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Reliability assessment for micro inertial measurement unit based on accelerated degradation data and copula theoryDOI: 10.17531/ein.2022.3.16 Issue: Article citation info: Chi B, Wang Y, Hu J, Zhang S, Chen X. Reliability assessment for micro inertial measurement unit based on accelerated degradation data and copula theory. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2022; 24 (3): 554–563, http://doi.org/10.17531/ein.2022.3.16.
Abstract: With its extensive use in industry, assessing the reliability of the micro inertial measurment unit (MIMU) has become a pressing need. Unfortunately, the MIMU is made up of several components, and the degradation processes of each are intertwined, making it difficult to assess the MIMU’s reliability and remaining useful life. In this research, we offer a reliability assessment approach for the MIMU, which has long-lifetime and multiple performance characteristics (PCs), based on accelerated degradation data and copula theory.Each PC model of MIMU is constructed utilizing drift Brownian motion to depict accelerated degradation process. The copula function is used to model the multivariate dependent accelerated degradation test data and to describe the dependency between multiple MIMU performance parameters. The particle swarm optimization algorithm is used to estimate the unknown parameters in the multi-dependent ADT model. Finally, the storage test and simulation example on MIMU’s accelerated degradation data verify the feasibility and effectiveness of the proposed method. |
A random maintenance last model with preventive maintenance for the product under a random warrantyDOI: 10.17531/ein.2022.3.15 Issue: Article citation info: Shang L, Zou A, Qiu Q, Du Y. A random maintenance last model with preventive maintenance for the product under a random warranty. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2022; 24 (3): 544–553, http://doi.org/10.17531/ein.2022.3.15.
Abstract: Although renewing pro-rate replacement warranty (RPRW) can help producers obtain some compensation from users, there seldom exists a two-dimensional random RPRW with a refund (2D-RRPRW with R) where a refund can guarantee the fairness of users. In addition, although random periodic replacement last (RPRL) can extend the service span after the expiry of the warranty, RPRL considering preventive maintenance (PM) has been seldom modeled to further lengthen the service span after the expiry of the warranty. In view of these, a 2D-RRPRW with R is devised to guarantee the fairness of users by integrating the limited job cycles and a refund into RPRW. Under the case where 2D-RRPRW with R warrants products with job cycles, a RPRL with PM is modeled to further lengthen the service span after the expiry of the warranty and reduce the failure frequency. It shows that to shorten the warranty period can makes the warranty cost of 2D-RRPRW with R to be less than the warranty cost of classic RPRW; and the performance of RPRL with PM outperforms the performance of classic RPRL. |
An adaptive PC-Kriging method for time-variant structural reliability analysisDOI: 10.17531/ein.2022.3.14 Issue: Article citation info: Nan H, Li H, Song Z. An adaptive PC-Kriging method for time-variant structural reliability analysis. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2022; 24 (3): 532–543, http://doi.org/10.17531/ein.2022.3.14.
Abstract: The practical application of time-variant reliability analysis is limited by its computationally expensive models which describe the structural system behavior. This paper presents a new adaptive PC-Kriging (APCK) approach to accurately and efficiently assess the time-variant reliabilities. Time interval is firstly discretized with a series of time instants and then the stochastic process is reconstructed by standard normal random variables and deterministic function of time. PC-Kriging (PCK) models are built at each time instant to predict the instantaneous responses of performance function. To improve the accuracy and efficiency, a new update strategy based on the integration of U- and H- learning functions is developed to refine the PCK models of instantaneous responses. One or two best samples are identified by the proposed learning criterion for updating the PCK models. Finally, Monte Carlo simulation (MCS) is used to estimate the time-variant reliability based on the updated PCK models. Four examples are used to validate the accuracy and efficiency of the proposed method. |
Evaluation of light commercial vehicles operation process in a transport company using the regression modelling methodDOI: 10.17531/ein.2022.3.13 Issue: Article citation info: Owczarek P, Brzeziński M, Zelkowski J. Evaluation of light commercial vehicles operation process in a transport company using the regression modelling method. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2022; 24 (3): 522–531, http://doi.org/10.17531/ein.2022.3.13.
Abstract: This paper presents an analysis of the results of daily observations from the execution of transport orders by three types of vehicles over a period of 2 years. The purpose of the research was to evaluate the operation process and determine the influence of important technical and operational variables on the economic efficiency of the operation process. A set of 7 quantitative variables, previously not considered in the evaluation of the commercial vehicle operation process, was subjected to statistical data analysis. An indicator analysis and evaluation of the intensity of use of the following types of vehicles was conducted: Renault Master, Fiat Ducato and Citroen Jumper. Based on the results of the research, the vehicle with the highest efficiency was determined and possible assumptions of the strategy applied in the company were indicated. The analysis and evaluation of vehicle efficiency gave rise to the identification of independent variables determining the company's income. Using the indicator method and the multivariate regression model, transport companies can evaluate the efficiency of transport tasks undertaken. |
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