Inspection data transformed

Inspection data transformed – cleansed, digitised, trendable

The challenge

Managing complex industrial infrastructures is often a delicate balance between leveraging vast volumes of legacy inspection data and integrating a torrent of new inputs from ongoing inspections. Because of these challenges, accurately planning and predicting the need for engineering, inspection, and maintenance activities on large and complex assets is a major, costly headache when not performed effectively.

A lack of confidence in inspection data quality, competing resources, shrinking inspection and maintenance budgets, risk prioritisation, and increasing interest and scrutiny from regulators all contribute to a perfect storm for operators. As a result, business and safety-critical decisions may be made with incomplete, incorrect, or poorly understood asset integrity data, which could mean:

  • An increase in actionable anomalies, unfit-for-purpose locations, loss of primary containment incidents, unacceptable risk profiles
  • Trending integrity data remains the goal but not the reality
  • Inspections are carried out which do not add value, incurring costs and reducing the finite resources available for higher priority scopes

The Imrandd Solution

EXACT was forged in the fire of age-old inspection workflow inefficiencies, devised to deliver a faster, simpler, and more cost-effective way of solving integrity management problems. It cleanses, corrects, and interprets large data sets, then maps and predicts equipment degradation to deliver actionable insights, guaranteed to significantly reduce OPEX and improve asset integrity management and plant reliability.

With EXACT, you have the power to transition from reactive to proactive, be more predictive and to use budgets more effectively; to accurately calculate the risk of degradation rather than act on discovery of a problem.

In summary

  • Cleanses, corrects, normalises and identifies gaps in legacy inspection data
  • Identifies correlations and trends in a cleansed data set
  • Predicts equipment degradation and potential failures
  • Graphically represents inspection data and degradation patterns
  • Identifies critical threats: determining threat levels per system and areas of over-inspection
  • Calculates corrosion degradation rates and remnant life, providing granularity of corrosion rates and remaining life assessments from systems through to test points