What dairy processing data looks like
Daily documents for dairy processing include raw milk acceptance records, standardized ingredient lists, pasteurization or UHT heat treatment records, CIP cleaning records, filling records, sample retention and microbial test reports. Data sources cover raw milk testing systems, MES production management systems, homogenization and heat treatment equipment, online temperature and flow monitoring systems, CIP systems, and LIMS laboratory management systems. Data updates in real time per milk tank and production batch. Single records include specific fields with units, such as raw milk colony count (CFU/mL), heat treatment temperature (℃), holding time (seconds), and CIP cleaning pH value.
Constraints for source citation and traceability
Data updates in real time per milk tank and production batch. Traceability requires precise matching of batch numbers to avoid linking records from unrelated production batches. Multi-source data comes from different systems. Traceability must link corresponding batch data across each system to ensure complete display of the production chain from raw milk acceptance to filling. Single records include specific fields with units. Retrieval must match both fields and units to prevent mismatches between values and applicable scenarios. Production data is perishable, and errors have serious consequences. Traceability must return results quickly to avoid production risks from delays.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum token count for citation display | 800–1200 characters | Corresponds to the quoteMaxToken parameter, matches the average length of single batch records for dairy processing, and fully displays key testing and operation data |
| Raw data return toggle | Enabled | Corresponds to the responseData parameter, used to directly trace fields and values from original documents such as raw milk acceptance and CIP cleaning records |
| Detailed display toggle | Enabled | Corresponds to the detail parameter, displays the complete traceability chain for the corresponding batch, including equipment numbers, testing times, and other details |
| Batch matching threshold | Top 3 matching results | Accurately locates records for the corresponding milk tank or production batch, avoiding matches to unrelated batches |
| Traceability data refresh interval | Calibrated based on actual measurements | Adapts to real-time updated production data, ensuring returned traceability content matches the current production batch |
Three Common Misconfigurations
- Setting the maximum token count for citation display too low, resulting in truncated traceability content that cuts off critical batch numbers and test values, preventing precise traceability.
- Failing to configure correct association rules for structured production documents, leading to some batches' raw milk acceptance or microbial test records not being properly linked, so Q&A results cannot match corresponding production data.
- Failing to configure differentiated traceability visibility for different types of queries, resulting in failure to meet requirements for scenarios that need to display sources, and redundant information appearing in scenarios that do not need it.
How to Verify Correct Configuration
- Initiate a process query targeting a specific milk tank batch, and check if the returned result includes the complete batch number and corresponding test values.
- Enable the traceability viewing function, and confirm access to original LIMS reports, CIP records, or MES documents.
- Test different types of queries to verify that display permissions for sensitive parameters meet configuration requirements.
- Check the FastGPT v4.17.0 backend logs to confirm that the response time of traceability requests meets production requirements.
All provided configuration values are common starting points, and should be evaluated against applicable on-site samples.