Jamshedpur, Apr 10 (PTI) Scientists underlined the rising need for advanced diagnostic tools, predictive modelling and integrated assessment techniques to ensure the safety, reliability and cost-effective operation of industrial assets, during a two-day national symposium here.
The symposium on ‘Remaining Life Assessment of Engineering Components (RLA-2026)’ was held at the CSIR-National Metallurgical Laboratory (NML), Jamshedpur on Thursday and Friday.
According to a release issued by the CSIR-NML, the deliberations highlighted key technical insights, industry relevance and future strategies for extending asset life.
The technical sessions covered areas such as creep and stress rupture-based life assessment, corrosion management and risk-based inspection, advanced RLA methodologies, and laboratory visits showcasing facilities at the institute.
The statement said participants emphasised that integrating Non-Destructive Evaluation (NDE), microstructural analysis and AI-driven data approaches is essential for accurate life prediction.
Speakers also stressed the need for stronger collaboration among R&D institutions, academia and industry to address emerging engineering challenges.
A Samanta of NTPC briefed participants on Indian Boiler Regulations (IBR) guidelines, noting that RLA investigations are currently conducted every five to six years.
He pointed out that component failures have been reported within months of inspection, underscoring the importance of high-quality RLA reporting. He also suggested increasing inspection frequency, while improving data quality and minimising testing downtime.
S K Nath of the Central Power Research Institute (CPRI) said automation in Non-Destructive Testing (NDT) has significantly reduced data generation time compared to manual methods, but cautioned that speed should not compromise quality.
Mangalore Refinery and Petrochemicals Ltd’s K Sateesh said RLA-based software has improved decision-making speed in refineries.
However, he flagged inconsistencies between current and past RLA reports due to data quality issues, stressing that accurate life extension depends on the integrity of collected data. PTI ANB RBT
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