Markov chain modelling of reliability analysis and prediction under mixed mode loading

Salvinder Singh, Shahrum Abdullah, Nik Abdullah Nik Mohamed, Mohd. Salmi Md. Noorani

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The reliability assessment for an automobile crankshaft provides an important understanding in dealing with the design life of the component in order to eliminate or reduce the likelihood of failure and safety risks. The failures of the crankshafts are considered as a catastrophic failure that leads towards a severe failure of the engine block and its other connecting subcomponents. The reliability of an automotive crankshaft under mixed mode loading using the Markov Chain Model is studied. The Markov Chain is modelled by using a two-state condition to represent the bending and torsion loads that would occur on the crankshaft. The automotive crankshaft represents a good case study of a component under mixed mode loading due to the rotating bending and torsion stresses. An estimation of the Weibull shape parameter is used to obtain the probability density function, cumulative distribution function, hazard and reliability rate functions, the bathtub curve and the mean time to failure. The various properties of the shape parameter is used to model the failure characteristic through the bathtub curve is shown. Likewise, an understanding of the patterns posed by the hazard rate onto the component can be used to improve the design and increase the life cycle based on the reliability and dependability of the component. The proposed reliability assessment provides an accurate, efficient, fast and cost effective reliability analysis in contrast to costly and lengthy experimental techniques.

Original languageEnglish
Pages (from-to)307-314
Number of pages8
JournalChinese Journal of Mechanical Engineering (English Edition)
Volume28
Issue number2
DOIs
Publication statusPublished - 12 Mar 2015

Fingerprint

Crankshafts
Reliability analysis
Markov processes
Torsional stress
Hazards
Probability density function
Automobiles
Distribution functions
Life cycle
Loads (forces)
Engines
Costs

Keywords

  • Failure
  • Markov Chain
  • Mixed mode
  • Reliability
  • Weibull

ASJC Scopus subject areas

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Cite this

Markov chain modelling of reliability analysis and prediction under mixed mode loading. / Singh, Salvinder; Abdullah, Shahrum; Nik Mohamed, Nik Abdullah; Md. Noorani, Mohd. Salmi.

In: Chinese Journal of Mechanical Engineering (English Edition), Vol. 28, No. 2, 12.03.2015, p. 307-314.

Research output: Contribution to journalArticle

@article{dd8939b8b36742a282bb523e9dae82d8,
title = "Markov chain modelling of reliability analysis and prediction under mixed mode loading",
abstract = "The reliability assessment for an automobile crankshaft provides an important understanding in dealing with the design life of the component in order to eliminate or reduce the likelihood of failure and safety risks. The failures of the crankshafts are considered as a catastrophic failure that leads towards a severe failure of the engine block and its other connecting subcomponents. The reliability of an automotive crankshaft under mixed mode loading using the Markov Chain Model is studied. The Markov Chain is modelled by using a two-state condition to represent the bending and torsion loads that would occur on the crankshaft. The automotive crankshaft represents a good case study of a component under mixed mode loading due to the rotating bending and torsion stresses. An estimation of the Weibull shape parameter is used to obtain the probability density function, cumulative distribution function, hazard and reliability rate functions, the bathtub curve and the mean time to failure. The various properties of the shape parameter is used to model the failure characteristic through the bathtub curve is shown. Likewise, an understanding of the patterns posed by the hazard rate onto the component can be used to improve the design and increase the life cycle based on the reliability and dependability of the component. The proposed reliability assessment provides an accurate, efficient, fast and cost effective reliability analysis in contrast to costly and lengthy experimental techniques.",
keywords = "Failure, Markov Chain, Mixed mode, Reliability, Weibull",
author = "Salvinder Singh and Shahrum Abdullah and {Nik Mohamed}, {Nik Abdullah} and {Md. Noorani}, {Mohd. Salmi}",
year = "2015",
month = "3",
day = "12",
doi = "10.3901/CJME.2015.0112.012",
language = "English",
volume = "28",
pages = "307--314",
journal = "Chinese Journal of Mechanical Engineering (English Edition)",
issn = "1000-9345",
publisher = "Chinese Mechanical Engineering Society",
number = "2",

}

TY - JOUR

T1 - Markov chain modelling of reliability analysis and prediction under mixed mode loading

AU - Singh, Salvinder

AU - Abdullah, Shahrum

AU - Nik Mohamed, Nik Abdullah

AU - Md. Noorani, Mohd. Salmi

PY - 2015/3/12

Y1 - 2015/3/12

N2 - The reliability assessment for an automobile crankshaft provides an important understanding in dealing with the design life of the component in order to eliminate or reduce the likelihood of failure and safety risks. The failures of the crankshafts are considered as a catastrophic failure that leads towards a severe failure of the engine block and its other connecting subcomponents. The reliability of an automotive crankshaft under mixed mode loading using the Markov Chain Model is studied. The Markov Chain is modelled by using a two-state condition to represent the bending and torsion loads that would occur on the crankshaft. The automotive crankshaft represents a good case study of a component under mixed mode loading due to the rotating bending and torsion stresses. An estimation of the Weibull shape parameter is used to obtain the probability density function, cumulative distribution function, hazard and reliability rate functions, the bathtub curve and the mean time to failure. The various properties of the shape parameter is used to model the failure characteristic through the bathtub curve is shown. Likewise, an understanding of the patterns posed by the hazard rate onto the component can be used to improve the design and increase the life cycle based on the reliability and dependability of the component. The proposed reliability assessment provides an accurate, efficient, fast and cost effective reliability analysis in contrast to costly and lengthy experimental techniques.

AB - The reliability assessment for an automobile crankshaft provides an important understanding in dealing with the design life of the component in order to eliminate or reduce the likelihood of failure and safety risks. The failures of the crankshafts are considered as a catastrophic failure that leads towards a severe failure of the engine block and its other connecting subcomponents. The reliability of an automotive crankshaft under mixed mode loading using the Markov Chain Model is studied. The Markov Chain is modelled by using a two-state condition to represent the bending and torsion loads that would occur on the crankshaft. The automotive crankshaft represents a good case study of a component under mixed mode loading due to the rotating bending and torsion stresses. An estimation of the Weibull shape parameter is used to obtain the probability density function, cumulative distribution function, hazard and reliability rate functions, the bathtub curve and the mean time to failure. The various properties of the shape parameter is used to model the failure characteristic through the bathtub curve is shown. Likewise, an understanding of the patterns posed by the hazard rate onto the component can be used to improve the design and increase the life cycle based on the reliability and dependability of the component. The proposed reliability assessment provides an accurate, efficient, fast and cost effective reliability analysis in contrast to costly and lengthy experimental techniques.

KW - Failure

KW - Markov Chain

KW - Mixed mode

KW - Reliability

KW - Weibull

UR - http://www.scopus.com/inward/record.url?scp=84924758792&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84924758792&partnerID=8YFLogxK

U2 - 10.3901/CJME.2015.0112.012

DO - 10.3901/CJME.2015.0112.012

M3 - Article

VL - 28

SP - 307

EP - 314

JO - Chinese Journal of Mechanical Engineering (English Edition)

JF - Chinese Journal of Mechanical Engineering (English Edition)

SN - 1000-9345

IS - 2

ER -