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Jian Li

Bio: Jian Li is an academic researcher from Xi'an Jiaotong University. The author has contributed to research in topics: Categorical variable & Control chart. The author has an hindex of 9, co-authored 30 publications receiving 303 citations. Previous affiliations of Jian Li include Shaanxi Normal University & Tsinghua University.

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors examined the production and transportation outsourcing problems of a two-echelon supply chain under the cap-and-trade policy and joint cap and trade and carbon tax policy, and showed that the extended model with carbon policies is more beneficial for emissions reduction, and the effect of emissions reduction gradually becomes smooth as the carbon price increases.

76 citations

Journal ArticleDOI
TL;DR: Simulation results show the proposed approach outperforms existing methods, especially at an early stage, and will aim at improving the method’s sensitivity in distinguishing faults similar to each other.
Abstract: This paper proposes a wavelet-based statistical signal detection approach for monitoring and diagnosis of bearing compound faults at an early stage. The bearing vibration signal is decomposed by an orthonormal discrete wavelet transform to obtain its energy dispersions at multiple levels. We investigate the statistical properties of the decomposed signal energy under both the normal and faulty conditions, based on which a generalized likelihood ratio test is developed. An exponentially weighted moving average control chart is then constructed to detect faults at an early stage. Simulation studies and a real case study are conducted to demonstrate the effectiveness of the proposed method. Furthermore, the comparison studies show that the proposed method outperforms the empirical mode decomposition method and Hilbert envelope spectrum analysis method. Note to Practitioners —This paper is motivated by the problem of monitoring and diagnosis of compound faults in rolling bearings at the early stage, which are seldom considered in existing methods. In this paper, we propose a new approach by using statistical signal detection method and wavelet transform to handle the fault signals. This work aims at monitoring vibration signals and diagnosing fault types. Our simulation results show the proposed approach outperforms existing methods, especially at an early stage. Our future work will aim at improving the method’s sensitivity in distinguishing faults similar to each other.

61 citations

Journal ArticleDOI
TL;DR: In this article, a phase II control chart is proposed that is robust in efficiently detecting various shifts, especially those in interaction effects representing the dependence among factors, and the use of log-linear models for characterizing the relationship among categorical factors that are adapted into a framework of multivariate binomial and multivariate multinomial distributions.
Abstract: This article considers statistical process control for multivariate categorical processes. In particular, there is a focus on multivariate binomial and multivariate multinomial processes. More and more real applications involve categorical quality characteristics, which cannot be measured on a continuous scale. These characteristic factors usually correlate with each other, indicating a need for multivariate charting techniques. However, there is a scarcity of research on monitoring multivariate categorical data, and most existing methods lack robustness for some deficiencies. This article reports the use of log-linear models for characterizing the relationship among categorical factors that are adapted into a framework of multivariate binomial and multivariate multinomial distributions. A Phase II control chart is proposed that is robust in efficiently detecting various shifts, especially those in interaction effects representing the dependence among factors. Numerical simulations and a real data example...

48 citations

Journal ArticleDOI
TL;DR: A Phase II log-linear directional control chart is proposed that exploits directional shift information and integrates the monitoring of multivariate categorical processes into the unified framework ofMultivariate binomial and multivariate multinomial distributions.
Abstract: The authors consider statistical process control of multivariate categorical processes and propose a Phase II log-linear directional control chart.

45 citations

Journal ArticleDOI
TL;DR: In this paper, a simple ordinal categorical chart is proposed to detect location shifts in the latent variable based on merely the attribute level counts, regardless of the continuous values of a latent variable.
Abstract: Traditional control charts for monitoring attribute data usually neglect the order among the attribute levels, such as good, marginal and bad, of a categorical factor. Such order may be reflected by an underlying continuous variable, which determines the level of the categorical factor by classifying it according to some thresholds in the latent continuous scale. This paper exploits this ordinal information and proposes a control chart for detecting location shifts in the latent variable based on merely the attribute level counts, regardless of the continuous values of the latent variable. The proposed ordinal chart is very simple to construct and enjoys the same setting as conventional categorical charts. Numerical simulations demonstrate the superiority of this simple ordinal categorical chart.

23 citations


Cited by
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Journal ArticleDOI
TL;DR: An overview and perspective of recent research and applications of statistical process monitoring, including health-related monitoring, spatiotemporal surveillance, profile monitoring, use of autocorrelated data, the effect of estimation error, and high-dimensional monitoring, among others are provided.
Abstract: This paper provides an overview and perspective of recent research and applications of statistical process monitoring.

282 citations

02 Nov 2011
TL;DR: This paper presents a novel statistical change-point detection algorithm based on non-parametric divergence estimation between time-series samples from two retrospective segments that is accurately and efficiently estimated by a method of direct density-ratio estimation.
Abstract: The objective of change-point detection is to discover abrupt property changes lying behind time-series data. In this paper, we present a novel statistical change-point detection algorithm based on non-parametric divergence estimation between time-series samples from two retrospective segments. Our method uses the relative Pearson divergence as a divergence measure, and it is accurately and efficiently estimated by a method of direct density-ratio estimation. Through experiments on artificial and real-world datasets including human-activity sensing, speech, and Twitter messages, we demonstrate the usefulness of the proposed method.

271 citations

Posted Content
05 Nov 2008-viXra
TL;DR: In this paper, the authors introduced two new discrete distributions: multivariate Binomial distribution and multivariate Poisson distribution, which were created in eventology as more correct generalizations of Binomial and Poisson distributions.
Abstract: This article brings in two new discrete distributions: multivariate Binomial distribution and multivariate Poisson distribution. Those distributions were created in eventology as more correct generalizations of Binomial and Poisson distributions. Accordingly to eventology new laws take into account full distribution of events. Also, some properties and characteristics of these new multivariate discrete distributions are described.

224 citations

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper investigated the impacts of CTP and LCSP on the production and carbon emission reduction level of a manufacturer, and explored which policy is better for society, and found that LCSP is more beneficial to society when the environmental damage coefficient is less than a threshold.

198 citations

Journal ArticleDOI
Yi Yu-yin1, Li Jinxi1
TL;DR: In this paper, the authors examined how carbon taxes and energy-saving products subsidies affect enterprises' operational decisions, and proposed a carbon-cost-sharing contract to ensure the supply chain members cooperate and realise larger energy savings and emissions reductions.

158 citations