Accelerated Life Testing

Physics of acceleration, Arrhenius/Eyring/inverse-power/Coffin-Manson models, test planning, censoring, ALT analysis, and extrapolation validity.

Private cohorts & on-site
Format: 3-day (8:30 a.m.–4:30 p.m.)
Level: Advanced
Location: Scheduled on demand · on-site at your facility or a regional venue
Date(s): Not yet scheduled for open enrollment. Get notified when it is, or book it privately for your team.
Includes: Certificate of Completion · printed slide binder · take-home reference text

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Faculty

Faculty details for this seminar will be announced with the full schedule.

Fees

Early: $1,895 (payment 4+ weeks ahead)
Standard: $2,095 (check/ACH) · $2,165 (card)

Group discount: $200 off per attendee for 3+ from the same organization.

Also Available

  • Corporate on-site delivery at your facility
  • Private cohort sessions
  • Digital curriculum licensing

Seminar Overview

Products are warrantied for years and developed in months; accelerated life testing (ALT) is the engineering discipline that closes that gap. This seminar is built from the authoritative reliability reference for the field — the ReliaSoft Accelerated Life Testing (ALT) reference — the same corpus that reliability engineers and QuART/ALTA practitioners use for acceleration models, test planning, and life-data analysis. The teaching material is the reference mathematics and methodology itself, not vendor marketing: acceleration models are derived and worked, not recited.

The curriculum follows the ALT arc end-to-end. It opens with the physics of acceleration: Arrhenius (thermal activation), Eyring (temperature plus reaction-mechanism realism), inverse power law (non-thermal stress), and the Coffin-Manson relationship for thermal-cycling fatigue — including when each model is valid and how over-stress invalidates them by changing the failure mechanism. It then covers test planning: which stresses, how many levels, sample size, test duration, and the censoring schemes (Type I, Type II, randomly censored, failure-terminated) that real programs live with. The final day is data analysis: fitting life-stress distributions, quantifying uncertainty and confidence bounds, and the model-validity checks that separate a defensible life estimate from a curve fit.

Attendees leave able to design an ALT program for a real product: choose the acceleration model, compute required sample sizes and stress levels from specified confidence targets, analyze the resulting data with censored observations, and extrapolate use-level life with honest confidence statements — then reconcile the ALT result with field data and warranty experience.

Ideal Learner

  • Reliability and test engineers who must design or interpret accelerated life tests
  • Design and materials engineers converting qualification data into life and warranty estimates
  • Quality and warranty analysts reconciling lab ALT results with field return data
  • Program managers who own durability demonstrations and sign-off decisions
  • Automotive suppliers, electronics, medical device, industrial-equipment, and consumer-product manufacturers facing multi-year warranty obligations on short development cycles

Learning Objectives

  • Select the correct acceleration model for the dominant failure mechanism — Arrhenius, Eyring, inverse power law, Coffin-Manson — and defend its validity limits for the material system
  • Design an ALT test plan: stress types and levels, number of levels, sample allocation, and duration targets derived from specified reliability and confidence goals
  • Apply censoring schemes correctly (Type I, Type II, random/failure-terminated) and account for suspended observations in the analysis
  • Analyze accelerated life data: fit life-stress distributions, estimate model parameters, and construct confidence bounds on parameters and use-level life
  • Detect invalid extrapolation — mechanism shifts, over-stress artifacts, poor model fit — and combine ALT predictions with field and warranty data for a defensible life claim

Consulting Sessions

Seminar attendees can sign up for individual consulting sessions with the instructor. Sessions are free for registered attendees, first-come first-served — sign up when registering by calling 248-539-0473 or during the seminar.

