Defense company uses BQR software for calculating the probabilities of safety events

 

Introduction

A manufacturer of explosive devices used BQR software to calculate the probabilities of premature detonation in the various product mission phases, to show compliance with the client safety requirements (probability was required to be smaller than 5‧10^-8).
Explosive devices have mechanical, electrical, and electronic protections. Severe safety events may result from combinations of protection failures.

 

Analysis Steps:

MTBF Prediction

Use MTBF prediction software to calculate component failure rates according to MIL HDBK 217F2 and NSWC standards

FMEA

• Import MTBF data to BQR Failure Mode, Effects and Criticality Analysis (FMECA) software, and automatically assign component level failure modes
• Conduct FMECA analysis
  • Select the standard to work by (the risk matrix, severities list, and criticality or probability groups are automatically defined according to each standard)
  • Define effects of component failures on the higher level assemblies, up to the system level
  • Define severities of system level failure modes
• Automatically calculate and generate FMECA reports, showing the number of failure modes in each severity and risk level

By definition, FMECA analyzes the effect of each single failure mode on the system.

Critical systems often include safety measures and redundancies; therefore, severe safety events only occur as a result of combined failure modes. Fault Tree Analysis (FTA) is the method for calculating the probability of failure combinations leading to the safety event.

The FMECA project is imported to BQR FTA module as a basis for the Fault Tree Analysis

Fault Tree Analysis

Conduct FTA analysis:

• Assign top safety event
• Define logical relations (gates) between relevant failure modes, deleting non-relevant failure modes (Top-Down process)
• Add “external” events such as probabilities of severe weather and operator error
• Automatically calculate probability of the top event, leading causes, and event combinations

Results

Probability of safety events was found to be in compliance with the client requirements.
Main drivers for the safety event were identified. It was found that mechanical failures have a much higher probability compared to electronic failures, therefore future products will focus on mechanical reliability.
Finally, the project files were easily updated to analyze the safety of product variants.