From asset register to next inspection date: the integrity data chain
Pressure equipment integrity software stores a chain: asset register, corrosion circuits, condition monitoring locations, dated thickness readings, computed short- and long-term corrosion rates, remaining life against t-min, and a next inspection date set by API 510, 570 or 653 arithmetic. Risk-based inspection consumes the same data. An inspection management system schedules the work; integrity software decides when the work is due.
Integrity software and inspection management software get confused because both hold inspection data. They answer different questions. An inspection management system answers who is doing what job, with which certified technician, against which purchase order, and where the report is. Integrity software answers whether this vessel can stay in service and until when. The first is a work system; the second is an engineering calculation with an audit trail. A mid-size owner-user runs both, and the expensive failure is when they do not share a database: thickness readings taken by the field crew live in the job system, and the integrity engineer re-keys them into a spreadsheet three weeks later. Every number below — corrosion rate, remaining life, next due date — is derived. If it is typed, it is wrong the moment the next reading arrives.
Source: Google Search Console, atlantisndt.com, 90-day window to 2026-09-01: 'pressure equipment integrity software' 9 impressions at position 62; 'pipeline audit preparation services' 114 impressions at position 35. Remaining-life and interval arithmetic from API 510 (pressure vessel inspection), API 570 (piping inspection) and API 653 (aboveground storage tanks); risk model inputs from API 580 and API 581.
| Step | Data the system must hold | What it computes | Failure mode |
|---|---|---|---|
| Asset register | Equipment ID, code of construction, design pressure and temperature, MAWP, material, joint efficiency, allowable stress, corrosion allowance, service, install date | The required thickness baseline for every component | MAWP and t-min stored inside a scanned datasheet instead of as fields |
| Circuitisation | Circuit ID, boundaries, material specification, service fluid, operating envelope, expected damage mechanisms, criticality class | Groups CMLs so one governing rate applies to like-for-like metal | Circuits drawn by line number rather than by damage mechanism, mixing unlike corrosion |
| CML register | CML ID, drawing reference, physical location, component type, nominal thickness, t-min, number of readings per CML, access method | Anchors every future reading to the same steel | CML identity not preserved through a revamp, so the history splits in two |
| Thickness history | Date, reading set, instrument and its calibration record, technician and certification, surface temperature, method | A dated series per CML | Readings kept in per-turnaround spreadsheets and never merged into one series |
| Corrosion rate | Two or more dated readings on the same CML | Long-term rate from initial to current thickness; short-term rate from previous to current; the governing rate is the one that gives the more conservative result | Negative or physically impossible rates from a mis-keyed reading, with no outlier flag |
| Remaining life | Current thickness, required thickness, governing corrosion rate | Remaining life = (t actual − t required) ÷ corrosion rate | t required taken as nominal minus corrosion allowance instead of the code thickness calculation |
| Next inspection date | Remaining life, equipment class, prior inspection date | API 510: internal or on-stream at the lesser of half the remaining life or 10 years, external visual at 5 years. API 570: thickness measurement at the lesser of half the remaining life or the class maximum. API 653: external visual at 5 years, internal not exceeding 20 years | Dates set by calendar habit and budget cycle rather than by the arithmetic |
| RBI inputs | Damage mechanism and damage factor inputs, generic failure frequency, inventory, fluid properties, detection and isolation systems, management systems factor | Probability of failure combined with consequence of failure to give risk and a plan date per API 580/581 | RBI run in a separate model that never reads the live thickness table |
The asset register carries the code, not just the tag
The register is where most implementations are quietly undermined. A tag number, a description and a P&ID reference are not enough. Integrity arithmetic needs design pressure and temperature, MAWP, material specification, allowable stress, joint efficiency, nominal thickness by component, corrosion allowance, code of construction and edition, service fluid, and installation date. Every one of those is an input to a required-thickness calculation.
When those values live inside a scanned U-1A form or a manufacturer's data report, the calculation cannot run and the engineer retypes them into a spreadsheet each cycle. Structured as fields, the required thickness for shell, heads and nozzles is computed once and recomputed whenever a repair, re-rate or replacement changes an input.
