Automation Workflow for Legacy Machine Control via Agent Bridge

Hyper-personalized production demands rapid line changes, but legacy CNC mills, lathes, and PLC-controlled machines lack modern APIs, creating a critical automation bottleneck. Manually operating these machines for each custom variant destroys throughput and margin. A software agent bridge automates this by acting as a virtual operator, using secure remote desktop protocols to scrape screens, push buttons, and transfer files. This eliminates the need for expensive hardware upgrades or manual intervention, directly reducing changeover time and labor cost while unlocking legacy assets for flexible production.

Implementation requires deploying containerized agent instances with secure, audited access to each legacy machine's HMI. The agent executes deterministic sequences defined in the central orchestrator (e.g., LangGraph), handling retries and logging all actions for traceability. Critical controls include pre-job simulation in a digital twin, mandatory human-in-the-loop approval gates for any deviation, and integration with the MES for work order closure. This architecture turns a manual, error-prone process into a reliable, auditable component of a reconfigurable production line, protecting utilization for low-volume, high-value orders.

This workflow automates the direct control of legacy industrial machines by deploying a secure software agent that acts as a virtual operator. It bridges the gap between modern orchestration systems and machines that only accept commands via proprietary HMI screens or file transfers. The agent automates screen scraping, button pressing, and secure file transfers via protocols like RDP or VNC, translating high-level reconfiguration commands from a system like a Manufacturing Execution System (MES) into the precise, low-level interactions the legacy equipment requires. This eliminates the manual bottleneck of operators physically re-programming each machine during a line changeover, directly saving labor hours and reducing changeover time.

Implementation requires deploying containerized agent instances on secure edge hardware adjacent to each legacy machine, with strict network segmentation. The architecture integrates with the central orchestration layer (e.g., LangGraph) for command receipt and status reporting. Critical controls include checksum validation for transferred G-code or ladder logic files, screenshot-based confirmation of machine state changes, and comprehensive audit logging. Exception handling routes failures—like a missed button press or communication timeout—to a human engineer via a ticketing system like ServiceNow, ensuring no unsupervised action proceeds on faulty equipment. This creates a production-grade, auditable bridge that turns legacy assets into programmable endpoints.

Phase 1 establishes the foundational agent bridge, deploying secure remote desktop containers to interface with legacy HMIs. The agent automates screen scraping, button pressing, and file transfers via protocols like VNC or RDP, translating high-level commands from a central orchestrator into low-level machine control. This initial layer unlocks basic integration, allowing legacy assets to receive job files and status commands, directly automating the manual upload and start sequences that bottleneck changeovers in low-volume runs.

Phase 2 layers on robust control logic and exception handling, implementing a state machine to manage machine readiness, job execution, and fault recovery. The agent monitors for HMI error pop-ups or stalled processes, routing exceptions to a human review queue in tools like ServiceNow. Phase 3 integrates the bridged machine into the broader production orchestration, syncing job status with the MES (e.g., SAP ME) and updating the line's digital twin. This final stage enables closed-loop OEE tracking and allows the legacy asset to participate in dynamic, agent-driven reconfiguration sequences for mixed-model production.

The operational bottleneck is clear: legacy machines with proprietary HMIs and no APIs cannot participate in automated reconfiguration sequences, forcing manual intervention that destroys line agility and adds 15-30 minutes of non-productive time per changeover. This workflow automates screen scraping, button pressing, and file transfer via secure remote desktop protocols (e.g., VNC, RDP) using a headless browser agent. The agent acts as a deterministic software operator, executing predefined sequences to load programs, start cycles, and read statuses, effectively giving a 1990s machine a modern API layer. The savings come from eliminating manual machine babysitting, reducing changeover errors, and unlocking the machine's capacity for mixed-model production.

Implementation requires deploying containerized agent instances on edge hardware adjacent to each legacy machine, with sequences defined in a state machine (e.g., LangGraph) that maps reconfiguration commands to specific HMI interactions. Critical controls include digital twin simulation to validate agent sequences offline, a human-in-the-loop approval gate for first-time execution of a new sequence, and comprehensive audit logging of all agent actions for traceability and compliance. Rollout must be phased, starting with non-critical machines, and include rigorous validation against physical safety interlocks to prevent the agent from issuing unsafe commands. This architecture turns a capex-heavy hardware upgrade problem into a scalable software integration challenge.

This workflow directly addresses the operational bottleneck of integrating non-networked, API-less machines into automated production lines. It eliminates the manual labor of screen monitoring, button pressing, and file transfers, which are major time sinks during rapid changeovers for custom orders. The business value comes from slashing changeover downtime, protecting overall equipment effectiveness (OEE), and enabling the inclusion of high-value legacy assets in hyper-personalized manufacturing without capital-intensive retrofits. The agent acts as a secure, programmable intermediary between the orchestration layer and the machine's human-machine interface (HMI).

Implementation requires deploying the bridge agent on a secure, network-accessible industrial PC adjacent to each legacy machine. The agent is programmed with machine-specific navigation logic, screen recognition templates, and secure credential management for RDP or VNC protocols. It receives JSON payloads from a central orchestrator (e.g., LangGraph) detailing the required machine state, program file, and validation checks. Critical controls include exception routing to a human review queue via Slack or Teams, comprehensive audit logging of all virtual interactions, and a heartbeat monitor to ensure agent availability. This architecture creates a durable, software-only integration layer for legacy control.