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Hazard Rate01:11

Hazard Rate

The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
Determination of Expected Frequency01:08

Determination of Expected Frequency

Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
Design Consideration01:22

Design Consideration

Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key aspect...
Fatigue01:21

Fatigue

Fatigue occurs when materials rupture under repeated or fluctuating loads, even at stress levels far below their static breaking strength. It typically results in brittle failure, even for ductile materials. It is a critical consideration in designing machines and structural components subjected to repetitive or varying loads. The nature of these loadings can range from fluctuating loads like unbalanced pump impellers causing vibrations to repeatedly bending a thin steel rod wire back and forth...

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Related Experiment Video

Updated: Jul 17, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Reliability calculation under seasonally varying failure rate.

Yuri A Ermolin1

  • 1Moscow State University of Communication Means (MIIT), Obraztsov Street 15, Moscow, 127994, Russia. karmapa@ipc.ru

ISA Transactions
|February 13, 2007
PubMed
Summary

This study introduces a method to simplify complex reliability problems by approximating a time-varying failure rate with a constant equivalent. This approach enables easier analytical solutions for engineering applications.

Related Experiment Videos

Last Updated: Jul 17, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Area of Science:

  • Reliability Engineering
  • Mathematical Modeling
  • Time-Series Analysis

Background:

  • Reliability analysis often involves complex, time-dependent failure rates.
  • Periodic piecewise constant failure rates present analytical challenges.
  • Existing methods may lack convenient analytical solutions for non-stationary systems.

Purpose of the Study:

  • To develop an analytical method for solving reliability problems with periodic piecewise constant failure rates.
  • To propose a technique for substituting a non-stationary failure rate with a stationary equivalent.
  • To derive a formula for calculating this fictitious equivalent stationary failure rate.

Main Methods:

  • Analytical solution of reliability problems.
  • Approximation of non-stationary failure rates using a stationary equivalent.
  • Derivation of a formula for the equivalent stationary failure rate.
  • Demonstration using a simplistic example.

Main Results:

  • A formula for calculating the fictitious equivalent stationary failure rate has been derived.
  • The proposed method allows for approximate analytical solutions to reliability problems.
  • The approach is convenient for engineering applications and further analysis.
  • A simplified example validates the effectiveness of the method.

Conclusions:

  • The substitution of a periodic piecewise constant failure rate with an equivalent stationary one simplifies reliability analysis.
  • The derived formula provides a practical tool for engineers.
  • This method facilitates approximate analytical solutions, enhancing the applicability of reliability engineering.