Comprehensive Evaluation of the Leaf spring Manufacturing station: Assessing Efficiency and Reliability

Authors

  • Anil Kumar Department of Mathematics, Brahmanand College Kanpur, India
  • A. kumar Department of Mathematics, Brahmanand College Kanpur, India

DOI:

https://doi.org/10.63671/ijsesr.v2i2.115

Keywords:

modelling, Markov Birth-Death process, the Chapman-Kolmogorov differential equations, availability analysis, Runge-Kutta Method

Abstract

An essential and crucial component of the suspension system is the leaf spring. Finding an ideal design that works well under a range of loading circumstances is the aim of this   investigation. This study offers a thorough availability and performance modelling evaluation of the leaf spring production sector, emphasizing the identification of crucial subsystems, the assessment of failure behaviours, and the measurement of their effect on total productivity. Here, we look at three different component conditions: fine, diminished, and crashed. The breakdown and maintenance rates of each component are assumed to be fixed and substantially separate. The system was analytically formulated using the Markov Birth-Death method. To compute the stable state probability, the Chapman-Kolmogorov differential equations were established based on the system's state-transition relationships, considering a spectrum of failure and repair rates.  Decision matrices are derived from different performance levels in terms of availability. The model's practical application is illustrated by numerical findings and case studies, which provide insights into scheduling preventative maintenance, improving production reliability, and allocating resources optimally. Therefore, the results of this study are considered to be helpful in analyzing availability and identifying the best maintenance techniques that may be used going forward to improve system performance.

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Published

2026-06-13

Issue

Section

Articles

How to Cite

Kumar, A., & kumar, A. (2026). Comprehensive Evaluation of the Leaf spring Manufacturing station: Assessing Efficiency and Reliability. International Journal of Science and Engineering Science Research, 2(2), 09-24. https://doi.org/10.63671/ijsesr.v2i2.115

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