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Our Asset Management Journey

Professor Sujeeva Setunge

Deputy Dean, Research and Innovation

School of Engineering

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RMIT Journey in Infrastructure Asset

Management

• Central Asset Management System (CAMS) for Buildings

• CAMS-Drainage

• Disaster resilience of bridges, culverts and floodways

• CAMS-Bridges

• Automated Tree inventory using airborne LiDar and Aerial imagery

• Intelligent Asset Management in Community Partnership – A smart

cities project

• Future cities CRC – New!!

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CAMS for Buildings

CAMS Mobile

• Australian Research council grant in partnership with – MAV

– City of Glen Eira

– City of Kingston

– City of greater Dandenong

– Mornington Peninsula shire

– City of Monash

– City of Brimbank

• State government grant to develop the cloud hosted platform

• City of Melbourne investment to develop practical features such as backlog,

scenario analysis, risk profile

• RMIT University property services and City of Melbourne – CAMS Mobile

inspection app

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CAMS for Buildings - Features

1. Database management

2. Data exploration

3. Deterioration prediction

4. Budget calculation

5. Backlog estimation

6. Risk management

RMIT University©2015

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CAMS clients

Property Services

Australia | Vietnam

Current Capability

Data Driven Models for

700 components

Cost and other input

Scenarios Analysis

Risk-cost Relationship

CAMS TECHNOLOGY - Buildings

Research In Progress

Visual Inspection

Inspection progress

RFIDs for asset

tracking

Previous Data

Plans / Photos / Defects

/ Asbestos etc.

Physical degradation

modelling – improve

accuracy

Cost for defects,

intermediate conditions,

works order, optimised

repair

Level of service for

Decision Making

Energy Retrofitting

iOT integration

Compliance Auditing

BIM Integration

Utilisation/Level of

service/User

Feedback

Automated mapping

CAMS

Life-Cycle

Modelling

CAMS

Mobile

Cloud-based Database

Multi-objective Decision Making

Smart Cities $871,000 Kingston,

Brimbank, Port Phillip+Hendry

Group

Next stage

Cross assets

Augmented

Reality

Emergency

manageme

nt

RMIT - $260,000 Hendry Group + City

of Melbourne

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Awards – During research stage

Engineers Australia, Asset Management Council Postgraduate Research Awards

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CAMS Awards

Received by end users after implementation

2017 Australian Financial review, Facilities Innovation Award 40 year Life Cycle

2017 Facilities Management Australia Excellence Award – RMIT Property Services

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CAMS for Drainage

• Funded by a consortium of partners – MAV

– City of Whittlesea

– City of greater Dandenong

– City of Port Phillip

– City of Darebin

– City of Monash

– City of Brimbank

– Melbourne Water

• Australian research council grant with Melbourne Water and City of Greater

Dandenong

• RMIT University seed funding for developing the cloud hosted platform

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Asset management framework

Step 1 • IDENTIFY CRITICAL PIPES

• Based on consequence of unexpected failure

Step 2 • CONDUCT CCTV INSPECTION

• Random sampling of (at least) 600 pipes

Step 3 • CONDUCT RISK ANALYSIS

• Probability of failure, Remaining life, Influential factors

Step 4 • MANAGE RISK

• Inspection time, Annual Maintenance Budget

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CAMS DRAINAGE demonstration

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MARKOV STRUCTURAL DETERIORATION

FINDING

•AVERAGE OF AGE (sample) = 60 YEARS

•Left figure shows predictive deterioration of network of concrete pipes which is calibrated using samples of CCTV data (summarized in right figure)

• If average age of pipe network is taken as 60 years as of 2010, then from left figure, there are 60% of pipe network is in condition 1, 15% in condition 2, 6% in condition 3, 3% in condition 4 and 16% in condition 5.

•Percentage of pipe network in each condition states can be predicted in the future years.

