Monitoring reliability of man-machine system of machining area using the Weibull distribution
DOI:
https://doi.org/10.37636/recit.v7n1e324Keywords:
Reliability, Machine-human, Weibull distribution, Exponential distributionAbstract
This publication presents the development of a method that seeks to monitor the parameters β (shape) and η (scale) for each component-subsystem combination following the Weibull distribution, necessary for the calculation of the reliability of the man-machine system in the machining area. This system defines the workshops of the metal-mechanic, with high-mix and low-volume batch production where conventional and Computerized Numerical Control (CNC) machines are involved, which share the manufacturing of parts that sometimes are unique, or their manufacturing period is short. The design of the man-machine system is based on the analysis of the failures of non-conforming parts in the machining area and on the failure rates, which the statistical model is developed for its evaluation, considering the 2-parameter Weibull distribution, and a redundant system with series-parallel configuration. The results obtained were based on the theoretical-practical, using mathematical and statistical models, as well as the Study Case. With the use of mathematical and statistical models, it is demonstrated that the probability of failure (risk) of the man-machine system is time-dependent and is generated by mechanical type stresses, which occur in the manufacture of parts.
Downloads
Metrics
References
D. Morin, "The Hamiltonian method," Introduction to Classical Mechanics, With Problems and Solutions, no. October, 2008.
J. C. Pardo, "A brief introduction to self-similar processes," Department of Mathematical Sciences, University of …, vol. 1, no. d, pp. 1-20, 2007.
M. Baro-Tijerina, M. Piña-monarrez, and B. Villa-covarrubias, "Weibull Stress / Strength Analysis with Non-Constant Shape Parameter," 2017, pp. 1-6.
R. L. Anjum and S. Mumford, Powers, Probability and Statistics, vol. 417. 2020. https://doi.org/10.1007/978-3-030-28722-1_8 DOI: https://doi.org/10.1007/978-3-030-28722-1_8
M. R. Piña-Monarrez, "Weibull stress distribution for static mechanical stress and its stress/strength analysis," Qual Reliab Eng Int, vol. 34, no. 2, pp. 229-244, 2018, https://doi.org/10.1002/qre.2251 DOI: https://doi.org/10.1002/qre.2251
M. W. Fu and J. L. Wang, "Size effects in multi-scale materials processing and manufacturing," Int J Mach Tools Manuf, vol. 167, no. May, 2021, https://doi.org/10.1016/j.ijmachtools.2021.103755 DOI: https://doi.org/10.1016/j.ijmachtools.2021.103755
I. Gödri, "Improving Delivery Performance in High-Mix Low-Volume Manufacturing by Model-Based and Data-Driven Methods," Applied Sciences (Switzerland), vol. 12, no. 11, 2022, https://doi.org/10.3390/app12115618 DOI: https://doi.org/10.3390/app12115618
E. Zio, "Some Challenges and Opportunities in Reliability Engineering To cite this version: HAL Id: hal-01550063," IEEE transactions on Reliability, vol. 65, no. 4, pp. 1749-1782, 2016. https://doi.org/10.1109/TR.2016.2591504 DOI: https://doi.org/10.1109/TR.2016.2591504
Z. S. Yea and M. Xie, "Stochastic modeling and analysis of degradation for highly reliable products," Appl Stoch Models Bus Ind, vol. 31, no. 1, pp. 16-32, 2015, https://doi.org/10.1002/asmb.2063 DOI: https://doi.org/10.1002/asmb.2063
R. M. Amaya-Toral et al., "Human-Machine Systems Reliability: A Series-Parallel Approach for Evaluation and Improvement in the Field of Machine Tools," Applied Sciences (Switzerland), vol. 12, no. 3, 2022, https://doi.org/10.3390/app12031681 DOI: https://doi.org/10.3390/app12031681
L. Rainie and J. Anderson, "The Future of Jobs and Jobs Training," Pew Research Center, no. May, pp. 1-95, 2017.
H. Pham, Handbook of Engineering Statistics Springer Handbook of Engineering Statistics, vol. 21, no. 4. 1956.
P. Baredar, V. Khare, and S. Nema, "Reliability assessment of biogas power plant," in Design and Optimization of Biogas Energy Systems, 2020, pp. 187-229. https://doi.org/10.1016/B978-0-12-822718-3.00005-8 DOI: https://doi.org/10.1016/B978-0-12-822718-3.00005-8
Erich Gamma, Design Pattersns. 2006. https://doi.org/10.1007/978-1-4302-0096-3_10 DOI: https://doi.org/10.1007/978-1-4302-0096-3_10
P. Vassiliou and A. Mettas, "Understanding accelerated life-testing analysis," Annual Reliability and Maintainability Symposium, Tutorial Notes, pp. 1-21, 2001.
B. Yaniktepe, O. Kara, I. Aladag, and C. Ozturk, "Comparison of eight methods of Weibull distribution for determining the best-fit distribution parameters with wind data measured from the met-mast," Environmental Science and Pollution Research, pp. 0-18, 2022, DOI: https://doi.org/10.21203/rs.3.rs-1185242/v1
https://doi.org/10.1007/s11356-022-22777-4 DOI: https://doi.org/10.1007/s11356-022-22777-4
J. Brier and lia dwi jayanti, Research Methodology, vol. 21, no. 1. 2020.
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2023 Rosa María Amaya Toral, Manuel Baro Tijerina, Martha Patricia García-Martínez, Cinthia Judith Valdiviezo Castillo
This work is licensed under a Creative Commons Attribution 4.0 International License.
The authors who publish in this journal accept the following conditions:
The authors retain the copyright and assign to the journal the right of the first publication, with the work registered with the Creative Commons Attribution license 4.0, which allows third parties to use what is published as long as they mention the authorship of the work and the first publication in this magazine.
Authors may make other independent and additional contractual agreements for the non-exclusive distribution of the version of the article published in this journal (eg, include it in an institutional repository or publish it in a book) as long as they clearly indicate that the work it was first published in this magazine.
Authors are allowed and encouraged to share their work online (for example: in institutional repositories or personal web pages) before and during the manuscript submission process, as it can lead to productive exchanges, greater and more quick citation of published work (see The Effect of Open Access).
