Reliability assessment of complex mechatronic systems using a modified nonparametric belief propagation algorithm

Abstract

Various parametric skewed distributions are widely used to model the time-to-failure (TTF) in the reliability analysis of mechatronic systems, where many items are unobservable due to the high cost of testing. Estimating the parameters of those distributions becomes a challenge. Previous research has failed to consider this problem due to the difficulty of dependency modeling. Recently the methodology of Bayesian networks (BNs) has greatly contributed to the reliability analysis of complex systems. In this paper, the problem of system reliability assessment (SRA) is formulated as a BN considering the parameter uncertainty. As the quantitative specification of BN, a normal distribution representing the stochastic nature of TTF distribution is learned to capture the interactions between the basic items and their output items. The approximation inference of our continuous BN model is performed by a modified version of nonparametric belief propagation (NBP) which can avoid using a junction tree that is inefficient for the mechatronic case because of the large treewidth. After reasoning, we obtain the marginal posterior density of each TTF model parameter. Other information from diverse sources and expert priors can be easily incorporated in this SRA model to achieve more accurate results. Simulation in simple and complex cases of mechatronic systems demonstrates that the posterior of the parameter network fits the data well and the uncertainty passes effectively through our BN based SRA model by using the modified NBP.

Fuzzy Decision Making for Conceptual Design of a Visual Servoing System Using Mechatronic Multi-Criteria Profile (MMP)

“…System reliability assessment (SRA) has been addressed as an important issue of the design process of mechatronic systems in many literatures [17,18]. A number of methods for reliability assessment have been developed, most of which estimate the system reliability using only the data of components [19]. The methods of fault tree analysis (FTA) and failure modes and effect analysis (FMEA) are the most popular tools for reliability assessment, while some other research have been established based upon using Petri nets (PN) for modeling of dynamic characteristics of complex mechatronic systems [17].…”

Reliability assessment of complex electromechanical systems: A network perspective

“…Although there are already various methods dedicated to system reliability evaluation, most of them estimate the reliability by using only the data of components, since it is much easier and less expensive to gather the components than the whole system. 2 Table 1 reviews and classifies the related methods of reliability assessment.…”

“…Percolation reliability is one of the typical indices for evaluation of network reliability and has the following advantages 39 : (1) Statistical descriptions of the network topology comply well with practical requirements for the analysis of system reliability. (2) The combinatorial explosion problem arising in the calculations of classical reliability, which in detail means that the computational complexity grows exponentially with the number of nodes or states increasing, can be circumvented. (3) Component reliability and the impact of system topology to network reliability are considered altogether.…”

Qualitative and quantitative approaches to analyse reliability of a mechatronic system: a case

“…Based upon the above studies in general, the authors believe that system risk and reliability assessment (SRRA) is a fundamental research problem in the field of mechatronics for the following reasons (Chen et al 2009;Zhong et al 2010;Sierla et al 2012;Khalaj et al 2013; Rao and Naikan 2014).…”

“…However, well-established integrated framework which takes into account vague, imprecise, and subjective issues in complex mechatronic system is still missing and is a source of concern which needs to be addressed. In the words of Zhong et al (2010) ''the attempt to improve system reliability makes the task of system reliability assessment an ongoing research topic''. In the system reliability and safety assessment, the focuses are not only the risks caused by hardware or software, but also the risks caused by ''human error'' (Cheng et al 2010).…”