What the data for this category looks like
Daily documents for general mechanical equipment assembly include assembly process cards, BOMs, torque records, gap adjustment records, commissioning reports, factory inspection sheets, and packing lists. Data sources include PLM/ERP systems, part inspection data, assembly tool collection terminals, test benches, MES systems, and customer technical agreements. Data is updated once per device and per order. Core fields include torque values (unit: newton meters), gap values (unit: millimeters), coaxiality detection data, preload force parameters, and others. Inspection and process records for a single device are generated and archived incrementally as assembly steps are completed.
How these characteristics constrain workflow orchestration
The make-to-order assembly of multiple varieties for this category requires workflows to bind exclusive variables for individual devices, to avoid mixing data from different orders. The collection logic for multiple data sources requires workflows to pull data in the order of assembly processes, to prevent incomplete process data from interfering with verification steps. Inspection records for a single device must be fully closed one by one, so workflows need to set node verification processes to ensure all required documents are uploaded before entering the audit link. In addition, errors during assembly directly affect subsequent installation and operation. Workflows must include exception interception and retry mechanisms to handle temporary issues such as tool disconnections and data transmission delays.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Data source binding rules | Associate three data sources: PLM/BOM, MES assembly records, and torque collection data | Covers the core data sources for inspection and process records of this category |
| Global variable binding | Bind the single-device serial number and order number in variables | Matches the per-device and per-order update frequency, enabling single-instance data isolation |
| Node ID configuration | Bind unique identifiers with nodeId 1 to 7 in process order | Aligns with the sequential logic of assembly processes, avoiding disordered node execution order |
| Node execution interval | 10-15 seconds per process node | Fits the actual operation rhythm of assembly processes, waiting for tool data to complete upload |
| Exception retry count | 3 times, with 60-second intervals between each retry | Addresses scenarios such as temporary disconnection of assembly tools and data transmission delays |
| Context length configuration | 8000 token | Adapts to the long-text output requirement of inspection report generation |
| AI chat node temperature configuration | Temperature switch off, or temperature switch on and set to 0 | Adapts to the deterministic output requirement of inspection report generation |
Three common errors
- When exporting a workflow and its associated JSON file and importing it to another environment, referenced plugins cannot be found. This occurs because the export process did not include local deployment configuration information for the plugins, and only synchronized workflow node logic.
- When using the text2sql node to generate SQL, returned results do not match expectations. This occurs because the exclusive table structure variable in
variableswas not bound, leading to incorrect SQL query scope. - The string returned by the AI chat node starts with a line break. This occurs because the node has format completion logic enabled by default, and the automatic line break configuration was not disabled.
How to confirm configuration is complete
- Trigger workflow execution, check whether each data source node successfully pulls BOM, torque records and other data for the corresponding assembly order, and verify that pulled fields match the preset configuration.
- Simulate a scenario where the gap adjustment record is not uploaded, confirm whether the workflow triggers exception interception and prompts for missing required documents.
- Call the AI chat node to generate an inspection report, confirm that returned content has no extra line breaks, and output meets the format requirements of the inspection sheet.
- Export the workflow and import it into the FastGPT v4.17.0 test environment, confirm that all associated plugins can load normally and execute node logic.
The values provided here are common starting points, and should be evaluated against operational samples specific to the deployment context.