role of science communication for grass root level capacity building in eco-h...
Role of science communication for grass root level capacity building in eco-h...Role of science communication for grass root level capacity building in eco-h...
Role of science communication for grass root level capacity building in eco-h...Pradip Sengupta
 
A Study on Development of Live Load Model for Passenger Vehicles-only Bridges
A Study on Development of Live Load Model for Passenger Vehicles-only Bridges A Study on Development of Live Load Model for Passenger Vehicles-only Bridges
A Study on Development of Live Load Model for Passenger Vehicles-only Bridges Hyeok Jin Choi
 
The Impact of Data Science on Finance
The Impact of Data Science on FinanceThe Impact of Data Science on Finance
The Impact of Data Science on FinanceRoger Fried
 
INDUSTRIAL TRAINING OF FLYOVER CONSTRUCTION
INDUSTRIAL TRAINING OF FLYOVER CONSTRUCTIONINDUSTRIAL TRAINING OF FLYOVER CONSTRUCTION
INDUSTRIAL TRAINING OF FLYOVER CONSTRUCTIONBhavek Sharma
 
Alex Preda (UCL), Finance as a boundary science. What can social scientists b...
Alex Preda (UCL), Finance as a boundary science. What can social scientists b...Alex Preda (UCL), Finance as a boundary science. What can social scientists b...
Alex Preda (UCL), Finance as a boundary science. What can social scientists b...Logic & Knowledge
 
CONSTRUCTION; A406 FLYOVER
CONSTRUCTION; A406 FLYOVERCONSTRUCTION; A406 FLYOVER
CONSTRUCTION; A406 FLYOVERSyed Rizvi
 
Non destructive testing of railway bridges
Non destructive testing of railway bridgesNon destructive testing of railway bridges
Non destructive testing of railway bridgesHarsh Singh
 
Route 2020 Metro Dubai Construction Details
Route 2020 Metro Dubai   Construction DetailsRoute 2020 Metro Dubai   Construction Details
Route 2020 Metro Dubai Construction DetailsDavid H Moloney
 
Data Science Application in Business Portfolio & Risk Management
Data Science Application in Business Portfolio & Risk ManagementData Science Application in Business Portfolio & Risk Management
Data Science Application in Business Portfolio & Risk ManagementData Science Thailand
 
Sabarmati Riverfront development project
Sabarmati Riverfront development projectSabarmati Riverfront development project
Sabarmati Riverfront development projectNoopur Raval
 
1. classification of urban roads 28 jun
1. classification of urban roads 28 jun1. classification of urban roads 28 jun
1. classification of urban roads 28 junPrathamesh Kulkarni
 
Data Science: Driving Smarter Finance and Workforce Decsions for the Enterprise
Data Science: Driving Smarter Finance and Workforce Decsions for the EnterpriseData Science: Driving Smarter Finance and Workforce Decsions for the Enterprise
Data Science: Driving Smarter Finance and Workforce Decsions for the EnterpriseDataWorks Summit
 
Strategic Asset Management: Knowing Where to Spend
Strategic Asset Management: Knowing Where to SpendStrategic Asset Management: Knowing Where to Spend
Strategic Asset Management: Knowing Where to SpendOHM Advisors
 

Andere mochten auch (19)

Role of science communication for grass root level capacity building in eco-h...
Role of science communication for grass root level capacity building in eco-h...Role of science communication for grass root level capacity building in eco-h...
Role of science communication for grass root level capacity building in eco-h...
 
A Study on Development of Live Load Model for Passenger Vehicles-only Bridges
A Study on Development of Live Load Model for Passenger Vehicles-only Bridges A Study on Development of Live Load Model for Passenger Vehicles-only Bridges
A Study on Development of Live Load Model for Passenger Vehicles-only Bridges
 
The Impact of Data Science on Finance
The Impact of Data Science on FinanceThe Impact of Data Science on Finance
The Impact of Data Science on Finance
 
INDUSTRIAL TRAINING OF FLYOVER CONSTRUCTION
INDUSTRIAL TRAINING OF FLYOVER CONSTRUCTIONINDUSTRIAL TRAINING OF FLYOVER CONSTRUCTION
INDUSTRIAL TRAINING OF FLYOVER CONSTRUCTION
 
Alex Preda (UCL), Finance as a boundary science. What can social scientists b...
Alex Preda (UCL), Finance as a boundary science. What can social scientists b...Alex Preda (UCL), Finance as a boundary science. What can social scientists b...
Alex Preda (UCL), Finance as a boundary science. What can social scientists b...
 
