Statistical inference for masked interval data with Weibull distribution under simple step-stress test and tampered failure rate model

2017 ◽  
Vol 231 (6) ◽  
pp. 654-665 ◽  
Author(s):  
Fariba Azizi ◽  
Firoozeh Haghighi ◽  
Elahe Ghadiri ◽  
Leila Torabi
Keyword(s):  
Weibull Distribution ◽  
Statistical Inference ◽  
Failure Rate ◽  
Stress Test ◽  
Interval Data ◽  
Rate Model ◽  
Simple Step

Is high-altitude mountaineering Russian roulette?

2013 ◽  
Vol 9 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Edward K. Cheng
Keyword(s):  
High Altitude ◽  
Failure Rate ◽  
Rate Model ◽  
Reliability Engineering ◽  
Significant Difference ◽  
Inference Techniques ◽  
Decreasing Failure Rate

AbstractWhether the nature of the risks associated with climbing high-altitude (8000 m) peaks is in some sense “controllable” is a longstanding debate in the mountaineering community. Well-known mountaineers David Roberts and Ed Viesturs explore this issue in their recent memoirs. Roberts views the primary risks as “objective” or uncontrollable, whereas Viesturs maintains that experience and attention to safety can make a significant difference. This study sheds light on the Roberts-Viesturs debate using a comprehensive dataset of climbing on Nepalese Himalayan peaks. To test whether the data is consistent with a constant failure rate model (Roberts) or a decreasing failure rate model (Viesturs), it draws on Total Time on Test (TTT) plots from the reliability engineering literature and applies graphical inference techniques to them.

scholarly journals Probabilistic failure rate model of a tidal turbine pitch system

2020 ◽  
Vol 160 ◽  
pp. 987-997
Author(s):  
Fraser J. Ewing ◽  
Philipp R. Thies ◽  
Jonathan Shek ◽  
Claudio Bittencourt Ferreira
Keyword(s):  
Failure Rate ◽  
Rate Model ◽  
Tidal Turbine ◽  
Pitch System

scholarly journals Statistical Inference for the Weibull Distribution Based on δ-Record Data

Symmetry ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 20 ◽  
Author(s):  
Raúl Gouet ◽  
F. Javier López ◽  
Lina Maldonado ◽  
Gerardo Sanz
Keyword(s):  
Maximum Likelihood ◽  
Experimental Design ◽  
Weibull Distribution ◽  
Bayesian Estimation ◽  
Statistical Inference ◽  
Numerical Computation ◽  
Weibull Model ◽  
Rainfall Series ◽  
Estimation Of Parameters ◽  
Record Data

We consider the maximum likelihood and Bayesian estimation of parameters and prediction of future records of the Weibull distribution from δ -record data, which consists of records and near-records. We discuss existence, consistency and numerical computation of estimators and predictors. The performance of the proposed methodology is assessed by Montecarlo simulations and the analysis of monthly rainfall series. Our conclusion is that inferences for the Weibull model, based on δ -record data, clearly improve inferences based solely on records. This methodology can be recommended, more so as near-records can be collected along with records, keeping essentially the same experimental design.

Multi-state failure phenomenon and analysis using semi-Markov model

2018 ◽  
Vol 35 (9) ◽  
pp. 2080-2091 ◽  
Author(s):  
Mahesh Narayan Dhawalikar ◽  
V. Mariappan ◽  
P.K. Srividhya ◽  
Vishal Kurtikar
Keyword(s):  
Markov Model ◽  
Weibull Distribution ◽  
Exponential Distribution ◽  
Failure Rate ◽  
Degradation Process ◽  
Markov Modeling ◽  
Content Type ◽  
Availability Analysis ◽  
Unique Approach ◽  
Reliability And Availability

Purpose Degraded failures and sudden critical failures are quite prevalent in industries. Degradation processes commonly belong to Weibull family and critical failures are found to follow exponential distribution. Therefore, it becomes important to carry out reliability and availability analysis of such systems. From the reported literature, it is learnt that models are available for the situations where the degraded failures as well as critical failures follow exponential distribution. The purpose of this paper is to present models suitable for reliability and availability analysis of systems where the degradation process follows Weibull distribution and critical failures follow exponential distribution. Design/methodology/approach The research uses Semi-Markov modeling using the approach of method of stages which is suitable when the failure processes follow Weibull distribution. The paper considers various states of the system and uses state transition diagram to present the transition of the system among good state, degraded state and failed state. Method of stages is used to convert the semi-Markov model to Markov model. The number of stages calculated in Method of stages is usually not an integer value which needs to be round off. Method of stages thus suffers from the rounding off error. A unique approach is proposed to arrive at failure rates to reduce the error in method of stages. Periodic inspection and repairs of systems are commonly followed in industries to take care of system degradation. This paper presents models to carry out reliability and availability analysis of the systems including the case where degraded failures can be arrested by appropriate inspection and repair. Findings The proposed method for estimating the degraded failure rate can be used to reduce the error in method of stages. The models and the methodology are suitable for reliability and availability analysis of systems involving degradation which is very common in systems involving moving parts. These models are very suitable in accurately estimating the system reliability and availability which is very important in industry. The models conveniently cover the cases of degraded systems for which the model proposed by Hokstad and Frovig is not suitable. Research limitations/implications The models developed consider the systems where the repair phenomenon follows exponential and the failure mechanism follows Weibull with shape parameter greater than 1. Practical implications These models can be suitably used to deal with reliability and availability analysis of systems where the degradation process is non-exponential. Thus, the models can be practically used to meet the industrial requirement of accurately estimating the reliability and availability of degradable systems. Originality/value A unique approach is presented in this paper for estimating degraded failure rate in the method of stages which reduces the rounding error. The models presented for reliability and availability analyses can deal with degradable systems where the degradation process follows Weibull distribution, which is not possible with the model presented by Hokstad and Frovig.

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