The register also has to carry state. Equipment is repaired, re-rated, temporarily patched, blinded and returned to service. A record that shows only the current configuration cannot explain a thickness series that steps upward the year a section was replaced. Configuration changes need dates, so that the corrosion rate calculation knows to restart the series at the new component.
Circuits are the analytical unit for piping
Piping is not inspected line by line; it is inspected by corrosion circuit. A circuit collects piping sharing material, service, operating temperature and pressure, and expected damage mechanisms, so that a rate measured at one location can be treated as representative. Getting circuit boundaries right is engineering judgement, and it is the highest-leverage decision in a piping programme.
The common error is to draw circuits along line numbers because line numbers already exist in the drawing system. Line numbers reflect process design, not degradation. A single line can cross a dead leg, an injection point, a temperature transition and a metallurgy change — four different corrosion behaviours pooled into one governing rate that represents none of them.
Injection points, mix points and dead legs need identification as their own entities within the circuit, because API 570 treats injection points with tighter intervals and specific CML placement upstream and downstream. Software that cannot flag an injection point separately will schedule it on the general circuit interval, which is the wrong answer in the location where accelerated corrosion is most likely.
CMLs: identity, placement, and readings per location
A condition monitoring location is a fixed, repeatable point on a component. Its record needs an identifier that never changes, a drawing reference and a physical description precise enough for a different technician to find the same spot next cycle, the component type, nominal thickness, calculated t-min, and the pattern of readings taken there — typically four quadrants on a pipe, more on an elbow's extrados.
Identity persistence is the whole game. If a revamp renumbers CMLs, or a new contractor invents a labelling scheme, one twelve-year history becomes two six-year histories. Both then produce long-term rates near zero, remaining life is overstated, and the software confidently pushes the next inspection out. Migration into new software is where this damage is most often done, so map old identifiers to new ones and keep both.
Placement should follow the damage mechanism expected in the circuit. Erosion-corrosion concentrates at elbows and downstream of restrictions; under-deposit attack sits at low points; CUI sits at penetrations and supports under insulation. CMLs placed for access convenience rather than mechanism produce a clean data set that describes the wrong metal. This is one of the things a programme audit and gap assessment looks at first.
Thickness history is data, not a stack of reports
Each reading needs a date, the value or value set, the instrument used with its calibration status on that date, the technician with their certification, the surface temperature where a correction applies, and the method. That metadata is what allows an anomalous reading to be judged rather than accepted. A step change of 0.080 inches between cycles is either real wall loss or a different instrument, a different couplant, paint left on, or a probe placed two inches off the mark.
Capture belongs at the CML, in the field, with prior readings visible on the screen. A technician who can see that the last reading here was 0.312 inches recognises 0.212 as suspect and re-measures on the spot. A technician recording numbers blind, into paper transcribed a week later, cannot. That is the argument for offline field data capture in an integrity programme rather than in reporting alone.
The system needs outlier handling that flags rather than deletes. Readings that produce negative corrosion rates, physically impossible rates, or thicknesses above nominal must be quarantined for engineering review with the disposition recorded. Silently dropping them hides measurement problems; silently accepting them corrupts every rate downstream.
Rate, remaining life, and the due-date arithmetic
Two corrosion rates are computed per CML. The long-term rate runs from the initial thickness to the current reading across the full elapsed period. The short-term rate runs from the previous reading to the current one. The governing rate is whichever gives the more conservative outcome, which is how a recent process change that started attacking a circuit gets caught instead of being diluted by a decade of benign data.
Remaining life is the current thickness minus the required thickness, divided by the governing rate. The trap sits in the required thickness. Nominal minus corrosion allowance is a procurement convention, not a code calculation. The required thickness comes from the pressure design calculation for that component under the code of construction, and using the procurement figure produces remaining lives that are wrong in whichever direction the design margins happen to fall.
The due date then follows the code. API 510 sets the internal or on-stream interval at the lesser of half the remaining life or 10 years, with external visual at 5 years. API 570 sets thickness measurement at the lesser of half the remaining life or the maximum for the piping class, with injection points on tighter intervals. API 653 sets external visual at 5 years and internal inspection not exceeding 20 years, subject to the corrosion-rate calculation for the bottom. Software should compute the date and show the inputs; an engineer approves it.
