What the Data for This Category Looks Like
Production data for lithium-ion cell manufacturing comes from raw material batch ledgers, workshop MES systems, slurry and coating testing equipment, workshop dew point monitoring devices, formation and grading cabinets, and laboratory testing equipment. Daily generated documents include batching records, coating and rolling parameter ledgers, winding/laminating process records, liquid injection process records, formation and grading data reports, and OCV and safety test reports. Data updates occur in real time per production batch and per individual cell. Fields include batch number, equipment ID, slurry solid content, coating areal density, dew point temperature, cell internal resistance, and other attribute items with clear units.
Constraints Imposed by These Characteristics on Workflow Orchestration
This category’s data is multi-source and updated at high frequency. Workflows must support triggering by process step to adapt to the inflow rhythm of real-time data. Multi-source data must be spliced in the order of the production process. Workflows need to be configured with multiple input nodes to merge outputs from different devices. Core parameters must be strictly verified. Workflows must filter abnormal data through parameter rules. Batch association requires workflows to pass context identifiers, ensuring process documents and abnormal reports are bound to the corresponding production batch. High-frequency data processing requires controlling loop logic complexity to avoid node execution timeouts that affect overall process stability.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Include batch number, solid content threshold, dew point threshold, internal resistance threshold | Used to verify the legality of input data from each link, matching the core production parameters of lithium-ion cell manufacturing |
nodeId | Bind the formation and grading node and the abnormal report generation node | Implement context transfer of batch data, ensuring that reports are associated with the corresponding production batch |
| Multi-source data merging node | Splice data in the order of batching → coating → assembly → formation and grading | Match the standard production process of lithium-ion cell manufacturing |
| Loop body nesting level | No more than 2 levels | Avoid loop logic complexity exceeding the processing requirements of multi-cell inspection data for a single batch |
| Timeout retry count | 3 times, 60 seconds interval each | Respond to temporary network fluctuations of equipment such as formation and grading cabinets |
| Abnormal trigger branch | Block the process when dew point data is lower than -40℃ | Match the strict requirements of lithium-ion cells on production environment humidity |
Three Common Misconfigurations
- When calling a database node in the workflow, the error "connect ETIMEDOUT" is displayed, but the database can be accessed normally locally. Cause: The intranet IP of equipment such as formation and grading cabinets has not been added to the network whitelist of the FastGPT container, or the correct device access port has not been configured.
- The loop body cannot implement multi-level nesting, and a parameter error prompt pops up during execution. Cause: Multi-level loop support has not been enabled in the workflow settings of FastGPT v4.17.0, or the nesting level exceeds the system limit.
- The generated abnormal report lacks the coating and rolling parameter field. Cause: The extraction rule for this parameter has not been configured in
variables, and the output data of the corresponding node has not been bound.
How to Verify Successful Configuration
- Submit production data for a test batch, check whether the workflow triggers each node in the preset process order.
- Simulate an abnormal scenario where dew point data is lower than -40℃, confirm whether the process triggers the blocking branch and generates an abnormal prompt.
- View the generated process documents and abnormal reports, confirm that all configured
variablesfield data is included. - Test the loop body processing multi-cell inspection data for a single batch, confirm that the results are correctly spliced and written to the document.
The values provided are common starting points and should be evaluated against the reader's own samples.