RiverFirst Vision (Final 2012)
RiverFirst Vision (Final 2012)RiverFirst Vision (Final 2012)
RiverFirst Vision (Final 2012)
 
CONSTRUCTION; A406 FLYOVER
CONSTRUCTION; A406 FLYOVERCONSTRUCTION; A406 FLYOVER
CONSTRUCTION; A406 FLYOVER
 
Non destructive testing of railway bridges
Non destructive testing of railway bridgesNon destructive testing of railway bridges
Non destructive testing of railway bridges
 
Route 2020 Metro Dubai Construction Details
Route 2020 Metro Dubai   Construction DetailsRoute 2020 Metro Dubai   Construction Details
Route 2020 Metro Dubai Construction Details
 
flyover and bridge problems and its solutions
flyover and bridge problems and its solutionsflyover and bridge problems and its solutions
flyover and bridge problems and its solutions
 
Ahmedabad srfdcl
Ahmedabad srfdclAhmedabad srfdcl
Ahmedabad srfdcl
 
Data Science Application in Business Portfolio & Risk Management
Data Science Application in Business Portfolio & Risk ManagementData Science Application in Business Portfolio & Risk Management
Data Science Application in Business Portfolio & Risk Management
 
Sabarmati Riverfront development project
Sabarmati Riverfront development projectSabarmati Riverfront development project
Sabarmati Riverfront development project
 
Flyover bridge
Flyover bridgeFlyover bridge
Flyover bridge
 
1. classification of urban roads 28 jun
1. classification of urban roads 28 jun1. classification of urban roads 28 jun
1. classification of urban roads 28 jun
 
Data Science: Driving Smarter Finance and Workforce Decsions for the Enterprise
Data Science: Driving Smarter Finance and Workforce Decsions for the EnterpriseData Science: Driving Smarter Finance and Workforce Decsions for the Enterprise
Data Science: Driving Smarter Finance and Workforce Decsions for the Enterprise
 
Strategic Asset Management: Knowing Where to Spend
Strategic Asset Management: Knowing Where to SpendStrategic Asset Management: Knowing Where to Spend
Strategic Asset Management: Knowing Where to Spend
 
Deeplearning in finance
Deeplearning in financeDeeplearning in finance
Deeplearning in finance
 
Slideshare ppt
Slideshare pptSlideshare ppt
Slideshare ppt
 

Ähnlich wie RIMS Update - Bridge Data Guidelines for Asset Management of Road Bridges

1 Click Factory Mbs Customer Solution (Besim) Upgrade Assessment
1 Click Factory   Mbs Customer Solution (Besim) Upgrade Assessment1 Click Factory   Mbs Customer Solution (Besim) Upgrade Assessment
1 Click Factory Mbs Customer Solution (Besim) Upgrade Assessmentguest29feccc6
 
Developing PostgreSQL Performance, Simon Riggs
Developing PostgreSQL Performance, Simon RiggsDeveloping PostgreSQL Performance, Simon Riggs
Developing PostgreSQL Performance, Simon RiggsFuenteovejuna
 
Tile-based Streaming of 8K Omnidirectional Video: Subjective and Objective Qo...
Tile-based Streaming of 8K Omnidirectional Video: Subjective and Objective Qo...Tile-based Streaming of 8K Omnidirectional Video: Subjective and Objective Qo...
Tile-based Streaming of 8K Omnidirectional Video: Subjective and Objective Qo...Alpen-Adria-Universität
 
IRJET-A Blind Watermarking Algorithm
IRJET-A Blind Watermarking AlgorithmIRJET-A Blind Watermarking Algorithm
IRJET-A Blind Watermarking AlgorithmLalith Kumar
 
