The measurement readings recorded during calibration that reflect the instrument's condition as it was being used, before any adjustments or corrections are made.
As-found data captures the true state of an instrument at the time of calibration, documenting how it was actually performing during the period since its last calibration. This data is recorded before any adjustments, cleaning, or corrections are made. It is the most important data in the calibration process because it reveals whether the instrument was providing accurate measurements while in service.
Recording as-found data is critical for assessing the reliability of measurements made since the last calibration. If the as-found data shows the instrument was within tolerance, there is confidence that measurements made during the calibration interval were valid. If the instrument is found out of tolerance (OOT), an investigation is triggered to determine the impact on products, processes, or test results that depended on the instrument's measurements.
For calibration management, as-found data serves multiple purposes. It provides the basis for OOT notifications and impact assessments. It is the primary input for calibration interval optimization — trends in as-found data across multiple calibration cycles reveal instrument stability and drift patterns. Statistical analysis of as-found data across a fleet of similar instruments can identify systematic issues (bad lot, design defect, environmental problem). Quality systems like ISO 9001, ISO 17025, and AS9100 all require as-found data to be recorded and retained as part of calibration records.
In an aerospace calibration lab, a Fluke 8846A precision multimeter arrives for annual calibration. The technician first measures its response to a 10.000V reference standard and records 9.987V as the as-found reading before any adjustments. This -0.013V drift reveals the instrument's degradation during service, critical for evaluating measurement uncertainty in flight control system testing. In a medical device manufacturer's lab, a Keysight 34465A used for pacemaker current measurements shows as-found readings of 1.0023 mA when testing against a 1.0000 mA standard. This +0.23 mA drift exceeds the ±0.1 mA specification, indicating potential patient safety risks from inaccurate current delivery measurements. Getting this wrong creates serious problems: if technicians adjust instruments before recording as-found data, manufacturers lose traceability to actual measurement errors that occurred during production. During FDA audits, missing as-found data on critical medical device test equipment can trigger 483 observations, as regulators cannot assess whether out-of-tolerance conditions affected product quality. Similarly, AS9100 auditors flag calibration records lacking proper as-found documentation, questioning whether aerospace components were tested with compromised instruments.
ISO/IEC 17025:2017 requires as-found data in section 6.4.6, mandating records of equipment condition before calibration activities. AS9100D references this through section 7.1.5.2, requiring objective evidence of measurement equipment status affecting aerospace product conformity. ISO 13485:2016 section 7.6 demands calibration records including pre-adjustment measurements for medical device traceability. ANSI/NCSL Z540.3-2006 section 9.1.3 explicitly requires as-found measurements to assess instrument drift and establish measurement uncertainty. IATF 16949 references ISO/IEC 17025 requirements through section 7.1.5.2.1 for automotive measurement systems. During audits, assessors verify as-found data completeness, looking for systematic recording procedures, proper documentation of out-of-tolerance findings, and evidence that measurement uncertainty calculations incorporate actual instrument drift patterns. ILAC-P10:2013 policy emphasizes as-found data as essential evidence for measurement traceability chains. Auditors specifically examine whether laboratories demonstrate understanding of how as-found conditions impact measurement results and customer risk assessment.
CalibrationOS captures as-found data through the Calibration Workflow module's initial measurement step, automatically prompting technicians to record pre-adjustment readings before any corrections. The system timestamps and locks as-found entries to prevent post-calibration modifications, ensuring data integrity. During certificate generation, the Reporting Engine automatically includes as-found vs. as-left comparisons, calculating drift rates and uncertainty contributions. The Asset Management module tracks as-found trends over time, generating drift analysis reports that help predict calibration intervals and identify degrading instruments. For audit preparation, the Compliance Dashboard displays as-found data completeness metrics across all calibrations, flagging any missing pre-adjustment measurements. The system's Exception Handling feature automatically triggers out-of-tolerance workflows when as-found readings exceed specified limits, ensuring proper investigation and customer notification procedures. Integration with the Quality Management module links as-found data to measurement uncertainty calculations, automatically updating uncertainty budgets based on actual instrument drift patterns observed during calibration cycles.
As-found data is the set of measurement readings recorded at the start of calibration, before any adjustments are made. It documents the instrument's actual condition during the period it was in service.
As-found data determines whether the instrument was performing within tolerance while in use. If it was out of tolerance, all measurements made since the last calibration may need to be reviewed for impact on quality.
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