María Magdalena Hernández Ramos

Universidad Autónoma de Ciudad Juárez

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Universidad Autónoma de Ciudad Juárez

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María Magdalena Hernández Ramos has a total of 10 co-authors. Here are the top co-authors by number of shared publications:

Manuel Roman Piña Monarrez
Industrial and Manufacturing Department, Engineering and Technological Institute, Universidad Autónoma de Ciudad Juárez, Ciudad Juárez 32310, Chihuahua, Mexico
8 shared publications
Osvaldo Monclova-Quintana
School of Engineering and Sciences, Tecnologico de Monterrey, Ciudad Juarez Campus, Ciudad Juarez 32470, Chihuahua, Mexico
7 shared publications
Jesús Manuel Barraza Contreras
Industrial and Manufacturing Department, Engineering and Technological Institute, Universidad Autónoma de Ciudad Juárez, Ciudad Juárez 32310, Chihuahua, Mexico
5 shared publications
Jesús F. Ortiz-Yáñez
Reliability Engineering Lab, TED DE MEXICO SA DE CV, Ciudad Juárez 32470, Mexico
2 shared publications
Secundino Ramos-Lozano
Industrial and Manufacturing Department, Engineering and Technological Institute, Universidad Autónoma de Ciudad Juárez, Chihuahua 32310, Mexico
2 shared publications
Baldomero Villa-Covarrubias
Engineering and Technological Institute, Universidad Autonoma de Ciudad Juarez, Ciudad Juarez 32540, Chihuahua, Mexico
1 shared publication

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Open Access
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- 9 November 2026
- Published by MDPI AG in Vibration
Weibull Stress/Strength Method to Random Vibration by Considering the Cumulative Damage
by María Magdalena Hernández-Ramos, Manuel Román Piña-Monarrez, Osvaldo Monclova-Quintana, Jesús Manuel Barraza-Contreras
The paper presents a methodology to determine the reliability of a mechanical element directly from the accumulated vibration damage. To make damage representative, the time, geometry, load and resonance effects were all incorporated into the analysis through a simulation. And since vibration is a variant stress, then the element’s reliability was determined by using a common shape parameter of the Weibull stress and Weibull strength distributions. The formulas to estimate the stress Weibull parameters from the vibration stress values, and the formulas to determine the strength Weibull parameters by considering the material fatigue factor and the vibration testing profile are both given. Then the common Weibull shape parameter and the accumulated damage were used to determine the element reliability. From the application, the element’s reliability occurred in the first row, and the expected reliability of 97% occurred in the seventh row of the accumulated damage table. Also, the reliability index of each accumulated damage row is provided.
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- 9 November 2026
- Published by MDPI AG in Vibration
Open Access
Weibull Stress/Strength Method to Random Vibration by Considering the Cumulative Damage
by María Magdalena Hernández-Ramos, Manuel Román Piña-Monarrez, Osvaldo Monclova-Quintana, Jesús Manuel Barraza-Contreras
The paper presents a methodology to determine the reliability of a mechanical element directly from the accumulated vibration damage. To make damage representative, the time, geometry, load and resonance effects were all incorporated into the analysis through a simulation. And since vibration is a variant stress, then the element’s reliability was determined by using a common shape parameter of the Weibull stress and Weibull strength distributions. The formulas to estimate the stress Weibull parameters from the vibration stress values, and the formulas to determine the strength Weibull parameters by considering the material fatigue factor and the vibration testing profile are both given. Then the common Weibull shape parameter and the accumulated damage were used to determine the element reliability. From the application, the element’s reliability occurred in the first row, and the expected reliability of 97% occurred in the seventh row of the accumulated damage table. Also, the reliability index of each accumulated damage row is provided.