A Blind Watermarking Algorithm
A Blind Watermarking AlgorithmA Blind Watermarking Algorithm
A Blind Watermarking AlgorithmIRJET Journal
 
IRJET-A Blind Watermarking Algorithm
IRJET-A Blind Watermarking AlgorithmIRJET-A Blind Watermarking Algorithm
IRJET-A Blind Watermarking AlgorithmIRJET Journal
 
Cost Analysis In IT - HES08
Cost Analysis In IT - HES08Cost Analysis In IT - HES08
Cost Analysis In IT - HES08Thomas Danford
 
MineDB Mineral Resource Evaluation White Paper
MineDB Mineral Resource Evaluation White PaperMineDB Mineral Resource Evaluation White Paper
MineDB Mineral Resource Evaluation White PaperDerek Diamond
 
IRJET- Securing the Reliable Connectivity among Wireless Body Area Networks w...
IRJET- Securing the Reliable Connectivity among Wireless Body Area Networks w...IRJET- Securing the Reliable Connectivity among Wireless Body Area Networks w...
IRJET- Securing the Reliable Connectivity among Wireless Body Area Networks w...IRJET Journal
 
pune muncipal corporation project report
pune muncipal corporation project reportpune muncipal corporation project report
pune muncipal corporation project reportyochoudhary
 
Edge optimized architecture for fabric defect detection in real-time
Edge optimized architecture for fabric defect detection in real-timeEdge optimized architecture for fabric defect detection in real-time
Edge optimized architecture for fabric defect detection in real-timeShuquan Huang
 
Ultra-High-Definition Quality of Experience with MPEG-DASH
Ultra-High-Definition Quality of Experience with MPEG-DASHUltra-High-Definition Quality of Experience with MPEG-DASH
Ultra-High-Definition Quality of Experience with MPEG-DASHBitmovin Inc
 
Cost Analysis in IT - Educause10
Cost Analysis in IT - Educause10Cost Analysis in IT - Educause10
Cost Analysis in IT - Educause10Thomas Danford
 
Review on Data Traffic in Real Time for MANETS
Review on Data Traffic in Real Time for MANETSReview on Data Traffic in Real Time for MANETS
Review on Data Traffic in Real Time for MANETSIRJET Journal
 
Using Data Management & 3D Data Visualization for More Complete CSMs and to S...
Using Data Management & 3D Data Visualization for More Complete CSMs and to S...Using Data Management & 3D Data Visualization for More Complete CSMs and to S...
Using Data Management & 3D Data Visualization for More Complete CSMs and to S...Joshua Orris
 
Using Data Management and 3-Dimensional Data Visualization to Generate More C...
Using Data Management and 3-Dimensional Data Visualization to Generate More C...Using Data Management and 3-Dimensional Data Visualization to Generate More C...
Using Data Management and 3-Dimensional Data Visualization to Generate More C...Antea Group
 
IRJET - A Research on Eloquent Salvation and Productive Outsourcing of Massiv...
IRJET - A Research on Eloquent Salvation and Productive Outsourcing of Massiv...IRJET - A Research on Eloquent Salvation and Productive Outsourcing of Massiv...
IRJET - A Research on Eloquent Salvation and Productive Outsourcing of Massiv...IRJET Journal
 
DICE @ Innomatch 2015, 3rd Regional Innovation Fair, Arad, Romania
DICE @ Innomatch 2015, 3rd Regional Innovation Fair, Arad, RomaniaDICE @ Innomatch 2015, 3rd Regional Innovation Fair, Arad, Romania
DICE @ Innomatch 2015, 3rd Regional Innovation Fair, Arad, RomaniaInstitute e-Austria Timisoara
 
Improvement in Error Resilience in BIST using hamming code
Improvement in Error Resilience in BIST using hamming codeImprovement in Error Resilience in BIST using hamming code
Improvement in Error Resilience in BIST using hamming codeIJMTST Journal
 

Ähnlich wie RIMS Update - Bridge Data Guidelines for Asset Management of Road Bridges (20)