RBI consumes the same database, and adds two dimensions
Risk-based inspection under API 580 and 581 does not replace thickness monitoring; it re-weights it. Probability of failure is built from a generic failure frequency modified by damage factors for the mechanisms credibly active on that equipment, by the effectiveness of inspections actually performed, and by a management systems factor reflecting the quality of the mechanical integrity programme itself. All of that draws on inspection history already in the database.
Consequence of failure is the dimension the inspection department usually does not own: fluid properties, inventory available for release, detection and isolation systems, personnel exposure, area and financial consequence. It has to be sourced from process engineering and kept current when the unit's service changes, because a circuit that switched to a different feedstock last year has a different consequence than the model holds.
The failure pattern is structural. RBI is run as a project, in a separate model, by a consultant, and then diverges from reality as new readings arrive in the inspection system. When both live on the same database, an inspection completed updates the damage factor and the inspection effectiveness input, and the risk ranking moves. The value of RBI is in its currency, not its original sophistication.
Where integrity software ends and inspection management begins
Draw the boundary at the decision. Integrity software decides what condition the asset is in and when it is next due. Inspection management executes: it builds the work list from those due dates, schedules the crew, checks that the technician's certification and the instrument's calibration are valid, captures the readings, produces the report and invoices the work. Both need the same thickness readings, from opposite directions.
The integration that matters is narrow and specific: due dates flow out to become work orders, and readings plus completed inspection records flow back in. Everything else can stay separate. Firms that attempt one monolithic system usually end up with an integrity model too rigid to reflect engineering judgement, or a work system too loose to produce auditable records. Two systems and one clean interface beats one system that does both badly.
On the execution side, Atlantis is Odoo-based, deployable cloud or on-premise, with offline field capture, certification and calibration tracking, and configurable report templates — the layer that gets readings out of the field and into the integrity model the same day. Where an existing package of inspection data is disputed or an audit finding lands on record quality, report validation and audit preparation address the documentary side. Affordable. Accessible. Fully customizable. Demo or quote on request via contact.
What is circuitisation and why does software need it?
A corrosion circuit groups piping that shares material, service fluid, operating conditions and expected damage mechanisms, so a corrosion rate measured at one CML legitimately represents the rest. It is an engineering judgement, not a drafting convenience. Circuits drawn along line numbers mix dissimilar metallurgy and service, and a governing rate calculated across them understates the risk on the worst component.
How is corrosion rate calculated from thickness readings?
Two rates are computed per CML. The long-term rate uses the initial thickness and the current reading over the elapsed period. The short-term rate uses the previous reading and the current one. The governing rate is the one producing the shorter remaining life, so accelerating corrosion is caught rather than averaged away by years of benign history.
What sets the next inspection date under API 510?
For pressure vessels, the internal or on-stream inspection interval is the lesser of one-half the remaining life or 10 years, and external visual inspection is at 5 years. Where remaining life is short, the code permits the full remaining life up to a stated cap. Confirm the current edition and any jurisdictional amendment applying to your equipment.
How do integrity software and inspection management software differ?
Integrity software owns the engineering decision: what condition is this asset in, and when must it next be inspected. Inspection management owns execution: scheduling crews, tracking certifications, capturing data, producing reports, invoicing. They share thickness readings and inspection dates. Kept in separate systems, readings arrive weeks late and the integrity model runs on stale data. See NDT inspection software.
What does RBI need that thickness monitoring alone does not?
Consequence data and damage mechanism modelling. API 581 combines a probability of failure — driven by damage factors, generic failure frequency, inspection effectiveness and a management systems factor — with a consequence of failure derived from fluid, inventory, detection and isolation. Thickness history feeds the probability side only; the consequence side needs process and layout data the inspection department rarely owns.
Why do CML identifiers matter so much?
Because a corrosion rate is only valid when consecutive readings come from the same steel. Renumbering CMLs at a revamp, or letting two contractors label the same location differently, splits one history into two short ones. Both then show a long-term rate of nearly zero, remaining life looks generous, and the thinning that is actually happening becomes invisible in the data.
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