Open Access
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Google Scholar
- 2 June 2026
- Published by MDPI AG in Applied Sciences
Determination of a Ball Bearing’s Strength at the Lower L₁₀ Life Limit and Its 1, 2 and 3 Sigma Percentiles
by Osvaldo Monclova-Quintana, Manuel Román Piña-Monarrez, María Magdalena Hernández-Ramos, Baldomero Villa-Covarrubias
In this paper, based on the Hertzian contact analysis, we determine the minimum dynamic load of a ball bearing using a Weibull probabilistic approach. The lower L₁₀ life limit was determined considering a confidence interval, the sample size that corresponds to the L₁₀ life (90% reliability), and the standard deviation of the related Weibull scale parameter η. Then, we determine a functional relationship between the normal and the Weibull distributions to determine the corresponding $1 σ$ , $2 σ$ , and $3 σ$ Six Sigma indices of the ball-bearing life. Finally, a standard method was established to determine the minimum dynamic load rating required for a ball bearing in such a way that it achieves 90% reliability at the lower bound of its $L_{10}$ life. In the case study, the SKF 6009 ball bearing was initially selected, with a dynamic load rating of 22.1 kN, exhibiting a lower bound reliability of 0.86 under a nominal Weibull scale parameter of strength of 910 MPa. After applying the proposed analysis, it was replaced with the SKF 71909 ball bearing, which provides a nominal Weibull scale parameter strength of 1174.54 MPa, which ensures 90% reliability at the lower bound of its L₁₀ life. Its reliability indices at the $1 σ$ , $2 σ$ , and $3 σ$ Six Sigma levels were $R (t) = 0.9174$ , $R (t) = 0.8880$ , and $R (t) = 0.8534$ , respectively.
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- 2 June 2026
- Published by MDPI AG in Applied Sciences
Open Access
Determination of a Ball Bearing’s Strength at the Lower L₁₀ Life Limit and Its 1, 2 and 3 Sigma Percentiles
by Osvaldo Monclova-Quintana, Manuel Román Piña-Monarrez, María Magdalena Hernández-Ramos, Baldomero Villa-Covarrubias
In this paper, based on the Hertzian contact analysis, we determine the minimum dynamic load of a ball bearing using a Weibull probabilistic approach. The lower L₁₀ life limit was determined considering a confidence interval, the sample size that corresponds to the L₁₀ life (90% reliability), and the standard deviation of the related Weibull scale parameter η. Then, we determine a functional relationship between the normal and the Weibull distributions to determine the corresponding $1 σ$ , $2 σ$ , and $3 σ$ Six Sigma indices of the ball-bearing life. Finally, a standard method was established to determine the minimum dynamic load rating required for a ball bearing in such a way that it achieves 90% reliability at the lower bound of its $L_{10}$ life. In the case study, the SKF 6009 ball bearing was initially selected, with a dynamic load rating of 22.1 kN, exhibiting a lower bound reliability of 0.86 under a nominal Weibull scale parameter of strength of 910 MPa. After applying the proposed analysis, it was replaced with the SKF 71909 ball bearing, which provides a nominal Weibull scale parameter strength of 1174.54 MPa, which ensures 90% reliability at the lower bound of its L₁₀ life. Its reliability indices at the $1 σ$ , $2 σ$ , and $3 σ$ Six Sigma levels were $R (t) = 0.9174$ , $R (t) = 0.8880$ , and $R (t) = 0.8534$ , respectively.
