This document applies to FastGPT v4.17.0.
What This Category’s Data Consists Of
Data for this category primarily comes from customer-provided BOMs, Gerber coordinate files, line change lists, MES systems, mounters, SPI/AOI inspection equipment, reflow oven temperature collection devices, and solder paste and component batch ledgers. Daily documents include first-piece confirmation records, repair traceability labels, and solder joint quality reports. Data updates occur in real time per work order and each line change. A single work order’s data includes fields such as part number, reference designator, component batch, furnace temperature parameters, and inspection results. Field units vary by corresponding document type, with no unified fixed standard.
Constraints Imposed on Workflow Orchestration
Data for this category comes from scattered sources and has flexible update rhythms. Workflows must support parallel pulling from multiple data sources to avoid single-node processing blocking. Field structures differ significantly across multiple document types. Workflows must include built-in field mapping rules to adapt to part number fields in BOMs and defect detection field formats in SPI reports. Frequent work order and line change updates require workflows to support dynamic triggering, to adapt to real-time synchronized ledger data. The high-risk consequences of wrong material placement and solder joint failure require workflows to add pre-check nodes. These nodes verify the matching relationship between part numbers, reference designators, and alternative materials, to ensure data accuracy. Traceability requirements also require workflows to retain complete link logs, associating traceability labels with corresponding work order data to facilitate subsequent problem troubleshooting.
How to Set Configurations
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
variables | Include three core variables: work order ID, component batch, furnace temperature parameters | Covers the core statistical and traceability dimensions of production ledgers for this category |
| Node timeout setting | 600 seconds | Adapts to the time consumption requirements of parallel pulling and verification from multiple data sources, avoiding task interruptions |
| Field mapping rules | Automatically match fields by document type | Adapts to the differences in field structures across multiple document types for this category |
nodeId | Assign unique identifiers to check nodes and data pulling nodes | Facilitates workflow debugging and quick location of failed nodes |
| Concurrent processing threshold | First 20 work orders | Avoids system resource overload, adapting to scenarios with parallel processing of multiple work orders |
Three Common Configuration Mistakes
- Phenomenon: When calling a workflow via API, the variables configured in
variablesare not returned correctly. Stitching works normally during debugging but anomalies occur during online calls. Cause: The correspondingvariablesparameter is not bound in the workflow’s output node, causing the variables to not be returned with the result. - Phenomenon: When calling workflows concurrently for multiple work orders, the front-end interface shows unresponsive status. Cause: The concurrent processing threshold is set too high, exceeding the system resource carrying capacity, and parallel request volume is not limited.
- Phenomenon: Dynamic tokens cannot be passed in workflows to call external interfaces. Cause: Tokens are not configured as dynamically updatable
variablesvariables, only fixed values are bound to external interface calling nodes.
How to Verify Successful Configuration
- Trigger a work order-level workflow, check whether the output results include all configured
variablesvariables, and verify that the variable values match the input parameters. - Simulate concurrent calls for multiple work orders, observe system resource usage, and adjust the concurrent threshold to match the carrying capacity of the current deployment environment.
- Switch between different types of document data sources, verify whether the field mapping rules automatically adapt to the field formats of the corresponding documents.
- Locate failed nodes, quickly troubleshoot abnormal links via
nodeIdidentifiers, and confirm that check and pulling nodes are running normally.
The values provided here are common starting points and should be measured against the reader's own samples.