What the data for this category looks like
Data sources for cement clinker and grinding production include online composition analysis, DCS systems, laboratories, kiln and grinding equipment, raw fuel ledgers, and energy metering devices. Data updates follow three rhythms:
- Real-time collection of kiln temperature and mill load parameters
- Shift-based updates for inspection records and batching adjustment plans
- Daily summaries of energy consumption and quality inspection results
Daily production documents include raw material batching plans, kiln operation records, laboratory reports, quality control notices, equipment inspection forms, and energy reports. Core fields include raw material mill runtime, kiln temperature setpoint, raw fuel ratio values, clinker output, and energy consumption. No unified fixed format exists. Mapping must be completed separately for each document type.
What constraints do these characteristics impose on workflow orchestration
Multi-source heterogeneous data sources require workflows with multiple nodes to connect to different data sources, avoiding data pull conflicts. Differences in update frequencies require workflows to set multiple trigger rules, adapting to real-time, shift-based, and daily collection rhythms. This prevents repeated data pulls or missed data. Diverse document types and inconsistent field mapping rules require splitting processing nodes by document type. Independent field matching logic must be configured for each category. Production links have strong interconnectedness: single parameter anomalies may trigger chain issues. Workflows must add linkage verification nodes to jointly verify kiln temperature and batching parameters, preventing abnormal data from entering the final report.
How to configure the workflow
This configuration is compatible with FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Trigger Timing | Configure in three categories: real-time category triggers every 60 seconds, shift-based category triggers every 8 hours, daily category triggers every 24 hours | Matches the update rhythms of online composition analysis, inspection records, and energy reports |
| Global Variable Binding | Bind variables to production shift, equipment number, current date | Adapts to ledger summary needs for multiple shifts and equipment, unifies parameter calling rules |
| Data Source Association | Associate 4 types of data sources: online composition analysis, DCS, laboratory, raw fuel ledger | Covers all core production data sources, avoiding data omission |
| Field Mapping Rules | Configure separately by document types such as raw material batching, kiln operation, laboratory report | Adapts to field differences of different documents, ensuring accurate data matching |
| Parameter Verification Thresholds | Clinker strength deviation ±2MPa, raw fuel ratio deviation ±0.5 tons | Matches the reasonable fluctuation range of production processes, filtering abnormal data |
| Node Retry Configuration | Retry failed nodes 2 times, retry interval 30 seconds | Addresses temporary network fluctuations or brief unavailability of data sources |
Three common configuration mistakes
- Phenomenon: Ledger fields generated after workflow runs are empty. Cause: The production shift parameter in
variablesis not correctly bound, making it impossible to match the data source for the corresponding shift. - Phenomenon: Unable to stop the current debug mode when debugging workflow nodes. Cause: The debug timeout switch is not turned off in the node configuration, or
nodeIdis incorrectly pointed to a loop-executing node. - Phenomenon: Only single-type document data is loaded when configuring multi-document references. Cause: Data source nodes are not split by document type, only a single data source configuration is bound, resulting in only data from the first document category being read.
How to verify a complete configuration
- Trigger test data matching the corresponding update frequency, check the workflow node's running logs to confirm that all data source nodes pull data normally.
- Check the global variable binding configuration, confirm that
variablescovers core parameters such as production shift, equipment number, and current date. - Manually input test data beyond the threshold range, verify that the verification node correctly triggers an exception prompt.
- Export the generated ledger report, confirm that all required document content such as raw material batching, kiln operation, and laboratory results is included.
The values provided are common starting points and should be measured against the reader's own samples.