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GEC – BUDGET DEMO

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CAMS for Drainage - Moving forward

Local Government Amendment (Performance Reporting and Accountability) Act

2014 requires a Council to report against prescribed performance indicators in the report of operations and performance statement in the Council's annual report. Identify performance indicators (e.g. number of flooding, blockages and collapse,

percentage of pipes in poor conditions 4 and 5) How to improve performance indicators over time

Inspection and repair manual for stormwater pipes Identify and optimize inspection schedule for new pipes and inspected pipes Repair manual for each type of defects such as cracking, corrosion and

displacement and open joints. How to risk-cost optimize repair actions

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Disaster resilience of bridges, culverts and

floodways

• Funded by CRC for Bush fire and Natural Hazards – MAV

– Lockyer Valley Regional Council

– Queensland Transport and Main Roads

– VicRoads

– Road and Maritime Services NSW

• Vulnerability Modelling of Road structures under flood, bush fire and

earthquakes

• GIS map of road structures with vulnerability rating

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Bridges under flood loading

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0.134m/s

spread rate

HRR/m(kW/m) Intensity

0-350 350-3500 3500-35000 35000 and above

Low Medium High Extreme

Bush Fire resilience

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Multiple Earthquake impact

• Damage due to multiple earthquake impacts

• Reliability based damage accumulation framework for bridges due

to multiple earthquake impacts

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WAY FORWARD – GIS INTEGRATION

• Austroads bridge design code introduced 1 in 2000 year flood design for bridges • Constructed bridges pre-1992 were mostly designed for 1 in 100 year ARI (Bennett et al.

2009)

1% AEP Flood

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Level 2 Inspection Data of Bridge Components (12-16) (e.g. Deck 8C; Girder 2C)

Significant Contributing Factors (6-14) (e.g. Built-year, Exposure Class, Traffic Volume)

Data collection from RAS Data filtering and processing

Markov’s Deterioration Model

Predicted Conditions/Probability Vector (e.g. Conditions of the components in next 5, 10, 20 years)

Input

Model

Output

CAMS for Bridges – RMIT, VicRoads and ARC

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Compare deterioration curves 8C

Metro South East Metro North West

No Factors, i.e. All components are the same.

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Output

Age C3 %Remain C4 %Remain

Yr+1 5.82 4.23

Yr+2 5.82 3.17

Yr+3 5.82 2.12

Yr+4 5.82 1.06

Yr+5 5.82 0.00

Remaining Conditions and Maintenance Budgeting

Age Budget Surplus Budget Need 3,4 Budget Supply

Yr+1 0 165 30

Yr+2 0 145 30

Yr+3 0 125 30

Yr+4 0 105 30

Yr+5 0 85 30

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• Royal Melbourne Institute Of Technology

• Brimbank City Council

• Nilumbik Shire Council

• Warrnambool City Council

• Whittlesea City Council

• Shire Of Campaspe

• Hobsons Bay City Council

• BAYSIDE City Council

• Melbourne Water

Project Partners

Automated council tree inventory using airborne LiDAR and aerial imagery Develop a new technology and software tool for cost-effective

inventory of council tree infrastructure using airborne LiDAR.

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LiDAR Remote Sensing of Urban Environment LiDAR System

3D view of LiDAR point cloud

Tree information retrieved from LiDAR data

Tree top

Tree

location

Height

Canopy

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Automatically captured trees from LiDAR shown as grey

clusters overlaid on Google image. Each grey cluster is a

tree. The outline of the cluster is the edge of tree crown

Data from

Warrnambool

Council. Over

thousand

trees captured

in less than 30

minutes.

Results are

99% correct.

Include all

council trees

and trees in

residential

garden

Similar quality

results

achieved from

Brimbank

Council data

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Sustainable planting of trees in suburban

environments on Shrinkable Clays Evaluate the influence of selected tree species on rates of soil water

uptake in a suburban environment;

Provide local government councils a rational suburban tree planting

management plan;

Provide civil engineering profession with new guidelines and rational

design models to reduce the risk of accommodating trees in an urban

environment, leading to an increased acceptance of trees within

communities living on problem clay sites.

City of Knox

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Intelligent Asset Management in

Community Partnership

• Smart cities project – MAV

– City of Kingston

– City of Brimbank

– City of Port Phillip

– Hendry Group

• Three smart precincts are developed integrating internet of things and

sensor technologies to optimise – Energy

– Environment

– Utilisation

– Just in time maintenance

Smart cities project – iOT for interactive city management

Three smart precincts in progress

Opportunities for collaboration

• Feel free to contact us to join any of the current initiatives. We will find a way to engage you and share the benefit

• CAMS for buildings, bridges and drainage

• Engage us to explore any new challenges

• Workshop on Vulnerable road structures 6 July 10- 1 pm at RMIT

• Engage our students for work experience/internships

Future Cities CRC

• RMIT is forming a consortium for a new bid in preparation for government funding

• MAV is forming a local council consortium for focus areas of

– Liveability, sustainability, healthy communities

– Consistent approach for managing community assets by local, state and federal governments

– Community led decision making

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