What the Data for This Category Looks Like
Daily documents for this category include control plans, process flow diagrams, work instructions, first-piece and patrol inspection records, SPC reports, PPAP materials, and 8D reports. Data sources include customer drawings and special characteristic lists, ERP/MES systems, measurement and inspection tool data, equipment process parameters, and supplier quality certificates. Documents include fields such as customer special characteristic codes, process identifiers, inspection thresholds, actual inspection values, and batch numbers. Units vary by inspection item, such as millimeters, newton meters, and percentage. Batch records update per production batch. Process control data updates per shift. Real-time equipment parameters are collected continuously.
Constraints Imposed on the "Workflow Orchestration" Link
Workflows must support connecting nodes from systems including ERP, MES, and measurement and inspection tools to meet multi-source data access needs. This avoids review deviations caused by scattered data. Workflows must support event-triggered or scheduled trigger modes to match high-frequency update business rhythms. This adapts to production nodes per batch and per shift. Workflows must include built-in multi-format parsing support to handle multi-type document processing needs. This covers document structures such as control plans and 8D reports. Workflows must include field verification steps to meet strict compliance requirements. This ensures customer special characteristic transmission aligns with vehicle customer quality system rules, and reduces the risk of batch defects reaching vehicle manufacturers. Workflows must support parallel batch document processing to match mass production attributes. This prevents delays in single-batch review.
Configuration Guidelines
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind batch data fields from ERP/MES and measurement and inspection tools | Data sources for this category are scattered, core fields such as batch numbers and special characteristics need to be referenced uniformly |
| Question Classification Node | Keep default configuration after initializing the model | Adapts to the problem classification logic for automotive parts documentation, avoids configuration conflicts caused by model switching |
| Single Search Limit | Top 8 entries | Matches the number of key fields of core documents for this category, covers main review dimensions |
| Timeout Threshold | 120 seconds | Adapts to the average time required for batch document parsing, avoids single-batch processing interruptions |
nodeId | Bind the output ID of the document parsing node | Ensure that the latest parsed document content is referenced during cross-review |
| Maximum Context | Calibrated based on actual measurements | Adapts to the content length of multiple types of documents, avoids truncation of key special characteristic information |
Three Common Misconfigurations
- Phenomenon: After selecting a knowledge base in the workflow, no optional values appear in the
variablesreference dropdown menu. Cause: The output of the data source node is not bound as the configuration source forvariables, so no available variable pool exists. - Phenomenon: When creating a new Question Classification Node, running or saving and publishing with the initialized AI model triggers an error. Normal function resumes after switching the model. Cause: The initialized model has not completed platform backend configuration verification, and is not included in the available model list.
- Phenomenon: The annotation logic configured for "Trigger after stream reply completes for the AI chat component does not run. Cause: The component’s stream reply mode is not enabled, or the annotation node is not correctly bound to the end event of the AI reply.
How to Verify a Successful Configuration
- Trigger the workflow for a test batch, and confirm the
variablesdropdown menu shows bound fields including batch numbers and special characteristics. - Run the Question Classification Node, and confirm the AI model options load normally with no error prompts.
- Enable stream reply mode, submit a test document, and verify the annotation logic triggers after the reply completes.
- Review the workflow running logs, and confirm all document parsing node output fields match the preset review dimensions.
The values provided are common starting points and should be measured against the reader's own samples.