Major infrastructure projects can cost billions of dollars and take many years to develop. To get transport projects purpose ready for Day 1 operations, the construction phase should include asset familiarisation, data transition, and a maintenance strategy that optimises asset performance towards a sustainable and resilient future.
Getting these elements right will take a project a long way towards success, but the transition from the construction phase into operations can bring things unstuck if there isn’t good knowledge transfer. So that’s where we’ll begin.
Transferring knowledge from construction to operations
When transitioning from commissioning through to Day 1 of operations, there is a change in the resourcing needed to manage assets – and significant risks arise around project knowledge transfer. If project knowledge is lost at this stage, it can lead to unexpected downtime of assets, reduced service levels, lost revenue, reputational impacts and resourcing constraints.
Sometimes these issues can be resolved over time, but there’s also a risk of long-term impacts on the operational business model. Time invested into change management and the handover to operations is wise – and will pay dividends.
Operations staff need to be properly familiarised with assets
New assets commonly come with new technology intended to streamline business operations and increase efficiency. During the construction phase, design teams will seek to optimise their designs with a future focus, but may pay insufficient attention to how existing or previous assets are functioning. As the construction phase transitions through commissioning and towards operations, operations staff will need a structured process across an extended period to absorb knowledge from the design and construction teams to become fully familiar with the assets. Alignment is required across project and organisational governance to ensure suitably qualified teams are properly familiarised to manage the various asset classes.
Familiarisation must be sufficiently robust to consider more than business-as-usual operations. It should include the various scenarios and disruptions that would test an organisation’s operational response, and should check the resilience of operations against both known and predicted future risks and changes, including extreme climatic events. It also requires a focus on both the technical and the behavioural responses that will be needed to handle different operating scenarios.
Transitioning asset data from BIM to a common AIMS
A powerful way in which organisations can build readiness for operations is establishing, as early as possible, a ‘single source of truth’ of asset data within an Asset Information Management System (AIMS). The transition of data from BIM models into the AIMS will enable organisations to monitor asset performance data and optimise asset operations.
BIM models are powerful tools and are increasingly being used to test asset scenarios, but there must be a robust BIM strategy in place to enable smooth and timely sharing of data to the AIMS and any other supporting asset management platforms. Ensuring that data is flowing into enterprise asset management systems well in advance of operations will support the integration of maintenance teams into operations and align asset performance to the business objectives.
Early establishment of a robust maintenance supply chain
During the design and construction phases, integrated lifecycle management will identify products for maintenance well in advance of commissioning and operations. The early transition of this asset data into business operations will inform the organisation’s Asset Maintenance Strategy and subsequent Strategic Asset Management Plan.
Organisations can consider how best to align with organisational objectives through alternative maintenance strategies and funding models, including risk transfer of some assets or components to third-party, consortium or franchisee contracting parties.
By establishing maintenance supply chains early, suppliers can be proactively coordinated for maintenance scheduling, spares inventory and data management. This will provide the opportunity to stress-test the resilience of the maintenance supply chain practices and enable early opportunities to optimise asset performance, apply continuous learning principles and upskill the workforce across the maintenance supply chain.
Moving towards a zero-failure future
Traditional approaches to maintaining transport infrastructure have tended to be preventative and corrective. To move towards zero-failure transport networks, asset managers will need to continue the shift from reactive approaches to more sustainable practices, such as condition-based maintenance and predictive asset management.
Advances in data and analytics are driving intelligent maintenance, but alignment is needed among new monitoring technologies (Internet-of-Things sensors and automated inspection platforms), analytics platforms (machine learning and artificial intelligence), asset management strategies, demand-driven asset wear and deterioration models, and the organisational vision to drive effort and investment. Early definition of systems and data requirements will inform the asset management strategy and associated maintenance schedules.
Embracing the advantages of data and technology can save on maintenance costs and maximise the safe performance and lifespan of the asset. Improved asset reliability and safety means less downtime and increased asset availability, which in turn means fewer impacts on customer journeys and a higher performing system.
Optimising asset performance and reducing environmental impacts
As new transport assets commence operations, technical and operational learnings will accumulate and opportunities will emerge to optimise performance over the life of the asset. When a continuous learning focus comes together with asset maintenance data, it is likely that minor operational changes can be made to reduce the costs of maintenance or operations, and enable a ‘repair, reuse, recycle’ view to managing the asset lifecycle. These activities can also align asset performance with environmental benchmarks and/or specific environmental targets such as reductions of embodied carbon or emissions. Performance can be monitored – and alternative scenarios tested – by bringing asset data together with digital twin modelling.
When asset management objectives and systems are established early, there will be many opportunities for organisations to optimise asset performance to be purpose-ready from Day 1 and throughout the entire asset lifecycle.
In other articles in the Getting transport projects purpose ready series, we explore how to safeguard success through customer-centric design, community and stakeholder engagement, project assurance, and data and analytics, with insights from our human-led, tech-powered community of solvers.
About the author
David Ballantyne is an Integrated Infrastructure Partner based in Sydney. David leads our national asset management practice. He has more than 20 years’ experience in major infrastructure projects and provides strategic advice across all phases of the asset life cycle.
This sponsored editorial is brought to you by PwC. For more information, please visit www.pwc.com.au.
