TotalAshChecker

Total Ash

dissolution EAEU herbal impurities microbiology minerals pharmacopoeia specification
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Total Ash Checker — Total ash verification (Ph. Eur. 2.4.16)

ℹ️ The utility verifies total ash content in herbal raw materials.
ℹ️ Does not use machine learning — rule-based logic only.
⚠️ High ash content → contamination with soil, sand, or mineral impurities.

Usage:
TotalAshChecker.exe → demo mode (console output)
TotalAshChecker.exe input.csv output.json → evaluate your data

Input format:
TotalAshPercent,LimitPercent,SubstanceName

Example:
3.8,5.0,Chamomile Flowers
6.2,7.0,Peppermint Leaves
8.5,7.0,Calendula Herb

— WHY IS THIS NEEDED?
Total ash is a key purity indicator for herbal materials:
• Reflects inorganic impurity levels,
• Critical for flowers, leaves, and aerial parts,
• Control per Ph. Eur. 2.4.16 is mandatory for herbal products.
Compliance is critical for registration and GMP release.

input.csv

TotalAshPercent,LimitPercent,SubstanceName
3.8,5.0,Chamomile Flowers
6.2,7.0,Peppermint Leaves
8.5,7.0,Calendula Herb

URS & FS — user requirements and functional specification

This document defines user requirements and functional specification for the quality-control utility. It supports deployment discussion, IQ/OQ preparation and QC workflow integration.

Utility: TotalAshCheckerAPI / object: Total AshCategory: EAEU pharmacopoeia

1. Scope

The Total Ash Checker utility is used for Total Ash. The actual input.csv is the source of truth for the input structure; control criteria are defined by the executable and the domain description.

The utility does not use machine learning; decisions are produced by deterministic rules.

Categories: EAEU pharmacopoeia

Tags: dissolution, EAEU, herbal, impurities, microbiology, minerals, pharmacopoeia, specification

2. Execution modes

TotalAshChecker.exe                            → demo mode (console output)
TotalAshChecker.exe input.csv output.json      → evaluate your data

3. Key controlled areas

  • dissolution / disintegration
  • pH and physicochemical parameters

4. Domain limits and critical parameters

  • ⚠️ High ash content → contamination with soil, sand, or mineral impurities.
Limits stated in the description must be verified against the current approved specification, pharmacopoeial monograph and registration dossier before production use.

5. URS — user requirements

IDRequirementCriticalityAcceptance criterion
URS-001The system shall accept an input.csv file for Total Ash with the exact columns listed in the “Input data contract” section.HighA file with the correct header is processed without manual editing; missing mandatory columns produce FAIL/import error.
URS-002The system shall support execution without arguments in demo mode and execution with input.csv output.json for user data.MediumBoth execution scenarios produce a predictable result or clear diagnostic error.
URS-003The system shall perform rule-based controls for: dissolution / disintegration, pH and physicochemical parameters.HighEach controlled parameter receives a status and message; the result does not depend on hidden Excel formulas or ML.
URS-004The system shall preserve traceability between batch/lot, source values, applied rules and final verdict.HighOutput includes batch identifier, source values, parameter statuses and critical findings.
URS-005The system shall generate machine-readable output.json for LIMS/ELN/MES, batch record and QA/QC review.HighJSON contains overall status, check array, warnings, failures and source-file reference.
URS-006The system shall support use in the client validation package: URS/FS, IQ/OQ preparation, installation and operational scenario checks.HighThe document, test scenarios and reproducible CSV/JSON flow are suitable for audit and internal approval.
URS-007The system shall clearly separate technical data errors from specification nonconformities.MediumSchema/type errors are not mixed with pharmacopoeial deviations and are reported separately.

6. input.csv data contract

The source of truth for the input schema is the actual input.csv header. Column names are technical identifiers and are not translated.

#ColumnTypeUnitDescriptionSampleControl rule
1TotalAshPercentdecimal%Total Ash %3.8mandatory numeric value; rule comparison is performed by the utility
2LimitPercentdecimal%Limit %5.0mandatory numeric value; rule comparison is performed by the utility
3SubstanceNametextas specifiedSubstance NameChamomile Flowersmandatory value; format and acceptability are checked by the utility

CSV example

TotalAshPercent,LimitPercent,SubstanceName
3.8,5.0,Chamomile Flowers

7. FS — functional specification

IDFunctionImplementation description
FS-001CLI entry pointThe executable TotalAshChecker.exe supports demo mode and input.csv output.json processing mode.
FS-002CSV parserThe import module reads CSV, validates header, column presence/order, value count and encoding. Decimal values are expected with a dot separator.
FS-003Field conversionEach column is converted to the expected type: identifier, text, decimal number, date/time or boolean flag.
FS-004Domain rule engineFor Total Ash, explicit rules are applied: range, minimum, maximum, absence of prohibited flag, data completeness or calculation-based check.
FS-005Criticality handlingCritical violations produce FAIL; non-critical deviations and incomplete data produce WARNING; full conformance produces PASS.
FS-006JSON writeroutput.json stores overall status, per-parameter results, source values, warnings, failures and diagnostic messages.
FS-007Integration contractThe CSV → JSON format is stable for invocation from LIMS/ELN/MES, scheduled task or wrapper service.
FS-008Error handlingSchema error, missing file, non-numeric value or JSON write failure returns diagnosable error without silent PASS.

8. output.json contract

The output file must be suitable for automated processing, audit review and correlation with the source input.csv row.

{
  "utility": "TotalAshChecker",
  "api": "Total Ash",
  "batchNumber": "",
  "overallStatus": "PASS|WARNING|FAIL",
  "checkedAtUtc": "2026-05-18T00:00:00Z",
  "checks": [
    {
      "parameter": "TotalAshPercent",
      "value": "3.8",
      "unit": "%",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "LimitPercent",
      "value": "5.0",
      "unit": "%",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    },
    {
      "parameter": "SubstanceName",
      "value": "Chamomile Flowers",
      "unit": "as specified",
      "status": "PASS|WARNING|FAIL",
      "message": "Rule-based check result"
    }
  ],
  "criticalFindings": [],
  "sourceFile": "input.csv"
}

9. OQ/PQ test scenarios

IDScenarioExpected result
TC-001Valid CSV with expected header and sample rowAll rows are processed; output contains PASS/WARNING/FAIL and parameter-level detail.
TC-002A mandatory input.csv column is missingImport is rejected or the row receives FAIL with schema reference.
TC-003A numeric field contains text or a blank valueType conversion error is recorded; the result is not hidden as PASS.
TC-004A parameter is outside specification or critical limitCritical parameters produce FAIL; non-critical deviations produce WARNING according to the rule.

10. QA/QC, CSV and change control

  • Before production use, the client records executable version, checksum, specification/monograph version, test CSV, expected JSON and IQ/OQ results.
  • Column names must not be changed without updating the validator and test scenarios.
  • The source CSV, output.json and utility version should be stored together as an evidence package.
  • Any change in control rules must go through change control and repeated OQ scenario verification.

Included in packages

EAEU Pharmacopoeia QC Suite

Package for EAEU pharmacopoeial methods: specifications, dissolution, microbiology, impurities and general tests.

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