1 Click Factory Mbs Customer Solution (Besim) Upgrade Assessment
1 Click Factory   Mbs Customer Solution (Besim) Upgrade Assessment1 Click Factory   Mbs Customer Solution (Besim) Upgrade Assessment
1 Click Factory Mbs Customer Solution (Besim) Upgrade Assessment
 
Developing PostgreSQL Performance, Simon Riggs
Developing PostgreSQL Performance, Simon RiggsDeveloping PostgreSQL Performance, Simon Riggs
Developing PostgreSQL Performance, Simon Riggs
 
Tile-based Streaming of 8K Omnidirectional Video: Subjective and Objective Qo...
Tile-based Streaming of 8K Omnidirectional Video: Subjective and Objective Qo...Tile-based Streaming of 8K Omnidirectional Video: Subjective and Objective Qo...
Tile-based Streaming of 8K Omnidirectional Video: Subjective and Objective Qo...
 
IRJET-A Blind Watermarking Algorithm
IRJET-A Blind Watermarking AlgorithmIRJET-A Blind Watermarking Algorithm
IRJET-A Blind Watermarking Algorithm
 
A Blind Watermarking Algorithm
A Blind Watermarking AlgorithmA Blind Watermarking Algorithm
A Blind Watermarking Algorithm
 
IRJET-A Blind Watermarking Algorithm
IRJET-A Blind Watermarking AlgorithmIRJET-A Blind Watermarking Algorithm
IRJET-A Blind Watermarking Algorithm
 
Cost Analysis In IT - HES08
Cost Analysis In IT - HES08Cost Analysis In IT - HES08
Cost Analysis In IT - HES08
 
MineDB Mineral Resource Evaluation White Paper
MineDB Mineral Resource Evaluation White PaperMineDB Mineral Resource Evaluation White Paper
MineDB Mineral Resource Evaluation White Paper
 
IRJET- Securing the Reliable Connectivity among Wireless Body Area Networks w...
IRJET- Securing the Reliable Connectivity among Wireless Body Area Networks w...IRJET- Securing the Reliable Connectivity among Wireless Body Area Networks w...
IRJET- Securing the Reliable Connectivity among Wireless Body Area Networks w...
 
pune muncipal corporation project report
pune muncipal corporation project reportpune muncipal corporation project report
pune muncipal corporation project report
 
Edge optimized architecture for fabric defect detection in real-time
Edge optimized architecture for fabric defect detection in real-timeEdge optimized architecture for fabric defect detection in real-time
Edge optimized architecture for fabric defect detection in real-time
 
Ultra-High-Definition Quality of Experience with MPEG-DASH
Ultra-High-Definition Quality of Experience with MPEG-DASHUltra-High-Definition Quality of Experience with MPEG-DASH
Ultra-High-Definition Quality of Experience with MPEG-DASH
 
Cost Analysis in IT - Educause10
Cost Analysis in IT - Educause10Cost Analysis in IT - Educause10
Cost Analysis in IT - Educause10
 
Review on Data Traffic in Real Time for MANETS
Review on Data Traffic in Real Time for MANETSReview on Data Traffic in Real Time for MANETS
Review on Data Traffic in Real Time for MANETS
 
Using Data Management & 3D Data Visualization for More Complete CSMs and to S...
Using Data Management & 3D Data Visualization for More Complete CSMs and to S...Using Data Management & 3D Data Visualization for More Complete CSMs and to S...
Using Data Management & 3D Data Visualization for More Complete CSMs and to S...
 
Using Data Management and 3-Dimensional Data Visualization to Generate More C...
Using Data Management and 3-Dimensional Data Visualization to Generate More C...Using Data Management and 3-Dimensional Data Visualization to Generate More C...
Using Data Management and 3-Dimensional Data Visualization to Generate More C...
 
IRJET - A Research on Eloquent Salvation and Productive Outsourcing of Massiv...
IRJET - A Research on Eloquent Salvation and Productive Outsourcing of Massiv...IRJET - A Research on Eloquent Salvation and Productive Outsourcing of Massiv...
IRJET - A Research on Eloquent Salvation and Productive Outsourcing of Massiv...
 