Open Access
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Cited by 1
- 12 August 2025
- Published by MDPI AG in Vibration
Weibull Reliability Based on Random Vibration Performance for Fiber Optic Connectors
by Jesús M. Barraza-Contreras, Manuel R. Piña-Monárrez, María M. Hernández-Ramos, Secundino Ramos-Lozano
Communication via optical fiber is increasingly being used in harsh applications where environmental vibration is present. This study involves a Weibull reliability analysis focused on the performance of fiber optic connectors when they are subjected to mechanical random vibration stress to simulate real-world operating conditions, and the insertion loss (IL) degradation is measurable. By analyzing the testing times and stress levels, the Weibull shape ( $β$ ) and scale ( $η$ ) parameters are estimated directly from the maximal and minimal principal IL stresses ( $σ_{1}$ , $σ_{2}$ ), enabling the prediction of the connector’s reliability with efficiency. The sample size n is derived from the desired reliability (R(t)), and the GR-326 mechanical vibration test (2.306 Grms for six hours) is performed on optical SC angled physical contact (PC) polish fiber endface connectors that are monitored during testing to evaluate the IL transient change in the optical transmission. The method is verified by an experiment performed with $σ_{1} = 0.3960$ and $σ_{2} = 0.1910$ where the IL measurements are captured with an Agilent N7745A source-detector optical equipment, and the Weibull statistical results provide a connector’s reliability R(t) = 0.8474, with a characteristic value of $η$ = 0.2750 dB and $β$ = 3. Finally, the connector’s reliability is as worthy of attention as the telecommunication sign conditions.
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- 12 August 2025
- Published by MDPI AG in Vibration
Open Access
Weibull Reliability Based on Random Vibration Performance for Fiber Optic Connectors
by Jesús M. Barraza-Contreras, Manuel R. Piña-Monárrez, María M. Hernández-Ramos, Secundino Ramos-Lozano
Communication via optical fiber is increasingly being used in harsh applications where environmental vibration is present. This study involves a Weibull reliability analysis focused on the performance of fiber optic connectors when they are subjected to mechanical random vibration stress to simulate real-world operating conditions, and the insertion loss (IL) degradation is measurable. By analyzing the testing times and stress levels, the Weibull shape ( $β$ ) and scale ( $η$ ) parameters are estimated directly from the maximal and minimal principal IL stresses ( $σ_{1}$ , $σ_{2}$ ), enabling the prediction of the connector’s reliability with efficiency. The sample size n is derived from the desired reliability (R(t)), and the GR-326 mechanical vibration test (2.306 Grms for six hours) is performed on optical SC angled physical contact (PC) polish fiber endface connectors that are monitored during testing to evaluate the IL transient change in the optical transmission. The method is verified by an experiment performed with $σ_{1} = 0.3960$ and $σ_{2} = 0.1910$ where the IL measurements are captured with an Agilent N7745A source-detector optical equipment, and the Weibull statistical results provide a connector’s reliability R(t) = 0.8474, with a characteristic value of $η$ = 0.2750 dB and $β$ = 3. Finally, the connector’s reliability is as worthy of attention as the telecommunication sign conditions.
Cited by 1
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Cited by 2
- 21 February 2025
- Published by Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne in Eksploatacja i Niezawodność – Maintenance and Reliability
Weibull Reliability Methodology based on Cumulated Vibration Damage
by María Magdalena Hernández Ramos, Manuel Román Piña Monarrez, Jesús Manuel Barraza Contreras, Osvaldo Monclova Quintanaz
In the paper, the formulated Weibull vibration reliability methodology is based on the cumulative vibration damage analysis. It lets us determine the reliability index of each damage element, each damage block, and the reliability of the analyzed element. The vibration cumulated damage is cumulated until D=1, by using the addressed vibration stress and a nonlinear cumulative damage model. Based on static and modal analysis, the vibration stress is determined by incorporating to it the geometry, weight and resonance effects. In the reliability analysis the Weibull shape (β) parameter is determined directly from the number of blocks, for which D=1. The damage element, damage block, and element reliability are all determined based on the values of beta (β) and D_i elements. Finally, based on the cumulated applied cycles n_i the Weibull scale (η) parameter is determined by to each D_i elements, damage block, and analyzed element.
