What Data Looks Like for This Category
Daily documents for this category include assembly process cards, BOMs, torque records, gap adjustment records, commissioning reports, factory inspection sheets, and packing lists. Data comes primarily from PLM/ERP, part inspection data, assembly tool collection systems, test benches, MES systems, and customer technical agreements. Updates occur once per device or per order. Fields include part numbers, torque values, gap parameters, and test results. Some parameters have defined units, such as newton-meters for torque and millimeters for gaps. Business processes focus on order-based assembly of multiple product varieties. Final performance relies on component fit and on-site debugging. This differs from part machining categories, where core qualification depends solely on single-dimensional size compliance.
How These Characteristics Constrain Workflow Orchestration
Multi-source heterogeneous data sources require workflows to configure variables to store cross-system field mapping rules. This unifies document formats exported from different systems. The update frequency per device or order requires workflow trigger logic to bind order or device IDs. Use nodeId to associate exclusive documents and records for the corresponding batch. The time-consuming multi-level BOM verification step requires splitting BOMs into batch-verifiable sub-nodes. This reduces single-node processing pressure. Parameters with units such as torque and gap need verification rules configured in the workflow. This avoids mismatched unit inputs. The test closed-loop link must connect commissioning, fault records, rectification orders, and other nodes. This forms a continuous process chain.
Configuration Settings
This page applies to FastGPT v4.17.0. The following configurations are designed based on the features of this version.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | Store grouped by order or device ID | Matches the exclusive data update frequency per device or order, ensures the workflow calls documents for the corresponding batch |
nodeId | Bind to the document ID of the corresponding batch | Associates assembly records and inspection data for each device or order |
| Issue optimization | Place after downstream data processing nodes | Corrects parameter errors in node outputs, meets the precision requirements of assembly links |
| Timeout threshold | 600 seconds | Covers the standard processing duration of multi-level BOM verification and test data validation |
| Parameter validation | Enable field unit matching rules | Meets requirements for business parameters with units such as torque and gap |
| Maximum context | Calibrate based on actual measurements | Adapts to the length of assembly documents, avoids context overflow |
| Single search limit | Top 10 entries | Meets the field quantity requirements for BOM verification |
Three Common Errors
- Phenomenon: Workflow invocation produces empty conversation logs with no execution records. Cause:
variablesare not configured to bind context data for the corresponding order or device, so the workflow cannot read associated assembly documents and records. - Phenomenon: A Docker-deployed FastGPT instance returns normal model test results, but workflow node execution fails. Cause: No system environment variable mapping rules are added to the workflow configuration, so workflow nodes cannot call the deployed model service.
- Phenomenon: The issue optimization component is configured but does not take effect, with output results not corrected as expected. Cause: The issue optimization component is placed before the workflow’s starting node, so it does not process output content from downstream nodes and cannot correct parameter errors.
How to Confirm Proper Configuration
- View the workflow’s
variablesconfiguration, confirm that field mapping rules bound to the corresponding order or device ID are set, and verify correct field loading by previewing node data. - Trigger a test workflow, check if node execution logs include business data such as assembly documents and torque records, and confirm that data sources are correct.
- Adjust the timeout threshold value, verify that the workflow completes normally when processing multi-level BOM verification, and confirm that the timeout threshold fits the current business scenario.
- View the trigger position of the issue optimization component, confirm that it is located after downstream data processing nodes, and verify that parameter correction takes effect by testing output content.
The values provided here are common starting points, and should be evaluated against the reader's own samples.