61607619
6160761961607619
61607619
 
DICE @ Innomatch 2015, 3rd Regional Innovation Fair, Arad, Romania
DICE @ Innomatch 2015, 3rd Regional Innovation Fair, Arad, RomaniaDICE @ Innomatch 2015, 3rd Regional Innovation Fair, Arad, Romania
DICE @ Innomatch 2015, 3rd Regional Innovation Fair, Arad, Romania
 
Improvement in Error Resilience in BIST using hamming code
Improvement in Error Resilience in BIST using hamming codeImprovement in Error Resilience in BIST using hamming code
Improvement in Error Resilience in BIST using hamming code
 

Mehr von Simon Gough

Using Data to Improve Customer Service
Using Data to Improve Customer ServiceUsing Data to Improve Customer Service
Using Data to Improve Customer ServiceSimon Gough
 
TSA Research Project Update
TSA Research Project UpdateTSA Research Project Update
TSA Research Project UpdateSimon Gough
 
ROMDAS Elite Survey Vehicle with Laser Crack Measurement System
ROMDAS Elite Survey Vehicle with Laser Crack Measurement SystemROMDAS Elite Survey Vehicle with Laser Crack Measurement System
ROMDAS Elite Survey Vehicle with Laser Crack Measurement SystemSimon Gough
 
Roading Efficiency Group (REG) Update
Roading Efficiency Group (REG) UpdateRoading Efficiency Group (REG) Update
Roading Efficiency Group (REG) UpdateSimon Gough
 
Putting dTIMS Outputs In Front of Asset Managers
Putting dTIMS Outputs In Front of Asset ManagersPutting dTIMS Outputs In Front of Asset Managers
Putting dTIMS Outputs In Front of Asset ManagersSimon Gough
 
PaveState - Understanding the Structural State of Pavements and their Future ...
PaveState - Understanding the Structural State of Pavements and their Future ...PaveState - Understanding the Structural State of Pavements and their Future ...
PaveState - Understanding the Structural State of Pavements and their Future ...Simon Gough
 
NZTA Asset Management Audits Update
NZTA Asset Management Audits UpdateNZTA Asset Management Audits Update
NZTA Asset Management Audits UpdateSimon Gough
 
Ingenium IPWEA Proposal
Ingenium IPWEA ProposalIngenium IPWEA Proposal
Ingenium IPWEA ProposalSimon Gough
 
Infrastructure Decision Support (IDS) Update
Infrastructure Decision Support (IDS) UpdateInfrastructure Decision Support (IDS) Update
Infrastructure Decision Support (IDS) UpdateSimon Gough
 
Extracting Wealth From Works Management Data
Extracting Wealth From Works Management DataExtracting Wealth From Works Management Data
Extracting Wealth From Works Management DataSimon Gough
 
Economic Network Plan Prioritising Investment
Economic Network Plan Prioritising InvestmentEconomic Network Plan Prioritising Investment
Economic Network Plan Prioritising InvestmentSimon Gough
 
Auckland Transport Database Operations Manual
Auckland Transport Database Operations ManualAuckland Transport Database Operations Manual
Auckland Transport Database Operations ManualSimon Gough
 
Database Health Index
Database Health IndexDatabase Health Index
Database Health IndexSimon Gough
 
Closing the Loop - Information Management Tools for Auckland Motorways
Closing the Loop - Information Management Tools for Auckland MotorwaysClosing the Loop - Information Management Tools for Auckland Motorways
Closing the Loop - Information Management Tools for Auckland MotorwaysSimon Gough
 
Business Process Improvement
Business Process ImprovementBusiness Process Improvement
Business Process ImprovementSimon Gough
 
Aspec Data Standards
Aspec Data StandardsAspec Data Standards
Aspec Data StandardsSimon Gough
 
Using Job Management Systems for Resurfacing Contracts
Using Job Management Systems for Resurfacing ContractsUsing Job Management Systems for Resurfacing Contracts
Using Job Management Systems for Resurfacing ContractsSimon Gough
 
RIMS Update - Best Practice: Traffic Count Estimation
RIMS Update - Best Practice: Traffic Count EstimationRIMS Update - Best Practice: Traffic Count Estimation
RIMS Update - Best Practice: Traffic Count EstimationSimon Gough
 
