rims forum 2013 database health index - mike tapper beca
DESCRIPTION
In conjunction with the Asset Management team at Auckland Transport (AT), Beca developed a database health index to assess confidence levels within the AT RAMM database. The index enables AT to identify strengths and weaknesses in their database, prioritise improvements and track corresponding database changes. It gives AT a comprehensive understanding of their asset database health in an simple one page visual based report. This results in improved value for money in setting database improvement programmes and improved decision making and analysis through better understanding of available data.TRANSCRIPT
Measuring and Monitoring Confidence in your RAMM Database
Viren Sharma 20 March 2013Mike Tapper
2013 Road Asset and Information Forum, Wellington
AT | Measuring and Monitoring Confidence in your RAMM Data base Page 3
ObjectivePurpose is to identify a repeatable mechanism for reporting the health of the data in the RAMM Database.
The index will be used to establish current condition and a benchmark for monitoring improvement
AT | Measuring and Monitoring Confidence in your RAMM Data base Page 7
RAMM INDEX
Active Assets Collected DataNon-
Carriageway Assets
• Surfacings• Pavements• Footpaths• Treatment
Length
• Visual Rating• High Speed
Data• Footpath
Rating • Maintenance
Costs • Traffic
• Bridges• Drainage• SWC• Signs• Streetlights
Index FrameworkRAMM INDEX
Pavement and Footpath Assets
Collected Data
• Surfacings• Pavements• Footpaths• Treatment
Length
• Visual Rating• Automated
Data• Footpath
Rating • Maintenance
Costs • Traffic
• Bridges• Drainage• SWC• Signs• Streetlights
AT | Measuring and Monitoring Confidence in your RAMM Data base Page 10
Confidence GradingGrade Description
1 Accurate / measured data
2 Minor inaccuracies
3 50% estimated
4 Significant data estimated
5 All data estimated
Grading RegimeThis format is used for both the ranking and the target setting.
AT | Measuring and Monitoring Confidence in your RAMM Data base Page 11
Dashboard Results – Pavement and FootpathsCategory Measures Result Measure Target Category Target Group Target
% of Network surfaced in RAMM over previous 4 – 15 months 7.6% Grade 2 Grade 1
% Surfaces 50% older than expected age 0.0% Grade 1 Grade 2
Illogical records (SAC with chipseal, unsealed with surface dates, duplicates, low & high widths, traffic volumes v hierarchy/pavement use, overlaps, no surfacings etc)
0.2% Grade 1 Grade 1
% of Network in RAMM 4 – 27 months previous 3.4% Grade 2 Grade 2
Benchmark length v typical urban length/km 93.3% Grade 1 Grade 2
Illogical records incl. % with no material or surface date, overlaps, duplicates etc 1.7% Grade 1 Grade 1
Proportion with layer information on roads with ADT > 500 vpd 99.7% Grade 1 Grade 3
New Layer length v 1st coat length in 4 – 15 months 0.0% Grade 4 Grade 2
Proportion of very short (< 20m) or very long (> 500m urban and 1km rural) TLs 10.8% Grade 2 Grade 1
Proportion of TLs with < 80% coverage of major surfacing 3.1% Grade 1 Grade 1
% updated in last 5 years on roads with ADT >500vpd 100.0% Grade 1 Grade 2
79 78
Pavement and Footpath Inventory
Pavement Layer
Treatment Length
Surfacing
Footpaths
8391
6550
8284
8292
AT | Measuring and Monitoring Confidence in your RAMM Data base Page 12
Dashboard Results – Collected DataCategory Measures Result Measure Target Category Target Group Target
Percentage compliant with AT policy (i.e. Percentage > 500 vpd not rated in last 1.5 years plus percentage < 500 vpd not rated in last 2.5 years)
100.0% Grade 1 Grade 1
% compliant with AT policy (i.e inspection length < 95% or rating section length > 300m unless rural local roads, service lanes etc where inspection length < 20%)
99.5% Grade 1 Grade 1
% network meeting AT policy for roughness (Main roads surveyed in last 1.5 years and local roads in last 2.5 years)
98.8% Grade 1 Grade 1
% network meeting AT policy for rutting (Main roads surveyed in last 1.5 years and local roads in last 2.5 years)
96.4% Grade 1 Grade 1
% network meeting AT policy for texture (Main roads surveyed in last 1.5 years and local roads in last 2.5 years)
96.4% Grade 1 Grade 1
Items per km for PA and SU fault codes in previous 4 – 15 months 16.4% Grade 5 Grade 2
Spread of location in previous 4 - 15 months 0.0% Grade 1 Grade 2
Counts in last 4 - 15 months (vs AT programme) 0% Grade 5 Grade 1
% having ADT Estimates 96.5% Grade 1 Grade 1
% estimates < 3 years old 4.2% Grade 5 Grade 1
% loading estimate + count (i.e. not default) 18.0% Grade 5 Grade 2
Footpath Rating
Percentage compliant with AT policy (i.e. Percentage rated in last 3.5 years) 95.3% Grade 1 Grade 1 95 90
8058
9097
90100
8776
Collected Data
Maintenance Costs
Traffic Count
Carriageway Rating
High Speed Data
8530
AT | Measuring and Monitoring Confidence in your RAMM Data base Page 13
Dashboard Results – Non-Carriageway Assets
Category Measures Result Measure Target Category Target Group Target
Difference in No. of bridges in database v Valuation quantity 10.0% Grade 1 Grade 1
Bridges with as-built drawings attached 40.9% Grade 3 Grade 2
Bridges with Inspection reports within the last 2.5 yerars 97.7% Grade 1 Grade 1
Culverts per km v benchmark (Rural) 102.6% Grade 1 Grade 2
Catchpits per km v benchmark (Urban) 86.2% Grade 2 Grade 2
SWC per urban km v benchmark 92.3% Grade 1 Grade 2
Renewal Activity (Construction Date in previous 4 – 27 months) 2.3% Grade 3 Grade 2
Signs per km v benchmark (Urban) 51.1% Grade 3 Grade 2
Renewal Activity (“replaced” date in previous 4 – 15 months) 0.2% Grade 4 Grade 2
Streetlights per km v benchmark (Urban) 64.8% Grade 3 Grade 2
Maintenance Activity (“replaced” date in previous 4 – 15 months) 1.2% Grade 4 Grade 2
Duplicates or near duplicates plus poles with no light or bracket 0.1% Grade 1 Grade 1
8093
8376
8261
7827
7667 8065
Bridges
Streetlights
Drainage
Surface Water Channels
Signs
Non-Carriageway Asset Inventory
AT | Measuring and Monitoring Confidence in your RAMM Data base Page 14
Implementation The index is run annually with a full report Index run quarterly with dashboard only Modular results give focus on key areas Allows a targeted improvement plan Tracks effectiveness on funding spent
AT | Measuring and Monitoring Confidence in your RAMM Data base Page 15
AT | Measuring and Monitoring Confidence in your RAMM Data base Page
Questions/Discussion