January 16, 2012

Worst case analysis - PA-10

Demonstrate that the product operates properly in extreme conditions

A. Scope

The purpose of a worst case analysis of a system is to ensure that it will function correctly under the extreme operating conditions that are specified for it.

It provides the means of assessing the performance of the system when it is subjected to the simultaneous existence of the various environment and interface conditions, which are generally:

  • initial tolerance of its components,
  • predicted ageing of its components during its lifetime,
  • extreme operating temperatures,
  • total radiation dose accumulated during its lifetime,
  • extreme variation of its power supplies,
  • extreme variation of its input signals,
  • extreme variation of its output loads.


The worst case analysis is based on the RNC documens : "RNC-CNES-Q-HB-30-502 Analyse pire cas" and " RNC-ECSS-Q-HB-30-01 Worst case analysis"

B. Principles of preparation

The worst case analysis is performed during design, normally at the end of phase B.

For each parameter analysed, the worst case analysis consists in determining the variation domain of the parameter (minimum value, maximum value) when the variables on which it relies each change within their own variation domain.

The analysis therefore requires a knowledge of:

  • the relationship between the parameter and its variables,
  • the relationship between each variable and the environment and interface stimuli.


Using these basic relationships, several methods can be used to determine the minimum and maximum variations of the parameter analysed:

  • the extreme values method,
  • the Monte-Carlo method,
  • the quadratic method.


If, after combining the extreme values, the product still meets the specifications, the analysis is complete.

If not, the quadratic method (least squares) can be used to refine the analysis.

The Monte Carlo method is used to find out the static distribution of a parameter between its minimum and maximum values. This distribution is obtained numerically by randomly drawing variables on which the parameter depends (the distribution laws of the variables must therefore be known).

If, at the end of the analysis, the product does not meet the requirements, recommendations are sent to the design entity.


RisksOperational anomaly under extreme conditions
Worst case analysis


Activities / documentation

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