Build duty cycle and stress distributions by lifecycle phase. Clickable matrix + exports.
Build step-stress profiles for HALT and derive HASS screens. Detection-first or duty-cycle driven.
Design physics-based burn-in strategies to screen early-life failures. Recommends stress conditions, duration, and acceleration factors tied to intended life and failure mechanisms.
Build a vibration mission profile, generate accelerated PSD test profiles, and derive fixture requirements with reliability demonstration sizing.
Apply MIL-style derating principles to electronic and mechanical components. Quantify derated margins, factors of safety, and thermal headroom, and generate compliance-ready summaries.
Quantify thermal acceleration using the Arrhenius model. Calculate acceleration factors, equivalent life, and test durations for accelerated life testing (ALT) and design margin assessment.
Fit 2-parameter Weibull models with FAIL and right-censored SUSP data. Overlay multiple datasets on Weibull probability paper and export beta, eta, B-life, and mission reliability metrics.
Estimate fatigue life driven by thermal cycling using the Coffin-Manson model. Ideal for solder joints, interconnects, and mechanically constrained assemblies exposed to cyclic strain.
Predict microelectronics lifetime using Black's equation. Evaluate current density, temperature sensitivity, activation energy, and MTTF for design trade-offs and technology comparisons.
Determine required sample size, allowable failures, or achieved reliability and confidence using binomial reliability-demonstration theory—aligned with common qualification and DV requirements.
Analyze air-moisture properties including relative humidity, wet-bulb temperature, and enthalpy. Useful for environmental testing, humidity stress analysis, and lab condition validation.
Build system-level Reliability Block Diagrams from a simple table, analyze Series/Parallel/Hybrid architectures, compute system reliability, and export diagrams and data for design reviews.
Estimate and update software reliability using Bayesian methods. Convert test results and failure data into predictive reliability metrics, MTTF, and release readiness insight.