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- 21 February 2025
- Published by Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne in Eksploatacja i Niezawodność – Maintenance and Reliability
Weibull Reliability Methodology based on Cumulated Vibration Damage
by María Magdalena Hernández Ramos, Manuel Román Piña Monarrez, Jesús Manuel Barraza Contreras, Osvaldo Monclova Quintanaz
In the paper, the formulated Weibull vibration reliability methodology is based on the cumulative vibration damage analysis. It lets us determine the reliability index of each damage element, each damage block, and the reliability of the analyzed element. The vibration cumulated damage is cumulated until D=1, by using the addressed vibration stress and a nonlinear cumulative damage model. Based on static and modal analysis, the vibration stress is determined by incorporating to it the geometry, weight and resonance effects. In the reliability analysis the Weibull shape (β) parameter is determined directly from the number of blocks, for which D=1. The damage element, damage block, and element reliability are all determined based on the values of beta (β) and D_i elements. Finally, based on the cumulated applied cycles n_i the Weibull scale (η) parameter is determined by to each D_i elements, damage block, and analyzed element.
Cited by 2
Open Access
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Cited by 1
- 21 February 2025
- Published by MDPI AG in Applied Sciences
Methodology to Determine the Stress Distribution Based on Fatigue Data with Bilinear Behavior and Its P–S–N Field and Testing Plan
by Osvaldo Monclova-Quintana, Manuel R. Piña-Monarrez, María M. Hernández-Ramos, Jesús F. Ortiz-Yáñez
In this paper, based on the Weibull Inverse Power Law, we present a methodology to determine the following: (1) the failure percentiles, referred to as the P–S–N field, of an S–N curve for a 42CrMo4 steel material exhibiting bilinear ( $s_{1} and s_{2})$ behavior (e.g., a competence failure mode); (2) the Weibull family that characterizes the entire bilinear behavior; and (3) the zero-vibration test plan that meets the required vibration reliability index of $R (t) = 0.97$ with a reliability confidence level of $C L = 0.75$ . From the application, based on the formulated normal–Weibull relationship, we determine the failure percentiles for the normal (one, two, and three) sigma levels, as well as those failure percentiles corresponding to the capability ( $C p$ ) and ability ( $C p k$ ) indices. Finally, we present the formulation to determine the $R (t)$ index and the $C L$ level associated with each normal percentile, along with their numerical values.
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- 21 February 2025
- Published by MDPI AG in Applied Sciences
Open Access
Methodology to Determine the Stress Distribution Based on Fatigue Data with Bilinear Behavior and Its P–S–N Field and Testing Plan
by Osvaldo Monclova-Quintana, Manuel R. Piña-Monarrez, María M. Hernández-Ramos, Jesús F. Ortiz-Yáñez
In this paper, based on the Weibull Inverse Power Law, we present a methodology to determine the following: (1) the failure percentiles, referred to as the P–S–N field, of an S–N curve for a 42CrMo4 steel material exhibiting bilinear ( $s_{1} and s_{2})$ behavior (e.g., a competence failure mode); (2) the Weibull family that characterizes the entire bilinear behavior; and (3) the zero-vibration test plan that meets the required vibration reliability index of $R (t) = 0.97$ with a reliability confidence level of $C L = 0.75$ . From the application, based on the formulated normal–Weibull relationship, we determine the failure percentiles for the normal (one, two, and three) sigma levels, as well as those failure percentiles corresponding to the capability ( $C p$ ) and ability ( $C p k$ ) indices. Finally, we present the formulation to determine the $R (t)$ index and the $C L$ level associated with each normal percentile, along with their numerical values.
Cited by 1
Open Access
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Google Scholar
- 12 December 2024
- Published by MDPI AG in Preprints.org
Methodology to Determine the Stress Distribution Based on Fatigue Data with Bilinear Behavior and Its P-S-N Field and Testing Plan
by Osvaldo Monclova-Quintana, Manuel R. Piña-Monarrez, María M. Hernández-Ramos, Jesús F. Ortiz-Yáñez
In this paper, the method to determine the percentiles of the P-S-N field when it presents bilinear (s1 and s2) behavior (e.g competence failure mode) is given. The percentiles are determined around the Weibull scale (η) parameter in Cycles that corresponds to the median applied stress of the whole bilinear behavior. The reliability (R(t)) index that corresponds to each P-S-N percentile are also determined. As well as the confidence reliability percentile (CL) that corresponds to each P-S-N percentile. The formulation to relate CL with its corresponding normal P-S-N percentile is also given. Numerically, the percentiles of the normal (one, two, and three) sigma levels, as well as those that correspond to the capability Cp and Cpk indices are related with their CL values, and R(t) indices. To validate the Weibull cycle bilinear family, a test plan is designed and numerically performed. In the numerical application we use the 42CrMo4 steel material.
