bomgrinder

The reliability prediction tool for avionics designers with a deadline

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Generate compliant reliability predictions using MIL-HDBK-217F for your designs.

Generate ARP4761A compliant FMEA worksheets.

Generate a reliability prediction report in seconds for your design. Produces MIL-HDBK-217F (with notices 1 and 2) compliant reliability predictions using rules and defaults recommendations from ANSI VITA 51.1.

Export the reliability report in an ARP4761A compliant FMEA worksheet using FMD-91 failure models and get ready early for your Safety Analysis.

Get MTBF for your design in seconds
Prepare ARP4761A ready artifacts
Individual components Failure Rates
Excel and CSV smart import
Customizable environment and temperatures duty cycle
Parts stress method (using your design rules or individual customization per component)

Pricing

Online tool

$0

Evaluate your design in seconds with unlimited online reliability reports

Unlimited reliability prediction reports
MIL-HDBK-217F reliability models
No login needed

Certification Kit

$299

Generate ARP4761A ready templates and artifacts for your airworthiness certification lifecycle data

Desktop application with full Components Reliability Database
1 year free updates and erratums
ARP4761A compliant FMEA worksheet using FMD-91 failure models
Fully Customizable duty cycle and environment
ARP4561A ready templates and contributions for your plans and reports

Frequently Asked Questions

Why MIL-HDBK-217F?

MIL-HDBK-217F is the industry standard for reliability prediction in avionics. It provides a comprehensive methodology for calculating component and system reliability, widely accepted by certification authorities. Our tool implements the latest version with notices 1 and 2, ensuring your predictions meet current industry requirements.

Why FMD-91?

FMD-91 failure models are specifically designed for avionics applications and are recommended by ARP4761A for Safety Analysis. These models provide more accurate failure rate predictions for modern electronic components compared to older methodologies.

Why ARP4761A?

ARP4761A is the standard guide for conducting Safety Assessment of civil airborne systems and equipment. Our tool generates FMEA worksheets that are compliant with this standard, helping you prepare for certification while saving time on documentation.

Can I use bomgrinder for industries other than aerospace?

While bomgrinder is optimized for avionics applications, its core reliability prediction capabilities can be valuable for other industries. However, the FMEA worksheets and some methodologies are specifically tailored for aerospace certification. We recommend consulting with our team for non-aerospace applications.

How accurate are the reliability predictions?

Our predictions are based on industry-standard methodologies and component databases. The accuracy depends on the quality of input data and component information. We recommend using manufacturer datasheets and verified component information for the most accurate results.

What file formats do you support?

We support Excel and CSV file formats for BOM imports. Our tool can automatically recognize common column formats, or you can configure custom mappings for your specific BOM structure.

Featured Articles

Understanding MIL-HDBK-217F Part Stress Method

Learn how the part stress method works, its advantages, and how to apply it effectively in your reliability predictions.

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FMEA in ARP4761A: A Complete Guide

Everything you need to know about creating ARP4761A compliant FMEA worksheets for your safety analysis.

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FMD-91 vs. Other Failure Models

Compare FMD-91 with other failure models and understand why it's preferred for avionics applications.

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Best Practices for BOM Preparation

Tips and tricks for preparing your Bill of Materials for accurate reliability predictions.

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Reliability Prediction in Modern Avionics

How modern tools and methodologies are revolutionizing reliability prediction in avionics design.

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Understanding Component Stress Factors

A deep dive into component stress factors and their impact on reliability predictions.

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