AI Agentic Workflow for Adaptive Torque Control in Assembly

Manual torque setup is a costly bottleneck in custom assembly, introducing errors, slowing changeovers, and compromising traceability. This workflow automates the programming of smart tools by ingesting the specific Bill of Materials (BOM) for each unit. It translates material specs and fastener requirements into precise torque-angle parameters, sent directly to connected tools via PLC or IIoT gateways. This eliminates manual data entry, prevents misapplied torque, and establishes a digital thread for compliance.

Implementation integrates with PLM for BOM data, MES for work order context, and smart tool controllers via OPC UA or proprietary APIs. The core orchestration, often built with LangGraph, manages the data flow, exception routing, and audit trail. Critical controls include pre-execution simulation in a digital twin, real-time data validation against tolerance bands, and mandatory human review gates for any out-of-spec result. This architecture reduces defect rates, accelerates line changeovers, and provides immutable quality records for regulated industries.

This workflow automates a critical quality bottleneck in custom manufacturing: ensuring the correct torque is applied to every unique fastener. It eliminates manual tool programming and paper-based traceability, directly reducing assembly errors, warranty claims, and compliance audit effort. The operational upside comes from first-pass yield improvement, elimination of manual data entry, and the ability to enforce precise specifications across thousands of product variants without slowing the line.

Implementation integrates a LangGraph-based orchestrator with PLM (e.g., Windchill), MES, and smart tool controllers. The orchestrator agent validates torque logic against material databases and historical yield before pushing parameters. Each fastener's angle-torque curve is logged to the MES and digital twin for full traceability. Out-of-spec results trigger immediate alerts in the CMMS and route to a quality engineer via ServiceNow, with all actions captured in an immutable audit trail for regulatory compliance.

Phase 1 establishes the core orchestration layer, integrating with the MES and PLM to ingest the custom BOM and material specifications. A LangGraph-based orchestrator agent interprets these inputs, queries historical torque-angle data, and dynamically generates the correct torque-angle profile for each fastener location. This profile is pushed to smart electric tools via an OPC UA or proprietary tool API, eliminating manual program lookup and entry errors. Concurrently, the architecture is instrumented to capture all torque-angle curves for traceability back to the serialized unit.

Phase 2 introduces real-time validation and exception handling. As the tool executes, the orchestrator ingests the live torque-angle curve, performs statistical process control (SPC) analysis, and compares it against the engineered spec. Any out-of-tolerance result automatically triggers an Andon alert at the station, halts the sequence, and routes a detailed non-conformance report with the failed curve to the CMMS for technician review. Phase 3 expands this into a predictive loop, using the aggregated historical data to recommend torque profile optimizations for new materials and flag tool calibration drift before it causes defects.

The rollout begins with a shadow mode, where the agentic system recommends torque values but a human technician approves and executes each setting via the smart tool interface. This phase validates the workflow's logic against the Bill of Materials (BOM) and material libraries without direct control, building confidence in the system's decision-making. Concurrently, a digital twin of the assembly cell ingests the same BOM data to simulate and log the expected torque-angle curves, creating a baseline for subsequent live-phase comparisons.

Upon validation, the system transitions to live control, where the agent directly programs the smart tool via the PLC. A critical governance control is the immediate line-stop and alert triggered by any out-of-spec torque-angle signature, which routes the incident to a designated quality engineer via the MES. This fail-safe, combined with comprehensive audit trails in the MES and QMS, ensures every fastener's torque is traceable to the specific product serial number, BOM revision, and agent decision rationale, providing the defensible record required for regulated industries like aerospace or medical devices.