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Google Scholar
- 12 December 2024
- Published by MDPI AG in Preprints.org
Open Access
Methodology to Determine the Stress Distribution Based on Fatigue Data with Bilinear Behavior and Its P-S-N Field and Testing Plan
by Osvaldo Monclova-Quintana, Manuel R. Piña-Monarrez, María M. Hernández-Ramos, Jesús F. Ortiz-Yáñez
In this paper, the method to determine the percentiles of the P-S-N field when it presents bilinear (s1 and s2) behavior (e.g competence failure mode) is given. The percentiles are determined around the Weibull scale (η) parameter in Cycles that corresponds to the median applied stress of the whole bilinear behavior. The reliability (R(t)) index that corresponds to each P-S-N percentile are also determined. As well as the confidence reliability percentile (CL) that corresponds to each P-S-N percentile. The formulation to relate CL with its corresponding normal P-S-N percentile is also given. Numerically, the percentiles of the normal (one, two, and three) sigma levels, as well as those that correspond to the capability Cp and Cpk indices are related with their CL values, and R(t) indices. To validate the Weibull cycle bilinear family, a test plan is designed and numerically performed. In the numerical application we use the 42CrMo4 steel material.
Open Access
Website
Google Scholar
- 9 August 2024
- Published by MDPI AG in Preprints.org
Weibull Random Vibration Reliability Based on Cumulated Damage
by María M. Hernández-Ramos, Manuel R. Piña-Monarrez, Jesús M. Barraza-Contreras, Osvaldo Monclova-Quintana
In this paper, based on the cumulated damage generated by the cyclical application of the testing vibration profile, a methodology to determine the reliability index of the analyzed component is given. In the analysis, the testing time, component geometry, applied weight, and material resonant frequency are all of them considered by using a dynamic, and amplitude factor. Then, from the generated vibration response data of the analysis, the corresponding bending stress is determined for each one of the rows of the testing profile. And by the cyclical application of the whole testing profile, the corresponding damage is cumulated to each profile cycle until the cumulated damage is D=1. Finally, the reliability that each one of the cumulated blocks (cyclical profile application) is determined by considering, the random vibration is a stress variable. Thus, we use the cumulative damage model with the inverse power law stress/life relationship to determine the two parameter Weibull distribution used to estimate the reliability index of each cumulated block. As a numerical application, we analyze a cantilever aluminum beam Al 6061-T6.
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- 9 August 2024
- Published by MDPI AG in Preprints.org
Open Access
Weibull Random Vibration Reliability Based on Cumulated Damage
by María M. Hernández-Ramos, Manuel R. Piña-Monarrez, Jesús M. Barraza-Contreras, Osvaldo Monclova-Quintana
In this paper, based on the cumulated damage generated by the cyclical application of the testing vibration profile, a methodology to determine the reliability index of the analyzed component is given. In the analysis, the testing time, component geometry, applied weight, and material resonant frequency are all of them considered by using a dynamic, and amplitude factor. Then, from the generated vibration response data of the analysis, the corresponding bending stress is determined for each one of the rows of the testing profile. And by the cyclical application of the whole testing profile, the corresponding damage is cumulated to each profile cycle until the cumulated damage is D=1. Finally, the reliability that each one of the cumulated blocks (cyclical profile application) is determined by considering, the random vibration is a stress variable. Thus, we use the cumulative damage model with the inverse power law stress/life relationship to determine the two parameter Weibull distribution used to estimate the reliability index of each cumulated block. As a numerical application, we analyze a cantilever aluminum beam Al 6061-T6.
