Xun Xiao

Bio: Xun Xiao is an academic researcher from Massey University. The author has contributed to research in topics: Weibull distribution & Control system. The author has an hindex of 6, co-authored 20 publications receiving 128 citations. Previous affiliations of Xun Xiao include City University of Hong Kong & Luleå University of Technology.

Optimal Design for Destructive Degradation Tests With Random Initial Degradation Values Using the Wiener Process

Abstract: This study investigates modeling, estimation and optimization of destructive degradation tests (DDTs) for highly reliable products with random initial degradation values. It is common to observe that the degradation paths of distinct products start from different values specified by a random variable. The random initial value introduces additional uncertainties to the degradation of the product. In this study, Wiener-process-based degradation models are developed for products with random initial values. We first consider a DDT without stress acceleration. In a DDT, the measurement of the degradation destroys a test unit and, thus, only one measurement is available for each unit. Closed-form maximum likelihood (ML) estimators are derived. Then, an accelerated DDT (ADDT) is considered. Based on these results, we investigate optimal designs of both DDT and ADDT with the objective of minimizing the asymptotic variance of the estimated $p$ th-quantile of the failure time distribution under use conditions. The optimal test plans have to be obtained through a numerical approach. Optimality of the plans is verified by the general equivalence theorem. An adhesive bond example with real degradation data is analyzed to show the performance of the proposed methods.

Modelling infant failure rate of electromechanical products with multilayered quality variations from manufacturing process

Abstract: The optimisation of product infant failure rate is the most important and difficult task for continuous improvement in manufacturing; how to model the infant failure rate promptly and accurately of the complex electromechanical product in manufacturing is always a dilemma for manufacturers. Traditional methods of reliability analysis for the produced product usually rely on limited test data or field failures, the valuable information of quality variations from the manufacturing process has not been fully utilised. In this paper, a multilayered model structured by ‘part-level, component-level, system-level’ is presented to model the reliability in the form of infant failure rate by quantifying holistic quality variations from manufacturing process for electromechanical products. The mechanism through which the multilayered quality variations affect the infant failure rate is modelled analytically with a positive correlation structure. Furthermore, an integrated failure rate index is derived to model the r...

Prediction of railway track geometry defects: a case study

Abstract: The aim of this study has been to develop a data-driven analytical methodology for prediction of isolated track geometry defects, based on the measurement data obtained from a field study. Within t...

Modelling the evolution of ballasted railway track geometry by a two-level piecewise model

Abstract: Accurate prediction and efficient simulation of the evolution of track geometry condition is a prerequisite for planning effective railway track maintenance. In this regard, the degradation and tamping effect should be equipped with proper and efficient probabilistic models. The possible correlation induced by the spatial structure also needs to be taken into account when modelling the track geometry degradation. To address these issues, a two-level piecewise linear model is proposed to model the degradation path. At the first level, the degradation characteristic of each track section is modelled by a piecewise linear model with known break points at the tamping times. At the second level, Autoregressive Moving Average models are used to capture the spatial dependences between the parameters of the regression lines indexed by their locations. To illustrate the model, a comprehensive case study is presented using data from the Main Western Line in Sweden.

Stochastic Ageing and Dependence for Reliability

Abstract: (2007). Stochastic Ageing and Dependence for Reliability. Technometrics: Vol. 49, No. 2, pp. 222-222.

Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis

Abstract: Digital transformation (DT) has become a buzzword, triggering different disciplines in research and influencing practice, which leads to independent research streams. Scholars investigate the antecedents, contingencies, and consequences of these disruptive technologies by examining the use of single technologies or of digitization, in general. Approaches are often very specialized and restricted to their domains. Thus, the immense breadth of technologies and their possible applications conditions a fragmentation of research, impeding a holistic view. With this systematic literature review, we aim to fill this gap in providing an overview of the different disciplines of DT research from a holistic business perspective. We identified the major research streams and clustered them with co-citation network analysis in nine main areas. Our research shows the main fields of interest in digital transformation research, overlaps of the research areas and fields that are still underrepresented. Within the business research areas, we identified three dominant areas in literature: finance, marketing, and innovation management. However, research streams also arise in terms of single branches like manufacturing or tourism. This study highlights these diverse research streams with the aim of deepening the understanding of digital transformation in research. Yet, research on DT still lacks in the areas of accounting, human resource management, and sustainability. The findings were distilled into a framework of the nine main areas for assisting the implications on potential research gaps on DT from a business perspective.