Matrix Approach to Computing <scp>MTTF</scp> of a System

This paper proposes a new method to compute the mean time to failure (MTTF) of a system that can be expressed with a combinatorial model whose components fail with i. i. d. The key idea is to use a matrix approach that replaces every component reliability with a specific matrix and replaces every operation (addition, subtraction, multiplication, and division) with its corresponding matrix operation in the system reliability computation. We can determine all coefficients of the polynomial expressing the system reliability by replacing each component reliability with a special matrix and thereby easily compute the MTTF by taking the integral of this polynomial. We assume two assumptions, where the first is i. i. d. component failure and the second is that the computational complexity of integral of the j ‐th power of reliability of each component is polynomial order for any natural number j not more than the number of components (like when component fails with exponential distribution). We can compute the MTTF of the system with polynomial order complexity when we can compute the system reliability with polynomial order complexity, under the above two conditions. © 2026 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Authors

Institutions

Publication Details

Journal
IEEJ Transactions on Electrical and Electronic Engineering
Published
2026-08-13
DOI
https://doi.org/10.1002/tee.70408
Primary Topic
Radiation Effects in Electronics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Matrix Approach to Computing MTTF of a System

Masahiro Hayashi
IEEJ Transactions on Electrical and Electronic Engineering
Radiation Effects in Electronics
article

Matrix Approach to Computing MTTF of a System

Masahiro Hayashi
article en

Abstract

This paper proposes a new method to compute the mean time to failure (MTTF) of a system that can be expressed with a combinatorial model whose components fail with i. i. d. The key idea is to use a matrix approach that replaces every component reliability with a specific matrix and replaces every operation (addition, subtraction, multiplication, and division) with its corresponding matrix operation in the system reliability computation. We can determine all coefficients of the polynomial expressing the system reliability by replacing each component reliability with a special matrix and thereby easily compute the MTTF by taking the integral of this polynomial. We assume two assumptions, where the first is i. i. d. component failure and the second is that the computational complexity of integral of the j ‐th power of reliability of each component is polynomial order for any natural number j not more than the number of components (like when component fails with exponential distribution). We can compute the MTTF of the system with polynomial order complexity when we can compute the system reliability with polynomial order complexity, under the above two conditions. © 2026 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

IEEJ Transactions on Electrical and Electronic Engineering
Tokyo City University (JP)
Openalex Percentile: Top 18%
Radiation Effects in Electronics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Matrix Approach to Computing <scp>MTTF</scp> of a System — Masahiro Hayashi · IEEJ Transactions on Electrical and Electronic Engineering (2026) | TGRS Research Map | TGRS