Based on the application scenario of third-party testing laboratories, this article demonstrates the practical application of intelligent formula engines and quality control systems within LIMS. Technical solutions enable automated calculation of testing data and compliance judgment, effectively addressing prominent pain points of traditional workflows including low efficiency and difficult quality control. This delivers implementable digital transformation solutions for laboratories.

I. Project Background

The third-party testing industry is experiencing rapid development. Data accuracy, computational efficiency and quality control capacity have become core pillars for stable laboratory operation. As testing business volumes keep rising, clients impose increasingly stringent requirements on report delivery timelines, exposing severe drawbacks of manual traditional management models.

A provincial product quality supervision and inspection institution primarily conducts testing for food and environmental matrices, issuing tens of thousands of test reports annually. Previously, the full business workflow relied on manual operations: inspectors manually input raw data, calculated results item by item, then quality control personnel performed compliance reviews against standard specifications.

The full workflow presented multiple critical pain points:

1. Manual calculation yields low efficiency and carries high risks of computational errors;
2. Quality control judgment depends on staff experience, introducing subjective bias to results;
3. Long report compilation cycles fail to meet clients’ tight delivery deadlines;
4. Difficult full data traceability prevents closed-loop implementation of quality management systems.

To resolve the above challenges, the institution deployed a LIMS built on the Gikam LCDP low-code platform. Deep integration of an intelligent formula engine and standardized quality control architecture enables automatic computation of testing data and intelligent compliance judgment, comprehensively boosting laboratory operational efficiency and overall quality management performance.

II. System Architecture and Technical Selection

1. Overall Architectural Design

Constructed on the Spring Cloud microservice framework, the system adopts the Gikam LCDP low-code platform as its technical foundation to deliver full-process digital management of testing businesses. The entire architecture consists of three tiers: infrastructure layer, business application layer and presentation interaction layer.

2. Testing Calculation Engine Design

The built-in testing calculation engine adopts a plug-in architecture that supports flexible registration and dynamic expansion of diverse calculation functions. Core calculation functions cover common testing scenarios including statistical analysis, precision evaluation, error correction and solution preparation.

This plug-in design delivers distinct advantages: business personnel can add custom formulas through configuration without underlying coding, while the system automatically parses and executes formulas. Meanwhile, the calculation engine incorporates robust error handling logic that automatically captures and alerts issues such as division-by-zero overflow and data type mismatches, guaranteeing reliable calculation outputs.

III. Implementation of Core Functions

1. Full Lifecycle Management of Testing Tasks

The system enables end-to-end digital management covering sample acceptance & commission creation, task assignment, testing analysis, quality control judgment and report issuance. Taking heavy metal testing in food as an example, the testing workflow proceeds as follows:

Commission Creation Stage

After clients submit testing commissions, the system automatically parses test items and generates task checklists.

Intelligent Task Allocation Stage

The system automatically matches inspectors and experimental equipment based on test methods and inspection teams to achieve rational task distribution.

Experimental Recording Stage

After completing pre-treatment, inspectors input raw data into the system.

Automatic Calculation Stage

The formula engine performs batch automatic calculation of sample concentrations per pre-defined computational formulas.

Quality Control Judgment Stage

The system judges result compliance against established quality control standards.

Report Generation Stage

The system dynamically renders report content via Word templates, supporting electronic signatures and anti-counterfeiting watermarks.

2. Quality Control System Architecture

The system establishes a full-process quality control framework covering pre-analysis, in-analysis and post-analysis stages.

• Pre-analysis: Standardize sampling locations and methodologies via sampling point management; automatically verify equipment status and check calibration validity and metrological certification status.
• In-analysis: Monitor reagent and environmental background via blank tests; verify method accuracy through spike recovery experiments; assess testing precision using parallel sample analysis. Real-time monitoring is realized via Statistical Process Control (SPC) quality control charts.
• Post-analysis: Automatically judge pass/fail status against preset rules, trigger alerts for abnormal data and initiate re-testing or investigation workflows.

SPC quality control analysis serves as a core system capability, supporting multiple chart types including X-bar charts, median charts, and individual-moving range charts, fully compliant with GB/T 4091-2001 Standard Control Charts. The system automatically triggers alerts when quality control data exceeds control limits or displays trending shifts, prompting technicians to implement timely corrective actions.

3. Automated Word Report Generation

A dual-engine architecture powers automated report generation: the POI-tl engine handles structured report templates with dynamic rendering of charts and images, while the Spire document library fulfills complex layout requirements and PDF conversion.

Report generation consists of five phases: template configuration, data population, verification & review, signature anti-counterfeiting and PDF conversion:

1. Business personnel configure report templates and define data sources & rendering rules via a visual interface;
2. The system automatically extracts data from testing tasks to replace template variables;
3. Reports undergo multi-level review to ensure data integrity and accuracy;
4. Approved reports are affixed with automatic electronic signatures and anti-counterfeiting watermarks;
5. Final documents are converted to PDF format for distribution and archiving.

IV. Application Outcomes and Value Analysis

Beyond quantitative performance indicators, the system delivers remarkable management benefits. Standardized workflows and full audit trails ensure laboratory operations comply with ISO/IEC 17025 requirements, with granular field-level permission control. These enhancements elevate standardized laboratory management and provide robust technical support for subsequent CNAS accreditation audits.

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