What data looks like for this category
Data for this category mainly comes from order design systems, sheet material and wood batch ledgers, CNC cutting and drilling equipment logs, ERP/MES systems, and moisture content test records. Daily documents include order disassembly drawings, cutting lists, edge banding and drilling programs, coating process parameters, hardware bill of materials, trial assembly and packaging records.
Data updates follow a per-order basic cycle, with real-time synchronization for each batch of material entry and daily production links. Fields include panel size, batch number, process parameters, test results, and other details. Formats are flexibly adjusted based on customization requirements.
What constraints these characteristics impose on workflow orchestration
Custom order-driven production involves a large number of panels with highly personalized dimensions. This requires workflows to support parallel processing of traceability data for different panels across multiple nodes.
Non-standardized documents from multiple sources require workflow configurations to adapt to input parsing for different formats. High data update frequency and strict real-time requirements mean workflows must set reasonable trigger timing to avoid data lag.
Defects such as panel misassembly and color difference are linked to multi-stage data. Workflows must connect all nodes across the order disassembly, production, and testing full link, to cover full-process data correlation.
How to set configurations
This document is written based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | Isolate by order ID, bind lifecycle to a single session | Ensure no mutual interference between multiple API or web requests, matching the independent traceability scenario of custom orders |
| Node trigger condition | Match node completion signals by nodeId | Accurately trigger subsequent analysis links, avoid invalid execution of non-target nodes |
| Parameter transfer method | Pass system parameters through workflow node outputs | Avoid reliance on global variables, adapt to access requirements for multi-source production data |
| Timeout threshold | 600 seconds | Cover the conventional time consumption of sheet material moisture content testing and CNC equipment log retrieval |
| Result storage duration | 30 days | Match the traceability requirements of the full order cycle, avoid invalid data occupying resources |
| Parallel node limit | Top 10 entries | Adapt to the panel quantity scale of custom orders, avoid resource overload |
Three common misconfigurations
- Symptom: Global parameters do not update with requests after the workflow runs, resulting in cross-session data crossover. Cause: The
variablesconfiguration is not isolated by order ID, causing multiple requests to share the same variable instance. - Symptom: The judgment node always triggers the ELSE branch, and cannot correctly match abnormal panel sizes. Cause: The "equals" "starts with" rules are incorrectly set as ELSE branch logic, confusing the branch attribution of matching conditions.
- Symptom: Device log parameters passed by the system are not recognized by the workflow, and the fields are empty. Cause: System parameters are not correctly passed through workflow node outputs, and incorrectly rely on unconfigured global variables.
How to confirm the configuration is correct
- Initiate a simulated order request, check whether the order ID parameter in
variablesupdates independently with the request, with no cross-session crossover. - Input abnormal panel size data, verify that the branch trigger logic of the judgment node matches the configuration, with no branch errors.
- Access CNC equipment log parameters, confirm that the workflow node can normally read and pass system-side parameters, with no empty fields.
- Run the full-process workflow, check timeout triggers, and confirm that the time consumption meets the expectations of actual production links.
The values provided are common starting points and should be measured against the reader's own samples.