By Anoop Naik, Chief Technical Officer, Pipeline Infrastructure Limited
A pipeline is rarely just one asset ageing at one speed. Buried steel, above-ground mechanical equipment and the electronic systems that run them all wear out on different clocks: coatings and welds fail through corrosion, fatigue and pressure cycling, while the control systems, software and cybersecurity layers operating the network often lose vendor support long before the pipe itself needs attention. For an industry built on 30-, 40- or even 50-year assets, managing that whole life cycle – and getting ahead of obsolescence before it turns into a crisis – is now as central to reliability as the quality of the steel and welds themselves. The task is not simply to keep an asset in service, but to keep it safe, reliable, secure, supportable and fit for purpose for as long as it operates.
Why life cycle thinking matters
For operators, this discipline protects the safety and integrity of assets carrying hazardous fluids through populated areas. For financiers, it underwrites the bankability of projects built on multi-decade cash flows. For regulators, it underpins continued operation and decommissioning decisions. A pipeline system is layered, involving buried steel, above-ground mechanical equipment, electrical systems and IT/OT systems, each ageing on its own clock. Industrial hardware is typically designed for 25-30 years of service, yet the electronics and automation inside it commonly carry commercial life cycles of only 5-15 years, so several obsolescence cycles must be managed within a single asset’s lifetime.
Coordinating these mismatched clocks, without over- or under-investing in any single layer, is the central challenge. Treating concept, engineering, construction, operation, maintenance, enhancement and retirement as one connected strategy, rather than isolated activities, lets an organisation judge condition and criticality, optimise maintenance spend, assess residual life, and manage obsolescence and time replacement before reliability suffers – basing capital decisions on risk, performance and condition rather than age alone.
A framework for the whole life cycle
Leading operators integrate these stages into one continuous philosophy – developing new capacity, operating and monitoring the network, maintaining assets safely to the end of life, and replacing or renewing them on condition and cost comparison – turning life cycle management into a standing input to investment planning rather than a maintenance afterthought.
Life extension calls are made through a structured risk assessment across three options – deferring major maintenance, upgrading, or replacing – with one firm boundary: no deviation where statutory or regulatory requirements apply. Operating history, failure trends and supportability data, not asset age, drive the final extend-upgrade-replace decision.
In practice: Pipeline Infrastructure Limited (PIL) has formalised this into its asset life cycle philosophy, applied consistently across a geographically dispersed network. Original equipment manufacturer (OEM) life cycle data is compiled for the major rotating fleet, including gas turbines, compressors and gas-engine generators, with risk assessed across mechanical, electrical, instrumentation and automation systems, staggering replacement against future cash flow and turning capital spikes into a predictable, budgeted programme.
Focusing where it matters most
Not every asset carries the same level of risk – a small share of the asset base typically accounts for the majority of supply-interrupting failures. Concentrating monitoring and renewal on this core, rather than spreading effort evenly, directs scarce resources where they cut the most risk.
In practice: PIL applies an 80:20 approach, focusing its lean technical teams on the asset base that is most critical, giving consistent, high-attention review at scale without resourcing every site as if it carried equal risk.
Automation assets: A layered life cycle
A control system is best understood as an ecosystem, not a single device – its continued operation depends on firmware, operating systems, licences, communication protocols, vendor support, spares and cybersecurity controls, not on hardware condition alone. A programmable logic controller or a remote terminal unit can stay serviceable for 10 years or more, but the workstations, servers and Windows-based operating systems around it are commercial off-the-shelf technology with a much shorter cycle, typically five years of standard support. The result is a layered life cycle in which different parts of the same automation solution go obsolete at different times, so operators need to manage the platform as one ecosystem rather than as individual devices – hardware condition alone can never confirm an automation asset is still fit for service.
Left unmanaged, these risks compound – an unpatched system guarding an uninspectable asset is a bigger risk than either alone. IEC 62402 formalises the fix: a shift from reactive replacement to planned obsolescence management, built on a register of at-risk items, defined risk criteria, and a quantified view of likelihood and impact, with a purely reactive stance reserved only for genuinely low-risk items.
In practice: PIL runs an obsolescence programme with a measurable target – extending at-risk equipment life by at least two years for half the affected base – giving a clear, honest picture across control, instrumentation and electrical systems, tracked by functional heads rather than surfacing only on failure.
