Data Overview for This Category
This category covers the full data chain from raw materials, production processes to final testing. Data sources include raw material quality certificates, heating furnace systems, press collection data, MES systems, non-destructive testing instruments, and customer forging drawings. Daily documents include forging process specifications, cutting cards, heating furnace records, forging process logs, mold life records, heat treatment entrustment slips, and ultrasonic testing reports. Data is updated once per piece, per batch, or per furnace heat. Core fields include furnace batch number, forging batch number, forging ratio, fiber direction, defect type, and testing parameters.
Constraints on Workflow Orchestration
The decentralized storage of multi-source data requires workflow configurations to include cross-node data pulling and aggregation steps, to ensure that raw material furnace batch numbers, production process parameters, and testing results can be associated and matched. Frequently updated data requires workflow startup rules triggered by furnace heat or batch to avoid redundant execution. Correlation checks for core fields (such as matching furnace batch numbers and forging batch numbers) must be embedded in the workflow’s pre-judgment nodes to prevent incorrect data from entering subsequent analysis links. Analysis logic for typical defects including folds and cracks must be bound to association rules for corresponding process documents and testing data, to ensure the integrity of analysis basis.
Configuration Settings
The following configurations are based on FastGPT v4.17.0, and are adapted to the quality traceability workflow orchestration needs of forging and die forging scenarios.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Global variable configuration | Bind three core global variables: furnace batch number, forging batch number, and forging ratio | Matches the per-furnace-heat/per-batch data update feature of this category, ensuring data consistency across the entire workflow |
| Node ID binding | Associate the nodeId of the heating furnace data node and non-destructive testing node | Enables precise pulling and association of multi-source data, avoiding cross-node data confusion |
| Prompt variable invocation | Call process specification fragments from variables, with a context length not exceeding 1000 characters | Covers personalized configuration requirements for forging process specifications, adapting to deformation step requirements for different forgings |
| Large model response verification | Set empty response retry count to 2 times, timeout threshold to 600 seconds | Addresses occasional empty responses from large models, meeting the requirement for result integrity in this category’s analysis |
| Boolean judgment trigger | Configure to trigger subsequent analysis nodes when "furnace batch number matches successfully" | Aligns with the core business link of this category that requires verifying material furnace batches and forging batches |
Three Common Configuration Mistakes
- Phenomenon: The boolean judgment node in the workflow shows a result of false, even though the boolean value of the preceding node is configured as true. Cause: Incorrect node ID binding; the variable read by the judgment node does not match the actual variable of the preceding node.
- Phenomenon: The AI chat node repeatedly returns
chat:LLM_model_response_emptywith no valid analysis content. Cause: No large model empty response retry mechanism is configured, and the timeout threshold is set too short to wait for the model to return a normal result. - Phenomenon: Global variables do not sync the latest furnace batch number data, leading to batch matching failure. Cause:
variablesupdates are not triggered per furnace heat or batch, and the workflow uses variable values from the previous batch.
How to Confirm Configuration Completion
- Manually trigger a single furnace heat test workflow, check the global variable panel, and confirm that fields such as furnace batch number and forging batch number match the current test data.
- Simulate a large model empty response scenario, verify whether the preset retry mechanism is triggered, and confirm that the retry count and timeout threshold meet the configuration requirements.
- Configure a boolean judgment test case, set the boolean value of the preceding node to true, check whether the judgment node correctly returns true, and verify the accuracy of node ID binding.
- Upload forging data from different batches, confirm that relevant fields in
variablesare automatically updated when the workflow starts, with no old data remaining.
The values provided are common starting points and should be measured against the user's own samples.