Open Access
Website
Google Scholar
Cited by 5
- 17 July 2024
- Published by MDPI AG in Applied Sciences
Acceleration of Service Life Testing by Using Weibull Distribution on Fiber Optical Connectors
by Jesús M. Barraza-Contreras, Manuel R. Piña-Monarrez, María M. Hernández-Ramos, Osvaldo Monclova-Quintana, Secundino Ramos-Lozano
The service life assessment of previous fatigue stress has a fundamental role in estimating the reliability of products like fiber optical connectors, and should replicate use in severe environments in telecommunications systems. However, the vibration prediction models used in the literature present limitations in vibration life prediction. In this paper, we propose using the insertion loss fatigue life and including it in the Weibull distribution to determine the Weibull parameters ƞ and β to evaluate fiber optic connector reliability R(t) under environmental and mechanical testing stress. We analyzed the failure data of a standard telecommunication fiber optical connector under a program of service life stress testing against that of a fiber optical connector under only mechanical vibration stress testing. The fiber connectors were monitored during the vibration testing to review the transient change of the optical signal. Their results showed that the reliability of the fiber connectors submitted to the service life program was $R (t) = 0.694$ , while that of the fiber connectors submitted to mechanical vibration only was $R (t) = 0.970$ . In addition, the analysis showed that the service life testing consumed 70.2% of the product’s lifetime. We present in Numerical Validation the steps to determine the acceleration factors of the vibration test developed.
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- 17 July 2024
- Published by MDPI AG in Applied Sciences
Open Access
Acceleration of Service Life Testing by Using Weibull Distribution on Fiber Optical Connectors
by Jesús M. Barraza-Contreras, Manuel R. Piña-Monarrez, María M. Hernández-Ramos, Osvaldo Monclova-Quintana, Secundino Ramos-Lozano
The service life assessment of previous fatigue stress has a fundamental role in estimating the reliability of products like fiber optical connectors, and should replicate use in severe environments in telecommunications systems. However, the vibration prediction models used in the literature present limitations in vibration life prediction. In this paper, we propose using the insertion loss fatigue life and including it in the Weibull distribution to determine the Weibull parameters ƞ and β to evaluate fiber optic connector reliability R(t) under environmental and mechanical testing stress. We analyzed the failure data of a standard telecommunication fiber optical connector under a program of service life stress testing against that of a fiber optical connector under only mechanical vibration stress testing. The fiber connectors were monitored during the vibration testing to review the transient change of the optical signal. Their results showed that the reliability of the fiber connectors submitted to the service life program was $R (t) = 0.694$ , while that of the fiber connectors submitted to mechanical vibration only was $R (t) = 0.970$ . In addition, the analysis showed that the service life testing consumed 70.2% of the product’s lifetime. We present in Numerical Validation the steps to determine the acceleration factors of the vibration test developed.
Cited by 5
Open Access
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- 1 January 2018
- Published by Universidad Autonoma de Ciudad Juarez in Cultura Científica y Tecnológica
Protocolo de Identificación de Riesgos para Gasolineras Caso de estudio: Empresa Operadora de Hidro SA de CV
by Vicente Jonathan Medina Loeza, Manuel Alberto Rodríguez Esparza, Karla Gabriela Gómez Bull, María Magdalena Hernández Ramos, Pedro Rodríguez Armas
Protocolo de Identificación de Riesgos para Gasolineras Caso de estudio: Empresa Operadora de Hidro SA de CV
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- 1 January 2018
- Published by Universidad Autonoma de Ciudad Juarez in Cultura Científica y Tecnológica
Open Access
Protocolo de Identificación de Riesgos para Gasolineras Caso de estudio: Empresa Operadora de Hidro SA de CV
by Vicente Jonathan Medina Loeza, Manuel Alberto Rodríguez Esparza, Karla Gabriela Gómez Bull, María Magdalena Hernández Ramos, Pedro Rodríguez Armas
Protocolo de Identificación de Riesgos para Gasolineras Caso de estudio: Empresa Operadora de Hidro SA de CV