Seminar Outline

  • Why acceleration works: stress-life relationships, activation energy, and the time-compression contract
  • The failure-mechanism invariant: accelerating time without changing the mechanism — and the over-stress trap that violates it
  • Usage-stress vs. time-stress acceleration; single-stress vs. multiple-stress models
  • The ReliaSoft ALT reference framework: reliability functions, life distributions, and stress transformations as the course's working toolkit
  • **Exercise 1: identify the dominant mechanism for three supplied failure modes and select/justify the acceleration model for each**
  • Arrhenius: the thermal-activation model, reaction rate, activation energy, and its life-stress relationship
  • Working the model: thermal ALT planning, level selection, and extrapolation to use temperature
  • Eyring: extending thermal acceleration with the quantum-mechanical basis and additional stress terms (voltage/humidity variants)
  • Model validity: glass transition and material phase effects, mechanism changes at high temperature, and honest limits of the extrapolation
  • **Worked example: high-temperature ALT of a plastic-housed electronic module — Arrhenius fit, activation energy, and the use-level life estimate**
  • Inverse power law: non-thermal stress (voltage, load, pressure) and its log-linear life-stress form
  • Coffin-Manson: thermal-cycling fatigue, plastic strain amplitude, and cycling-count life
  • Mechanical fatigue connections: S-N behavior, cumulative damage, and where Coffin-Manson meets material fatigue data
  • Choosing between models when multiple mechanisms coexist; interaction and combined-stress considerations
  • **Exercise 2: plan a thermal-cycling ALT for a plastic part using Coffin-Manson — cycle amplitude, count, and required test time from a target life**
  • Stress level selection: maximum stress limits, spread across levels, and the allocation tradeoff (more levels vs. more samples per level)
  • Sample size determination from confidence and precision requirements — worked with the reference methodology
  • Test duration estimation and stopping criteria; optimizing for information per unit test cost
  • Acceleration factor computation and its role in planning vs. its misuse as a marketing number
  • **Exercise 3: design a complete ALT plan (stresses, levels, samples, duration) to demonstrate a 10-year life at 95/90 confidence — and compute what it actually costs in test time**
  • Life data types: complete (uncensored) vs. censored (suspended) observations; right-censoring in test reality
  • Type I (time-terminated), Type II (failure-terminated), randomly censored data — mechanics and consequences for estimation
  • The reliability function R(t), failure distribution f(t), hazard function λ(t): the working vocabulary for all that follows
  • Life distributions in ALT: an affiliated engineering firmial, Weibull, lognormal — selection by mechanism and physics
  • **Exercise 4: given a censored dataset from a running test, compute rank-based nonparametric reliability estimates and discuss the censoring effects**
  • Fitting the life-stress model: parameter estimation from accelerated data, likelihood concepts for censored data
  • Confidence bounds: on model parameters, on reliability at use conditions, and on time-to-failure percentiles — and what each bound is for
  • Model-fit diagnostics: probability plots, likelihood ratio tests, and residual behavior as validity evidence
  • Uncertainty communication: the difference between "the model says" and "the data support" in a design review
  • **Worked example: full analysis of a two-temperature-level ALT dataset with suspensions — parameters, bounds, and the honest life statement**
  • Detecting mechanism change: curvature in the stress-life relationship, bimodal failure signatures, and the physics behind them
  • Over-stress artifacts: what high-stress data teaches about use-level behavior — and what it does not
  • Degradation-based ALT: when performance degradation (wear, drift, strength loss) is measurable before failure
  • Step-stress testing: concepts, models, and the cautionary boundaries of its use
  • **Exercise 5: given an ALT dataset whose fit degrades at the highest stress, diagnose the mechanism shift and re-derive the valid life estimate from the defensible data subset**
  • The reconciliation problem: ALT predictions vs. warranty returns vs. field failures — why they disagree and how to use the disagreement
  • Updating ALT models with field data; acceleration-factor calibration from early field exposure
  • Feeding ALT results into reliability growth, warranty reserve planning, and design-change decisions
  • Course capstone: attendees present their own ALT plan or dataset for instructor and peer critique
  • **Exercise 6: capstone — from a supplied field-return dataset plus ALT results, produce a reconciled life estimate and a warranty-reserve recommendation, and defend both**

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