Bid Documentation and Quotation Preparation for Process Changes and Engineering Changes: Workflow Orchestration

Data sources for this category include PLM, ERP, MES, supplier materials, validation tests, and customer-specific requirements. Update frequency is

This page is written based on the workflow configuration specifications for FastGPT v4.17.0.

What this category of data looks like

Data sources for this category include PLM, ERP, MES, supplier materials, validation tests, and customer-specific requirements. Update frequency is irregular, triggered by each change. Daily documents cover ECN/ECR, change assessment forms, drawings and BOM version files, process validation reports, transition plans, inventory disposal documents, and customer approval documents. Data fields include change number, version number, effective date, material code, process parameters, customer approval document number, and others. Some fields must match the format specifications of corresponding systems. There are no universal standard units.

What constraints these characteristics impose on workflow orchestration

Multi-source data access requires workflows to support cross-system node configuration. This ensures drawings can be pulled from PLM and BOM data can be pulled from ERP. Irregular data updates require workflows to use trigger-based execution. This avoids redundant data or delays caused by scheduled pulls. Complex document structures require workflows to support multiple attachment associations and version verification nodes. This ensures change documents used in bid documentation are the latest valid versions. Multi-field format requirements require configuration of parameter verification nodes. This filters non-compliant input data. Severe error consequences require workflows to include multi-level approval and rollback nodes. This prevents unvalidated changes from entering production links.

How to set configurations

Configuration ItemRecommended ApproachRationale
Global variable isolationIsolate by user IDMatches multi-member collaboration scenarios for change teams, prevents conflicts from duplicate variable names
Context loading nodeBind historical session variablesSupports calling ECN and BOM historical data from past changes
Custom prompt nodePre-set 800–1200 character promptsAdapts to format requirements for different bid documentation scenarios
Timeout threshold1200 secondsAdapts to time requirements for pulling data from multiple systems
nodeId mappingBind dedicated node IDs for PLM/ERPAccurately pulls change-related data from corresponding systems
Maximum attachment upload size1000 MBAdapts to storage requirements for large drawings and process validation reports
Number of associated documents per single runFirst 5 entriesPrevents workflow nodes from loading too much data and causing lag

Three common configuration errors

  • Context does not take effect when calling APIs. Workflow nodes return empty historical change data. The cause is failure to correctly bind the variables parameter to the context loading node.
  • Global variable scope is confused. Change data from different users overwrites each other. The cause is failure to enable the global variable isolation configuration by user ID.
  • Custom prompts do not take effect. Output content uses the system default "you might ask" prompts. The cause is failure to add a custom prompt configuration node after the AI reply node.

How to verify correct configuration

  • A change process is initiated, triggered using different user accounts, and global variables are checked to confirm no mutual interference.
  • The workflow is triggered, and confirmation is made that corresponding ECN and BOM data can be pulled from bound PLM and ERP nodes, and that field formats meet requirements.
  • Workflow operation logs are reviewed to confirm no timeout exceptions are triggered.
  • The custom prompt node is tested, and confirmation is made that output content matches pre-set change scenario prompts.

The values provided here are common starting points, and should be evaluated against the samples used in the target deployment.