Sydney Trains – MIDT – Measurement and Inspection Digital Twin


MIDT applied strategic asset management principles to transform manual labour-intensive maintenance inspection processes that have existed for decades into automated, integrated, and connected digital processes, improving asset insights and decision making, enabling predictive maintenance practices, improved sustainability, and the welfare and safety of employees

Using LIDAR data collection technology to automate measurement and inspection activities for 10 technical maintenance plans removed 40,000 hours per annum of manual inspection activities from the rail-corridor, improved network availability, and increased Asset Master Data integrity, location and condition accuracy enabling asset visualisation, integration, and the foundations for Predictive Maintance practices 

Figure 1 – LiDAR automates asset data collection and provides visualisation that enables deep insights into asset condition

Glossary of Terms

MIDTMeasurement & Inspection Digital Twin: Name of the project initiative within Sydney Trains
LiDARLight Detection And Ranging: is a surveying method which illuminates pulsed laser light, measures the reflected pulses and creates digital 3D representation of the target area
ALOAsset Lifecycle Optimisation: Method used by Sydney Trains to assess the asset lifecycle cost and risk profile, and make decisions on asset investment to meet expected performance
EDTEnterprise Digital Twin: A virtual representation of the physical asset created from point cloud data captured by the LiDAR device
MTPVSydney Trains Mechanised Track Patrol Vehicle: which traverses the whole network over a 2-week period as part of a regular maintenance regime.
TMPTechnical Maintenance Plan that provides the inspection requirements and measurement standards for each inspection type

Project Description

Sydney Trains operates in the rail sector of the Transport for NSW cluster, and maintains over 756,000 rail assets that includes 1,599km of track, 1,536km of overhead wiring, 2,263 electric and diesel fleet cars, and 169 stations.  Sydney Trains has annual maintenance budget of $1.5 billion and an asset portfolio valued at over $46 billion. On average there are 147 million passenger journeys recorded across the metropolitan network annually

Problem Statement

Increased service demand for both passenger and freight traffic has reduced track access windows for maintenance. Sydney Trains has sought to invest in innovative rail technology to improve network performance, asset risk management and sustainability of maintenance practices

MIDT was established to addresses the following asset management challengers:

  • Maintenance staff are required to enter the Railway Corridor to undertake manual measurement and inspection activities for routine maintenance exposing them to risk of working in the vicinity of live train operations
  • Increasing demand in passenger and freight traffic on main lines has reduced both frequency and duration available for network maintenance
  • Manual inspection processes are resource intensive, inefficient, and time-consuming resulting in low quality data capture which can be subjective or incomplete, leading to inconsistent datasets for decision making
  • Low quality asset condition and performance data restricted the ability to optimise maintenance interventions and perform long-term asset planning using predictive maintenance strategies
  • Asset Management Objectives required improved asset data collection and accuracy for ALO and lifecycle cost reduction

Application of Asset Management Principles

In developing MIDT, Sydney Trains ran a Proof of Concept (POC) utilising LiDAR technology. The POC demonstrated that LiDAR could replace 95% of manual human measurements in the rail corridor for platform clearance inspection, however while the solution met the primary objective to remove a small number of track workers from the danger zone, it was not financially sustainable as:

  • LiDAR was expensive to own and maintain, and had high obsolesce
  • Only solved one inspection problem
  • There was a marginal decrease in overall work effort
  • Didn’t integrate with back-office processes
  • Limited vendors had demonstrated experience using LiDAR technology in railway environments that could provide the desired model and data processing

Applying Strategic Asset Management principles for whole of asset lifecycle analysis combined an integrated asset planning model focused on the Rail Corridor rather than individual asset classes enabled:

  • 10 additional inspections identified that could benefit from LiDAR data capture, changing the sustainability of the initiative by dramatically increasing the number of infrastructure worker hours that could be removed from the danger zone, and significantly increasing the efficiency gains for back-office processes
  • A single technology source that would produce high quality assured data collection across multiple asset classes that could service stakeholder requirements, including creation of a “Point Cloud” that would enable visualisation of the Corridor for site survey and possession planning
  • Commercial framework that separated data collection from data processing and establishment of a data processing panel to enable multiple organisations to be engaged based on asset class experience
  • Foundations for predictive maintenance practices though collection of repeatable measurements for asset location and condition data that improves asset interventions, optimisation of asset lifecycle models and possession planning across the network

