What the data for this category looks like
Data related to PCB manufacturing comes from customer Gerber/drill tape/BOM files, CAM systems, equipment operating parameters, bath test results, AOI inspection reports, electrical test reports, and laboratory sectioning reports. Daily generated documents include engineering production instructions, Gerber analysis records, drilling and lamination parameters, chemical analysis records, and more. Fields include aperture unit (mm or mil), lamination temperature (℃), defect count, inspection pass rate, and other metrics. Data is updated per production batch, per shift, or collected continuously, and updates in real time as production lines run.
What constraints these characteristics impose on the workflow orchestration link
Multiple heterogeneous data sources require the workflow to be configured with multiple data source pull nodes, each connected to CAM systems, equipment terminals, and inspection systems. The update cadence of per production batch, per shift, or continuous collection requires the workflow to be bound to production batch completion events or scheduled trigger rules, to avoid delayed data or duplicate process triggers. The large number of specialized fields and inconsistent units require the workflow to use variables to bind standardized fields and unify parameter formats. The business characteristic of severe consequences for errors requires configuring exception verification and branch processes, to block non-compliant processes and trigger exception reports.
The configuration in this chapter is based on FastGPT v4.17.0.
How to set the configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Global variable binding | Bind Gerber analysis records, drilling parameters, and AOI report data stored in variables | Matches daily documents and multi-source data sources for PCB manufacturing |
| Node trigger condition | Trigger by production batch completion event, with a delay of 20–30 minutes | Adapts to the update frequency per production batch, reserves buffer time for equipment data upload |
| LLM response verification rule | Check that the response includes engineering production instruction fields and exception type identifiers | Matches the required content for process documents and exception reports |
| Exception branch configuration | Trigger the exception report generation process when the node corresponding to nodeId returns a failure | Corresponds to the severe business risk of errors in PCB manufacturing |
| Timeout threshold setting | 600 seconds | Adapts to the typical time required for CAM equipment parameter pulling and large model calls |
| Variable update trigger | Calibrated based on actual production line data upload rhythm | Adapts to the real-time update frequency of continuous collection |
Three common mistakes
- The preceding boolean field of a judgment node shows as true, but the connected conditional judgment node always returns false. The cause is that the production line status field stored in
variablesis not correctly bound to the parameters of the judgment condition, leading to incorrect reading of the judgment logic. - LLM chat nodes occasionally return empty responses, triggering the
chat:LLM_model_response_emptyerror. The cause is that response verification and retry branches are not configured, failing to cover the business scenario of occasional large model exceptions. - Global variables are not updated with the latest inspection data in real time. The cause is that the variable update trigger timing does not match the equipment data upload rhythm, and the update is not triggered based on the production batch node completion status.
How to confirm the configuration is complete
- Manually trigger a simulated production batch workflow, check whether global variables correctly load preset data such as Gerber analysis records and drilling parameters.
- Simulate the scenario of an empty LLM response, verify whether the preset retry or exception report generation process is triggered.
- Adjust the node trigger delay time, check whether the workflow starts execution after the set delay duration.
- Check whether the binding parameters of the judgment node match the fields in
variables, verify that the conditional judgment logic operates normally.
The values provided are common starting points and should be measured against the reader's own samples.