What the data for this category looks like
Data for this category comes from registered process documents, raw material batch ledgers, DCS control systems, weighing systems, LIMS laboratory information management systems, chromatography data systems, and QMS quality management systems. Data updates occur once per production batch and per process step. Daily documents include batch production records, material balance ledgers, reaction and purification process records, cleaning validation records, impurity profile reports, deviation and change management documents. Data fields include batch identifiers, process parameter values, material weighing data, impurity test values, solvent residue values, and compliance audit records. Units vary based on test items and process links.
What constraints these characteristics impose during deployment and upgrade
Multi-source heterogeneous data and batch-based updates require compatibility configuration for multi-system data docking during deployment. Differences in document formats across process links require retaining compatible import logic for older template versions. High-frequency batch updates require sufficient storage and retrieval performance to avoid data synchronization delays. The strong correlation between impurity profiles and compliance documents requires retaining data association logic to allow quick access to relevant batches and test records during audits. The rigor of registered processes requires permission control for core parameters to prevent arbitrary modifications that could affect audit accuracy.
How to configure settings
This configuration is based on FastGPT v4.17.0:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 10–20 connections | Adapts to concurrent requirements of high-frequency batch-level data writing and retrieval |
STORAGE_S3_ENDPOINT | Fill in according to the enterprise's existing storage service address | Meets storage needs for docking with LIMS and chromatography data systems |
| Single import data limit | 500–1000 entries per import | Matches the number of documents generated per batch for this category, avoiding import timeouts |
REDIS_URL | Fill in according to the enterprise's existing cache service address | Accelerates batch data retrieval and associated queries |
| Permission control configuration | Divide by job roles | Ensures access compliance for registered process and impurity profile data |
Three Common Configuration Mistakes
- Phenomenon: When importing knowledge base data exported from older versions, a prompt appears indicating field mismatch or format errors. Cause: The template was not adjusted to match the exclusive document field structure of this category, resulting in missing or incorrectly formatted exclusive fields such as batch numbers and impurity profile data.
- Phenomenon: When searching for impurity profile reports, the corresponding batch production records cannot be linked. Cause: Batch identifier fields across different systems were not bound, resulting in no data association logic.
- Phenomenon: Database connection timeouts occur when importing multiple batches of data. Cause: The
DB_MAX_LINKparameter was not adjusted to a value adapted for concurrency, resulting in insufficient database connections to handle high-frequency write requests.
How to verify successful configuration
Perform the following checks:
- Perform a single batch data import, check that the import status is successful, and review the import logs for no field mismatch prompts.
- Search for the impurity profile report of a specific batch, confirm that the batch production records and weighing data can be retrieved, and verify that the association is correct.
- Adjust the
DB_MAX_LINKparameter to different values, observe the concurrent import performance, and confirm that the parameter value meets the current business concurrency requirements. - Verify that only authorized personnel can access sensitive data related to registered processes and impurity profiles using accounts with different job roles.
The values provided are common starting points and should be measured against the reader's own samples.