What data for this category looks like
Data for this category primarily comes from daily production documents of electroplating plants, electronic connector and hardware surface treatment workshops. These documents include bath analysis records, process parameter cards, fixture usage records, film thickness and adhesion test reports, hazardous waste management ledgers, and online water quality monitoring records. Data sources cover customer surface treatment specifications, bath test results, rectifier operating data, real-time water quality monitoring results, and hazardous waste registration ledgers. Data update frequencies include per bath cycle, per shift, and fixed monitoring cycles. Fields include bath component proportions, process temperature and current, fixture numbers, film thickness values, emission indicators, and more. There is no unified standardized format, and the format changes with workshop production adjustments.
What constraints these characteristics impose on workflow orchestration
Data for this category is multi-source and has no unified update rhythm. Workflow orchestration must support triggering data pulling per bath cycle, per shift, or per monitoring cycle, and adapt to dynamic reading of non-standardized fields. Unlike the spraying category, which uses coating atomization and curing as core parameters, this category uses bath state and pre-treatment data as core basis. Since production data directly relates to the process costs and compliance requirements of bid quotations, the workflow must embed data verification nodes to filter abnormal values and expired records. Adjacent production links rely on real-time parameters such as bath liquid and fixtures, so the workflow must reserve callable variable nodes. This ensures that process parameters in quotations and documents match actual production, and avoids bid invalidation caused by parameter mismatches. Since errors can lead to batch rework and environmental penalties, the workflow must set an abnormal alert link to trigger prompts when data is abnormal.
Configuration Settings
This page is written based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
| Trigger Rule | Trigger per bath cycle or scheduled per shift | Matches the update rhythm of this category's data based on production cycles |
| Variable Binding | Bind production data fields via variables | Adapts to non-standardized dynamic data such as bath components and process parameters |
| Node Identification | Bind verification nodes via nodeId | Used to quickly locate abnormal links |
| Data Pull Limit | Pull up to 10 entries per single request | Matches the number of bath cycles in a single production batch |
| Timeout Setting | 600-second timeout per single call | Prevents delays in pulling multi-source data from affecting bid preparation |
| Data Verification | Set abnormal filtering thresholds based on actual measurements | Adapts to production data judgment standards of different workshops |
| Output Mapping | Bind bid document template fields | Ensures generated quotations and document parameters match actual production |
Three Common Mistakes
- No submit button appears in the session interface after the workflow runs, and only empty text is returned. The cause is that user-submitted bid project parameters are not bound via
variables, so the interaction node is not activated. - When calling the Mermaid MCP Server to generate a flow chart, the returned image link is empty. The cause is that the correct external service call node is not configured in the workflow, and process parameters are not passed as generation basis as required.
- Loop execution terminates automatically before reaching the preset number of times, failing to complete all data pulling. The cause is that the loop node's termination condition does not match the data update frequency, causing data pulling failure to trigger early termination.
How to Confirm Proper Configuration
- Trigger the workflow, then check if a submit button pops up in the session interface to confirm the interaction node is activated normally.
- Call the Mermaid MCP Server node to verify if a valid image link is returned, confirming the external service configuration is correct.
- Run the loop node to check if production data is pulled at the preset rhythm, confirming the loop condition matches the data update frequency.
- View the workflow logs to confirm all data nodes correctly read production document fields with no abnormal error reports.
The values provided here are common starting points and should be measured against the reader's own samples.