What data looks like for this category
Data for this category covers approved formulation processes, material batches, MES/electronic batch records, equipment and environmental monitoring data, and LIMS and quality management system content. Data is updated per production batch, each key process step, and fixed monitoring schedules. Daily documents include master production documents, batch production records, batch packaging records, cleaning records, inspection records, deviation/CAPA/change documents, and batch release review forms. Fields include material batch numbers, process parameter values, deviation descriptions, inspection results, and equipment operating parameters. Units include kilograms, degrees Celsius, hours, percentage, and similar units.
What constraints do these characteristics impose on workflow orchestration
Data sources are scattered and update frequently, so workflows must support connecting to multiple system data source nodes and trigger execution per batch. There are many document fields that must comply with GMP compliance requirements, so workflows must include field validation nodes to ensure generated process documents and exception reports contain all required fields. The entire batch production process requires operations and corresponding documents to be generated synchronously, so workflows must bind process step nodes and document generation nodes to ensure corresponding document drafting is automatically triggered after an operation is completed. Additionally, batch release reviews need to be associated with multi-dimensional data, so workflows must integrate inspection, deviation, and environmental monitoring data before generating release judgment documents.
How to configure settings
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
variables | Bind batch number, material batch, and process step number as required variables, with a value range of 1–20 characters | Material batch numbers for this category are typically 1-20 characters, comply with GMP data identification specifications, and adapt to the variable binding rules of FastGPT v4.17.0 version |
| Data Source Node Configuration | Connect to read-only interfaces of MES, LIMS, and quality management systems, with a timeout setting of 600 seconds | Production system data responses typically take 300-500 seconds; reserving sufficient buffer time prevents workflow termination due to timeout |
| Document Generation Node | Call built-in compliant templates to generate batch production records and deviation reports, with field mapping rules strictly matching required fields | GMP requires batch records to fully include all specified fields to ensure documents meet regulatory requirements |
nodeId Trigger Rules | Configure to trigger the review node after the document generation node passes validation | Ensure document content complies with regulations before entering the review link, which aligns with production process approval logic |
| Failure Retry Configuration | Retry 3 times when data source connection fails, with an interval of 120 seconds | Occasional network fluctuations in production systems can be recovered through retries, avoiding workflow interruptions caused by a single connection failure |
Three Common Mistakes
- Symptom: Database connection error
connect ETIMEDOUTappears in the workflow, and local access works normally. Cause: The database access whitelist is not configured in the FastGPT container network, or network isolation between the container and the database is not lifted. - Symptom: The batch number bound to
variablesis empty during workflow execution, and corresponding documents cannot be generated. Cause: The variable passing rule is not configured before the workflow starts, or the trigger node does not correctly pass the batch parameter. - Symptom: Workflow configuration does not take effect after modifying the docker-compose file to add environment variables. Cause: The compose configuration is not reloaded and the service is not restarted, or the environment variable name is misspelled and does not match FastGPT recognition rules.
How to Confirm the Configuration is Correct
- Manually pass a test batch number to check if
variablesare correctly bound to workflow node parameters. - Simulate a production system data request to verify if the data source node can return valid data within
600 seconds. - Trigger the document generation node to check if the output batch records contain all GMP-required required fields.
- Trigger the failure retry logic to verify if the node retries the specified number of times after a connection timeout.
The values provided here are common starting points and should be measured against the reader's own samples.