General Mechanical Equipment Assembly Equipment Inspection and Maintenance Q&A: Workflow Orchestration

Daily documents for general mechanical equipment assembly include assembly process cards, BOMs, torque records, clearance adjustment records

What the data for this category looks like

Daily documents for general mechanical equipment assembly include assembly process cards, BOMs, torque records, clearance adjustment records, commissioning reports, factory inspection sheets, and packing lists. Data sources include PLM/ERP, part inspection data, assembly tool collection, test benches, MES, and customer technical agreements. Updates occur once per device or per order. Document fields include equipment model, order number, torque value (unit N·m), clearance value (unit mm), coaxiality tolerance (unit μm), and other fields, with a core focus on component fit and assembly debugging results.

What constraints these characteristics impose on workflow orchestration

This category uses a multi-variety order-based assembly model, so data is updated individually for each device. Workflows must bind the variables parameter to adapt to the BOM and process requirements of different orders. Tasks such as verifying multi-level BOMs and physical stock availability, adjusting clearances and coaxiality take a long time. Workflows must reserve sufficient execution duration. The volume of assembly documents varies with order complexity, so workflows must support dynamic adjustment of node configurations for file parsing and data invocation. They must also cover closed-loop processing logic for abnormal scenarios such as missing or incorrect parts, and performance over limits.

How to configure settings

The following configurations are formulated based on the workflow logic of FastGPT v4.17.0.

Configuration ItemRecommended SettingRationale
variablesBind order number, torque threshold, clearance tolerance rangeAdapt to personalized assembly parameters and process requirements for each device
nodeIdSpecify unique identifiers for BOM verification and clearance debugging nodesQuickly locate abnormal execution links in the workflow
Single execution timeout600–1200 secondsCover the typical time required for multi-level BOM verification and assembly parameter debugging
Form trigger ruleStart only after all required fields are filledAvoid triggering workflow execution before input is complete
File upload node limitSingle file no larger than 100 MBMatch the typical size of documents such as assembly process cards and BOMs
External search tool call configurationBind dedicated search nodes, call the top 8 resultsRetrieve publicly referenced content related to equipment maintenance, focusing on core information

Three common misconfigurations

  • Workflow execution times out and returns an execution timeout error. This occurs because the timeout setting is not adjusted for the long-duration links of assembly BOM verification and clearance debugging, causing execution duration to exceed the preset threshold.
  • Calling the workflow API with file upload returns a file parsing failure. This occurs because allowed formats and size limits are not configured for the file upload node, making it unable to receive large-volume assembly documents.
  • The external search tool result call limit is not set, returning too many redundant search results. This occurs because a rule to call only the top 8 core matching results is not implemented.

How to confirm configurations are correct

  • Trigger the test workflow, input simulated order parameters, and verify that variables loads the BOM and process data for the corresponding order.
  • Upload a standard assembly process card, confirm that the file upload node receives it normally and returns valid parsed content.
  • Leave the required form fields blank, verify that the workflow cannot start, and confirm that the trigger rule is active.
  • Trigger the external search node, input a general equipment maintenance question, and confirm that valid reference results are returned.

The values provided are common starting points and should be evaluated against samples relevant to the specific deployment.