Key challenges
- Specialist expertise: Condition assessments need OEM or qualified third-party depth. A flawed read means a flawed decision, so internal competency to challenge external findings is essential.
- Information asymmetry: Discontinuation notices and phase-out schedules are rarely published openly, making structured OEM collaboration essential to any proactive approach.
- Data continuity: Incomplete inventories, outdated diagrams and missing configuration backups make it hard to set a reliable baseline or judge priorities.
- Capital allocation: Extension, refurbishment and replacement compete for the same budget, and upgrades are often deferred while equipment still runs, despite growing risk.
- Vendor dependency: OEMs can discontinue controllers, software or spares even on well-performing systems, and proprietary configurations, licences and tools can lock operators into one supplier’s road map.
- Safety vs. cost: Deferring replacement to save money must be weighed against integrity risk.
- Workforce transition: Legacy knowledge needs deliberate transfer, not incidental handover.
A data-driven, digital response
- These challenges can be addressed through a data-driven approach, including:
- Digital asset replicas: A live digital record of design, inspection and maintenance history.
- Predictive maintenance: Sensors and AI shift maintenance from fixed schedules to condition-based maintenance.
- Remote inspection: Specialist expertise applied at distant sites without travel.
- Open architectures: Modular, interoperable platforms that let components, including security controls, be replaced individually.
- Dedicated data function: One function owning asset data as the foundation for every other tool.
In practice: PIL uses predictive insight and augmented reality inspection, enabling head office specialists to conduct fault-finding remotely, backed by a dedicated central technical services function that owns asset data, thereby diagnosing the network from a single hub and eliminating specialist travel while building a history that makes predictive decisions rather than reactive.
Strengthening the approach
It is key to start with one comprehensive asset register covering hardware, firmware, software, licences, network dependencies, spares, vendor support status, cybersecurity exposure and criticality, then classify assets by consequence, condition, obsolescence risk and replacement lead time. Best practice includes the following:
- Forecast obsolescence in capital plans: Build expected end-of-life dates into long-term budgets.
- Standardise on open architectures: Specify interoperable systems in new projects and standardise platforms where practical to avoid lock-in and reduce spare part diversity.
- Manage knowledge structurally: Document legacy expertise before it retires with the workforce.
- Map dependencies and phase modernisation: Link controllers, servers, workstations and instruments, then upgrade in planned tranches using phased migration, parallel operation and simulation to cut risk.
- Hold minimum spares and road maps: Keep strategic spares, test equipment and short-, medium- and long-term technology road map ready, informed by manufacturer end-of-support notices.
- Assess residual life and test recovery routinely: Use inspection data, not age, to judge remaining life, and rehearse recovery and restoration through periodic drills.
- Prioritise by risk, proportionately: Weigh safety, production, environmental, cybersecurity and recovery consequences, choosing added controls, selective replacement, refresh, migration or full platform replacement, rather than blanket replacement.
In practice: PIL grounds replacement planning in measured evidence – using in-line inspection data and population surveys to calculate residual pipeline life directly, so capital and inspection effort go to the sections that genuinely need it, not spread uniformly across the route.
A collaborative approach
- Leadership: Fund life cycle management as a strategic programme, not a line item.
- Vendors: Agree on support timelines, migration paths and cybersecurity update commitments well ahead of end-of-life.
- Regulators: Keep dialogue open on life extension methods and evolving standards.
- Cross-functional planning: Align engineering, finance and operations on every major decision.
- Workforce: Training professionals across legacy and emerging technology to ensure knowledge transfer.
Conclusion
Pipelines are built for generations, but that longevity is earned, not automatic. Mechanical and static assets fail through measurable physical wear, and automation assets become obsolete through lost support, unavailable spares, incompatible software, cybersecurity gaps or fading expertise, often well before the pipe itself needs attention. Managing both requires one life cycle approach spanning engineering, operations, maintenance, cybersecurity, procurement and finance.
Operators that plan for an asset’s end from day one, focus on the critical few assets that matter most, treat automation as one ecosystem rather than isolated devices, and let data – not assumption – guide extend-upgrade-replace decisions will keep their networks safe, secure and fit for purpose for decades to come. Built to last, these assets must also be managed to adapt.
The path forward is proactive, not reactive. Condition monitoring, predictive maintenance, obsolescence tracking and technology/cybersecurity road maps should flag emerging risks before they become failure, backed by strategic spares, secure system architecture, tested backups, vendor-support agreements and workforce capability development.
