Guides

Learn how to spot gradual measurement drift caused by instrument aging, fixture wear, or environmental changes using TofuPilot's trend and control charts.

Learn how to build a business case for hardware test automation and measure ROI using TofuPilot's yield, cycle time, and defect data.

Learn how to tag OpenHTF test runs with station, line, factory, and shift metadata, then compare first pass yield across production lines using TofuPilot.

Learn how to replace opinion-based test decisions with data-driven manufacturing quality control using TofuPilot's analytics platform.

Compare MIL, SIL, and HIL testing approaches with cost, speed, and fidelity tradeoffs, plus Python examples for hardware-in-the-loop validation with TofuPilot.

Learn how to build full observability into your hardware test operations using TofuPilot's dashboards, alerts, and analytics.

Learn how to build repeatable hardware test sequences using TofuPilot with OpenHTF and Python for structured, automated test orchestration.

Learn how to track test fixture health, calibration, and lifecycle using TofuPilot's station monitoring and measurement trending.

Learn how to manage separate test environments with environment variables, config files, and TofuPilot workspace separation.

Learn how to monitor hardware test operations in real time using TofuPilot's live dashboards, yield tracking, and instant failure alerts.

Learn how to automate sensor calibration workflows, track calibration certificates, and manage multi-point calibration data with TofuPilot.

Learn how to package, distribute, and deploy OpenHTF test scripts to production stations using virtual environments, PyInstaller, and version tracking.