Figure 2: Multiple Inspection Types can be captured using a single LiDAR run

Figure 3: Utilisation of a Single Data source to service multiple business requirements

Solution Innovation Originality

MIDT leverages LIDAR data collection technology to automate measurement and inspection activities and improve asset visualisation. Data collected enables a virtual representation of the physical network, the environment, and all related asset information to produce a deep understanding of the physical asset condition

LiDAR (Light Detection And Ranging) is a surveying method which illuminates pulsed laser light, measures the reflected pulses and creates digital 3D representation of the target area. MIDT engaged a partner vendor to mount their LiDAR system As-A-Service on the MTVP which traverses the network over a 2-week period as part of a regular maintenance regime

A geo-referenced 3D spatial data model is acquired for the railway infrastructure without manual track-walk or track possession. The Point Cloud data is processed to provide both measurement and visual data outputs that meet the TMP inspection requirements previously captured and recorded via manual processes

Figure 4: Automation of Manual Asset Inspection & Measurement for Platform Clearances using LiDAR mounted on MTPV2

Figure 5: Multiple manual forms are replaced by data points that are captured and represented in a virtual model

Figure 6 – LiDAR enables insights into assets and their relationship to other assets on the Network

Figure 7: Visualisation of the Rail Corridor for Improved Planning & Decision Making

Program & Project Management

MIDT followed Sydney Trains engineering assurance model.  Each stage commenced with a baseline workshop to align all stakeholders on scope, schedule, budget, and assurance deliverables. The integrated team provided the following:

  • New engineering standards for site survey and location of survey targets across the network
  • Optimisation of Maintenance Plans and latitudes aligned to bi-annual LiDAR runs
  • Test plans for system testing stages for each LiDAR run and pre and post data processing results against standards
  • Safety assurance including assessment of human factors
  • Changes to end-to-end processes and procedures across Sydney Trains
  • Configuration management and commission.

The stages included:

  • Proof of Concept (POC) -LiDAR was trailed and proved to be a technology that can remove manual measurement
  • Technical Pilot10 additional inspection types across electrical, civil, track, corridor & surveying disciplines were incorporated into the technical pilot across 20Kms of corridor to demonstrate it could pass requirements
  • Commissioning – Management of change across multiple divisions including solution architecture, safety, technical validation, procurement, human factors, data management, establishment, and operations management
  • Handover – Implementation into BAU Operations, including the establishment of annual funding, new positions, and capabilities to manage digital processes and new partnerships with vendors
  • Continuous improvement review is undertaken to optimise the technology and maintenance interventions

Benefits to the organisation and community

MIDT has delivered the following benefits:

  • Improved track worker safety through the removal of 40,000 hours per annum of manual labour activities from the rail corridor
  • Efficiency savings of an additional 10,000 hours on upstream and downstream routine maintenance activities that is no longer required
  • Higher network availability for passenger and freight vehicles through removal of inspection types that required track possession
  • Optimised maintenance asset intervention planning through improved asset condition data
  • Standardised methodology for measurement activities across all territories which has improved accuracy of asset location information
  • Digital tools and technologies that align with TfNSW and Sydney Trains strategies for scalability and sustainability in asset investment outcomes
  • Transformation of static, subjective and disconnected manual asset inspection processes into automated, integrated, and connected data driven digital process

Team Contribution

MIDT brought together engineering and operational stakeholders from across multiple asset disciples to standardise on the use of a single technology and integrated business processes. Traditionally engineering and maintenance disciples for electrical, civil, track, corridor & surveying were siloed, with investigation of Rail technology being discipline specific. This was a significant change is business thinking requiring high levels of facilitation and collaboration across disciple to agree on technology, assurance requirements, data validation, and process change  

Multiple stakeholders were engaged from across Sydney Trains and TfNSW to deliver MIDT.  Key stakeholders included: 

