What this category of data looks like
The data covers all stages of the injection molding process. Daily documents include injection molding process cards, raw material drying records, mold history logs, first-piece inspection records, patrol inspection forms, and material change and machine cleaning records. Data sources include resin batch and property sheets, injection molding machine operating parameters, mold temperature controller data, manufacturing execution systems (MES), dimensional and appearance inspection results. Data update frequency follows per production batch, each mold change or material change operation, and each shift patrol cycle. Document fields include equipment number, process parameter thresholds, raw material moisture content, mold usage count, and more. Field units include degrees Celsius, megapascals, seconds, millimeters, and others.
What constraints these characteristics impose on workflow orchestration
The high data update frequency and scattered trigger scenarios require workflows to support event-based triggering, rather than fixed-period scheduling. Multiple types of heterogeneous data sources require workflows to integrate documents in different formats and real-time device data, so unified parameter mapping rules must be configured. The number of documents associated with a single production batch fluctuates with mold changes and material changes, so the upper limit of context loading for a single workflow invocation must be restricted to avoid resource overload. Equipment inspection and maintenance issues must be linked to historical data for specific molds and batch raw materials, so workflow nodes must support binding variables and nodeId parameters to pass context, ensuring each workflow instance is associated with exclusive data for the corresponding production scenario.
How to set up configurations
These configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Trigger Condition | Match the production batch number passed via variables | Only trigger the workflow at mold change, material change, or patrol nodes for the corresponding batch, to reduce invalid runs |
| Tool Execution Order | Run in the sequence of the configured execution serial numbers | Ensure that patrol data retrieval, process parameter verification, and maintenance plan generation are executed in logical order |
| Context Loading Upper Limit | First 8 associated historical documents | Match the scale of documents associated with a single production batch, to control memory usage |
| Response Text Filtering | Remove built-in platform statement | Align with the professional scenario of equipment maintenance Q&A, to avoid irrelevant output |
| Timeout Threshold | 600 seconds | Adapt to the average time required for injection molding equipment data retrieval and problem analysis |
| Context Binding | Bind nodeId to pass the current injection molding machine ID | Ensure each workflow node is linked to the historical logs and operating data of the corresponding equipment |
Three common mistakes
- Phenomenon: Multiple tool nodes in the workflow do not execute in the expected order, and some tools are not triggered. Cause: No tool execution serial number is configured, or serial numbers are duplicated, causing the system to fail to identify execution priorities.
- Phenomenon: The AI-generated maintenance response includes unconfigured system statement text at the end. Cause: Response text filtering configuration is not enabled, so the system retains the default built-in output content.
- Phenomenon: Response latency of the problem classification node fluctuates significantly, failing to meet patrol cycle requirements. Cause: Associated documents are not filtered using the scenario parameters passed via
variables, leading to large differences in the volume of documents loaded per invocation.
How to confirm the configuration is correct
- Manually trigger the workflow for the corresponding mold change or material change event, and check whether tools execute in the configured sequence.
- Review the AI-generated maintenance response, and confirm that no unconfigured system statement content appears.
- Review the workflow run logs, and confirm that node call latency falls within the preset timeout threshold range.
- Check whether
variablesandnodeIdparameters correctly pass production batch and equipment ID information.
The values provided are common starting points and should be measured against the reader's own samples.