RIMS Update - Guideline for Pavement Strength Testing
RIMS Update - Guideline for Pavement Strength TestingRIMS Update - Guideline for Pavement Strength Testing
RIMS Update - Guideline for Pavement Strength TestingSimon Gough
 

Mehr von Simon Gough (20)

Using Data to Improve Customer Service
Using Data to Improve Customer ServiceUsing Data to Improve Customer Service
Using Data to Improve Customer Service
 
TSA Research Project Update
TSA Research Project UpdateTSA Research Project Update
TSA Research Project Update
 
ROMDAS Elite Survey Vehicle with Laser Crack Measurement System
ROMDAS Elite Survey Vehicle with Laser Crack Measurement SystemROMDAS Elite Survey Vehicle with Laser Crack Measurement System
ROMDAS Elite Survey Vehicle with Laser Crack Measurement System
 
Roading Efficiency Group (REG) Update
Roading Efficiency Group (REG) UpdateRoading Efficiency Group (REG) Update
Roading Efficiency Group (REG) Update
 
Putting dTIMS Outputs In Front of Asset Managers
Putting dTIMS Outputs In Front of Asset ManagersPutting dTIMS Outputs In Front of Asset Managers
Putting dTIMS Outputs In Front of Asset Managers
 
PaveState - Understanding the Structural State of Pavements and their Future ...
PaveState - Understanding the Structural State of Pavements and their Future ...PaveState - Understanding the Structural State of Pavements and their Future ...
PaveState - Understanding the Structural State of Pavements and their Future ...
 
NZTA Asset Management Audits Update
NZTA Asset Management Audits UpdateNZTA Asset Management Audits Update
NZTA Asset Management Audits Update
 
Ingenium IPWEA Proposal
Ingenium IPWEA ProposalIngenium IPWEA Proposal
Ingenium IPWEA Proposal
 
Infrastructure Decision Support (IDS) Update
Infrastructure Decision Support (IDS) UpdateInfrastructure Decision Support (IDS) Update
Infrastructure Decision Support (IDS) Update
 
Extracting Wealth From Works Management Data
Extracting Wealth From Works Management DataExtracting Wealth From Works Management Data
Extracting Wealth From Works Management Data
 
Economic Network Plan Prioritising Investment
Economic Network Plan Prioritising InvestmentEconomic Network Plan Prioritising Investment
Economic Network Plan Prioritising Investment
 
Auckland Transport Database Operations Manual
Auckland Transport Database Operations ManualAuckland Transport Database Operations Manual
Auckland Transport Database Operations Manual
 
Database Health Index
Database Health IndexDatabase Health Index
Database Health Index
 
Closing the Loop - Information Management Tools for Auckland Motorways
Closing the Loop - Information Management Tools for Auckland MotorwaysClosing the Loop - Information Management Tools for Auckland Motorways
Closing the Loop - Information Management Tools for Auckland Motorways
 
Business Process Improvement
Business Process ImprovementBusiness Process Improvement
Business Process Improvement
 
Aspec Data Standards
Aspec Data StandardsAspec Data Standards
Aspec Data Standards
 
3D StreetCam
3D StreetCam3D StreetCam
3D StreetCam
 
Using Job Management Systems for Resurfacing Contracts
Using Job Management Systems for Resurfacing ContractsUsing Job Management Systems for Resurfacing Contracts
Using Job Management Systems for Resurfacing Contracts
 
RIMS Update - Best Practice: Traffic Count Estimation
RIMS Update - Best Practice: Traffic Count EstimationRIMS Update - Best Practice: Traffic Count Estimation
RIMS Update - Best Practice: Traffic Count Estimation
 
RIMS Update - Guideline for Pavement Strength Testing
RIMS Update - Guideline for Pavement Strength TestingRIMS Update - Guideline for Pavement Strength Testing
RIMS Update - Guideline for Pavement Strength Testing
 

