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Calculator Library / Reliability

Product Lifecycle Reliability Analysis

Analyze field, bench, or warranty life data with a 2-parameter Weibull model. Enter failure and censored observations, estimate lifecycle behavior, read B-life and mission reliability, and use the plots to judge whether the product is showing infant mortality, random failure, or wear-out behavior.

Lifecycle workspace

Organize the life data before fitting the model

Reliability core: fit β and η from failure and censored life data, then read mission reliability, percentile life, and failure pattern from the Weibull curves.

Recommended data structure

Use one row per unique observation pattern. Quantity lets one row stand in for repeated identical units. Interval rows let you approximate failure discovered between two inspections by fitting at the midpoint. Segment tags can represent product family, supplier lot, design revision, or reliability-growth phase.

Scenario management

Save, reload, or move full reliability models

Comparative scenario workspace

Compare saved reliability stories side by side

Select the current draft and any saved scenarios you want to compare. The first selected scenario becomes the delta baseline.

Select at least one valid scenario to compare reliability curves, B10 life, mission reliability, and warranty exposure.

Scenario Segment β η B10 Mission reliability Expected claims Warranty status Δ mission
Save or select scenarios to activate side-by-side comparison.

Life data

Failure and censored observations

# Start life End life Status Quantity Segment Unit / lot note Actions

Analysis plots

Weibull probability plot

Failed data Censored data Fitted Weibull

Decision planning

Warranty and maintenance planning

Planning summary

Run the analysis to estimate preventive-replacement timing, warranty exposure, and the life required to hit your target reliability.

Life at target reliability - Time required to hit the target survival probability.
Suggested replacement interval - Uses an early-action rule based on pattern and B-life timing.
Expected warranty claims - Estimated failures inside the warranty window for the entered fleet size.
Warranty plan status - Compares expected claims against the allowed-claims threshold.
Warranty-window survival - Estimated unit survival through the planned warranty window.
Recommended spare pool - Central and upper-bound replacement demand translated into spare coverage.
Inspection checkpoint - Recommended review point before the risk curve steepens materially.
Candidate interval Reliability Expected claims Claims range Hazard rate Status
Run the analysis to compare candidate warranty and replacement intervals.
The comparison table will show how reliability and expected claims change as you move the interval earlier or later.
Checkpoint Life Reliability Expected failures Suggested spares
Run the analysis to build a service-checkpoint plan.

Model validation

Fit and model comparison

Recommended model

Run the analysis to compare Weibull, lognormal, and exponential fits before relying on the life estimates.

Best fit model -
Probability plot quality -
Data quality warning level -
  • Warnings and model-quality notes will appear here after the analysis runs.

Interpretation guidance

Failure pattern framing

These guidance cards translate the fitted beta shape and mission reliability into a practical lifecycle story.

Infant mortality

Use this frame when the fitted beta is below 1. This usually points to screening, workmanship, startup defects, or early-life corrective actions.

Random failure zone

Use this frame when beta is near 1. This usually suggests exposure-driven failures, steady hazard, and operational spare-parts planning.

Wear-out pattern

Use this frame when beta is above 1. This usually points to replacement timing, service intervals, and design-life commitments.

Reliability growth tracking

Segment and phase progression

Tag rows with segments such as prototype, pilot, rev B, supplier lot, or launch phase to track whether reliability is improving or regressing.

Baseline segment - First valid segment with enough failures to fit a curve.
Latest segment - Most recent valid segment in the data-entry order.
Mission reliability delta - Difference between latest and baseline segment mission survival.
Segment Units Failures β η Mission reliability Δ vs baseline Data quality
Add segment labels to life-data rows to activate reliability growth tracking.

How this tool will work

Planned workflow

1

Enter the life data

Load failure and censored units, confirm time units, and establish the mission-time question.

2

Fit the Weibull model

Estimate shape and scale, then check the probability plot and fitted curves.

3

Read B-life and reliability

Review B10, characteristic life, mean life, and mission-time reliability.

4

Translate to action

Use the interpretation layer for warranty, maintenance, redesign, or screening decisions.