  • Network Maintenance – Initial review of technology options and recommendation of LiDAR as the most appropriate technology to meet the Engineering Standards for Platform Clearances. Operational testing of LiDAR technology on the MTPV for POC and management of third-part deliverables
  • Asset Management – Applied strategic asset management thinking and intelligent maintenance principles for improved asset insights into performance and sustainable maintenance practices to improve the initiative outcomes and secure long-term funding. Multiple stakeholders were engaged though workshops to identify opportunities and leverage innovation in process and technology to achieve further benefits that aligned with the asset management objectives
  • Major Works Project Delivery – Project management and project methodology to show incremental value along the way to executives, and to identify further improvement opportunities as the project progressed with each stage concluded
  • Engineering & Systems Integrity – Technical advice and systems assurance change documentation. Standardisation of measurement activities across all territories, the realignment of 10 TMP’s and their latitudes to twice yearly LiDAR runs, the development of new standards for automated inspections, and standards for survey markers across the network to improve data collection accuracy
  • Safety Assurance – Safety Change Plan in alignment with the Safety Management of Change Procedure to provide visibility of the safety argument indicating how the safety objectives for MIDT were to be met and describe the safety management activities required to provide evidence that the safety arguments have been met
  • Organisational Change – Operational Change plan and leadership change support, employee consultation and embedding to support transition of Infrastructure Workers in the Maintenance Division from manual to automated asset inspection processes. A phased implementation and parallel run approach was adopted to ensure operational efficiency. Change champions supported behaviour change, ways of working, and training in new processes and technology
  • Operations – Provided Train paths and operational flexibility to enable the scheduling of the pilot, implementation, and possession planning to install survey markers across the network
  • Transport Asset Management Branch – Development of new standards and input on Asset Technology strategy

General Comments

MIDT overcame multiple difficulties which lead to approximately 100 key findings being identified in both the POC and Technical Pilot that improved the success of the solution being delivered into operations.

Key findings and resulting changes are listed below:

  • LiDAR is a tool for collecting data to report on conformance/non-conformance and will not provide root cause of any underlying issues which manual inspection provides the opportunity to assess. Higher volumes of data are collected requiring the development of analysis and degradation models for each asset class to interpret and predict root cause
  • For some inspection types, the LiDAR technology was unable to determine the location and length of the fixed asset along the corridor. For example, the start and end point of a tunnel. Implementing LiDAR-visible survey targets on selected track sections enhanced the location accuracy
  • GPS location accuracy using existing Track Location System technology was not sufficiently accurate to support automated capture of some inspection types. Using only control targets and LiDAR IMU Trajectory while excluding GPS dramatically increased the accuracy of the mobile laser scanning point cloud to +/- 20mm
  • The terrain of the network and different weather conditions impact the quality of the data collected and the ability to assure data collection results. The introduction of a double head scanner results in a higher density point cloud which has increased accuracy for some inspection types across different terrain and weather events
  • When automating asset inspections, using third parties there is a lag between data collection and data processing. Tight controls are required to ensure all activities are delivered sequentially to remain within Technical Maintenance Plan (TMP) latitudes.  A dedicated team was established within network maintenance to manage third-party deliverables to KPI’s and ensure the timely delivery of sequential processes in compliance with inspection timeframes and within latitude
  • TMP Inspection intervals for all inspections required new processes, development of standards for automation of inspection using digital technology, allowances for down time during wet weather, data processing and analysis and any other disruptions to the MTPV schedule

MIDT contribution to Rail has been significant: 

  • Safety – removal of human intervention on Rail corridor assets resulting in a safer workplace for maintenance staff and increased asset availability and reliability
  • Asset Management – provides insights into asset performance that has improved asset planning and decision making through increased data integrity for Master Data of assets, their locations, and condition
  • Possession Management – removal of the need for on-site surveys for possession planning using the Digital Twin to support virtual surveys
  • Sustainability – creation of sustainable maintenance practices and operating costs by removing inefficient manual processes, standardising measurement activities and optimising maintenance interventions
  • Customer – improved network availability to support increased frequency of service through reduced need for shutdowns of the Network for manual inspections
  • Employee Satisfaction – delivers on corporate goals for the use of technology and digital tools to enhance employee productivity, safety, and efficiency and support intelligent working
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