RIMS Update - Bridge Data Guidelines for Asset Management of Road Bridges

  • 1. Bridge Data Guidelines for Asset Management of Road Bridges Simon Bush: Opus Consultants Piotr Omenzetter: University of Auckland Theuns F. P. Henning: University of Auckland Peter McCarten: Opus Consultants
  • 2. Our role as asset managers • How do you prove you are contributing to national strategic outcomes? • How do you prove you are achieving value from money from bridge management funding? • Why? Our role is to ensure the assets we manage provide for the nations needs and therefore support the economy • How? Through the use of an advanced asset management approach
  • 3. It is important to get it right • Close to 18000 bridges nationally (circa 4500 on state highways and 13500 on Local roads). • On average a bridge every 5km nationally and every 2.5km on state Highways. New Zealand therefore functions on its bridges. • Aging local bridge stock
  • 4. New Zealand bridge asset management • NZGAO 2003: Limited evidence of an advanced asset management approach • USGAO 2008: The bridge program does not fully align with GAO’s principles… …in that the program lacks focus, performance measures. For example, the program’s statutory goals are not focused on a clearly identified federal or national interest. • NZGAO 2010: As asset information improves over time, there is a need to ensure the information is cost-effective to collect, and is as complete and up to date as possible, and remains useful.
  • 5. New Zealand benchmark survey • Areas of innovation • Risk based inspections • Changes to the visual inspection programme • Areas of good practice • Compliance with standards/expectations • Good level of inventory data • Area for improvement • Understanding of bridge performance and strategic outcomes • Performance data collected, but not generally stored • Data management • Reliance on visual inspections • Knowledge and use of other forms of data collection
  • 6. The underlying framework Data Collection Core Asset Management Advanced Asset Management Level Basic functionality of asset management achieved including Core data may be insufficient for Core valuations and prioritisation of advanced asset management annual budget Core asset management may be Used for network level analysis, Intermediate insufficient for as long term forecasting condition/risk and planning cannot be undertaken investment level scenario analysis Core asset management may be Used for further analyses/ at a insufficient as long-term planning detailed level, such as diagnostics. Advanced and detailed analysis cannot be Used in the development of more undertaken accurate intervention measures/costs
  • 7. Outcome: criticality and risk diagram 40.0 35.0 Risk Rating 30.0 25.0 Core Intermediate Advanced 20.0 AHB, 3.0, 20.6 GB, 2.0, 16.6 WRB, 3.0, 17.2 15.0 MH, 2.0, 15.6 10.0 SC, 2.0, 10.6 TSSR, 1.0, 8.8 NM, 3.0, 8.2 SBNS, 1.0, 7.4 LCNS, 1.0, 5.9 5.0 MSLN, 1.0, 4.8 Criticality Rating 0.0 0.0 0.5 Data collection tools available to bridge asset2.0 1.0 1.5 managers 2.5 3.0 Risk – and criticality-diagram
  • 8. Bridge data detailed in guideline Governance/Policy Directives: Government Strategic Objectives Recommended data for collection
  • 9. Collection methods detailed in guideline Data collection tools available to bridge asset managers
  • 10. Strategy application: example a) Auckland Harbour Bridge b) Newmarket Viaduct c) Small culvert on SH1 d) Small rural timber bridge
  • 11. Strategy application: example Culvert Timber Bridge AHB Newmarket Performance criteria Risk Cons. Risk Cons. Risk Cons. Risk Cons. Structural safety 10.0 7.5 27.0 11.3 2 1 3 3 Hydraulic/geotech. safety 10.0 5.0 22.5 3.8 Serviceability 5.0 1 5.0 1 12.0 2 7.5 2 Functionality 15.0 2 5.0 1 18.0 2 7.5 2 Aggregate: risk (RMS) / 10.6 2 5.7 1 20.6 3 8.0 3 criticality (max cons.) Data collection regime Intermediate Core Advanced Advanced Asset management level Advanced Core Advanced Advanced a) Auckland Harbour Bridge b) Newmarket Viaduct c) Small culvert on SH1 d) Small rural timber bridge
  • 12. Conclusion • Asset managers have new challenges going forwards • Have to adopt new technology • Have to start to understand their asset in greater detail • They have to do this if the bridges are to last 100 years and economically sustainable outcome is to be achieved
  • 13. Questions? More Information? See NZTA website for the data collection and monitoring strategy Simon.bush@opus.co.nz