Vacrms2

Vacrms2 is a modular software framework for data acquisition, control, and remote monitoring of vacuum-based scientific instruments and manufacturing equipment. It provides a unified interface to collect sensor data, issue control commands, and orchestrate experiments across heterogeneous hardware, enabling consistent operation of vacuum systems, gauges, pumps, valves, and analytical instruments.

The project grew from the earlier Vacrms family used in university and industry labs. The first public release of Vacrms2 established a plugin-based core around 2019, with subsequent major revisions that broadened hardware support, added scripting, and improved scalability.

The Vacrms2 core consists of a lightweight engine, a plugin manager, and a transport layer. It supports adapters for hardware via serial, USB, Ethernet, or fieldbuses; the data model uses timestamped events and measurements; and a scripting API (Python) enables custom experiments and automation. A modular transport stack includes MQTT, WebSocket, and local inter-process communication options. Security features include authentication, access control, and audit logging. Time synchronization relies on NTP or PTP.

The core is designed to be hardware-agnostic; driver adapters implement instruments such as vacuum gauges, vacuum pumps, valves, mass spectrometers, and residual gas analyzers.

Key features include real-time streaming and recording, event-driven control, rule-based automation, scenario templates, versioned configurations, offline and simulation modes, and a web-based dashboard for monitoring.

Licensing and development: Vacrms2 is released under the MIT license and hosted on public repositories; contributions are coordinated through version control and an open governance model.

Applications and impact: Widely used in academic labs and small to mid-sized manufacturing facilities; supports vacuum deposition, surface science experiments, thin-film characterization, and educational demonstrations.

Reception and limitations: Noted for flexibility and extensibility, but has a learning curve and dependency management challenges in very large deployments.