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To improve the detecting abilities of upward and downward parameter changes in high‐quality process, two combined schemes by integrating memory‐type, that is, exponentially weighted moving average (EWMA) or cumulative sum (CUSUM), and memoryless, that is, Shewhart, are proposed for monitoring the time between events (TBE), which is modeled as an exponential distributed variable. A Monte Carlo simulation method is employed to obtain the Run Length (RL$RL$) properties, that is average run length (ARL$ARL$), of the proposed schemes for different parameter settings. The nearly optimal monitoring parameter combinations under different change size are obtained by minimizing the out‐of‐control ARL$ARL$ with the satisfied in‐control ARL$ARL$. Using the designed parameters, the ARL$ARL$ performance of the proposed monitoring schemes is compared with the existing EWMA and CUSUM TBE. The results show that the proposed combined Shewhart–EWMA or Shewhart–CUSUM TBE generally perform better than the corresponding EWMA or CUSUM TBE for large changes and they also show better performance than the Shewhart TBE for small changes. Finally, a real dataset of organic light‐emitting diode (OLED) failure time from Sumsung company is employed to indicate the usage and implementation of combined TBE schemes. [ABSTRACT FROM AUTHOR]

Monitoring the ratio of two normal random variables, which is usually denoted as RZ, is one of the most important directions in statistical process control (SPC). In production scenarios, when the product specification is related to the relative ratio of two components in a mixture, or when the ratio represents a property of the product, or the difference between a product's quality measurement before and after an operation (such as a chemical reaction), the product quality can be improved by applying monitoring schemes for RZ. To further enhance the sensitivity of traditional RZ schemes in detecting process changes, especially small and moderate ones, this paper proposes an improved exponentially weighted moving average (IEWMA) monitoring scheme. The run length (RL) distribution of the proposed IEWMA‐RZ scheme is obtained by using the Monte‐Carlo (MC) simulation. The superiority of the proposed monitoring scheme is shown by comparing with the existing EWMA‐RZ scheme. [ABSTRACT FROM AUTHOR]

The coefficient of variation (CV) is one of the most important quality characteristics in industrial applications. There have been some control charts for monitoring this dimensionless and normalized characteristic. This paper presents three double exponentially weighted moving average (DEWMA) charts for monitoring the CV. Many numerical simulations are performed and the results are given in several tables to show the properties of the proposed DEWMA CV charts. Through comparisons with other existing exponentially weighted moving average (EWMA) CV charts using the average run length (ARL) metric, it is shown that the proposed DEWMA CV charts perform better than the existing EWMA CV charts for small shifts, especially when the smoothing parameter increases. In addition, a detailed comparison among the proposed three DEWMA CV charts is also presented. A real date example from industry is used to show the implementation of the proposed charts. [ABSTRACT FROM AUTHOR]

The coefficient of variation (CV) chart is widely used in the process where the standard deviation is proportional to the mean. In this work, two separate one-sided triple exponentially weighted moving average control charts are proposed to monitor the CV squared (denoted as TEWMA- $ {\mathrm{\gamma }^2} $ γ 2 chart). By adding the variable sampling interval (VSI) feature to the proposed - $ {\mathrm{\gamma }^2} $ γ 2 charts, the VSI TEWMA- $ {\mathrm{\gamma }^2} $ γ 2 charts are further proposed to improve the performance of the TEWMA- $ {\mathrm{\gamma }^2} $ γ 2 charts. Through extensive Monte Carlo simulations, the zero-state and steady-state run length (RL) performances are presented. The comparisons with the existing CV charts, based on several run length metrics show the superiority of the proposed charts, especially for small shifts. Moreover, the overall measure, expected ARL (EARL), also shows the outperformance of the $ {\mathrm{\gamma }^2} $ γ 2 charts. In addition, based on the average time to signal (ATS) and adjusted ATS (AATS), it is shown that the VSI strategy makes the TEWMA- $ {\mathrm{\gamma }^2} $ γ 2 charts detect the shifts more quickly. An illustrative example from the sintering process is finally provided to display the application of the proposed charts. [ABSTRACT FROM AUTHOR]

This paper examines how the Durkheimian approach to the 'ideal' delineates a possible way of straddling the dilemma between the normative orientation of 'powerful knowledge' accounts and the critical orientation of 'knowledge of the powerful' accounts. It argues that the normative aims are embedded in the fabrics of the sociological description with which the Durkheimian notion of 'elementary form' is concerned. To see where this enterprise can lead, this paper turns to the sociology of education of Bourdieu and Bernstein. Both draw on Durkheim's writings on primitive classifications in education and society, working towards uncovering the regularities of the world of knowledge classifications. Keeping in line with Bourdieu and Bernstein, this paper argues that one has to make the same refusal to the advocates of an abstract ideal of educational knowledge that is dissociated from its social conditions of historical realization in pedagogic contexts, and to the advocates of a cynical relativism of ideal that rejects any necessities socially established. [ABSTRACT FROM AUTHOR]

This paper makes a theoretical contribution to the discussion of interdisciplinary knowledge in curriculum and research. As a challenge to much of the Mode 2 thesis concerned only with the importance of knowledge being socially relevant, this paper demonstrates how a Bernsteinian approach to interdisciplinarity relates to the internal configurations underpinning interdisciplinary knowledge. Inspired by explorations of Bernsteinian communities, this paper sets out to conceptualize the socio‐epistemic constraints under which powerful disciplinary boundary crossing occurs. The major claim is that the boundaries between disciplines and between them and the field of practice, are essential for boundary crossing. The interdisciplinary efforts do not necessarily involve diminishing disciplinary boundaries, but they are vulnerable to external weakening when there is little connection to the disciplinary core that provides stable internal norms. This paper adds to the discussion by suggesting alternatives to interdisciplinary integration, which do not require a background intellectual consilience between disciplines. It presents an appeal for a form of interdisciplinarity that is pursued to a practical end within refining disciplinary conceptual models, without invoking exaggerated claims for 'relevance', and with no need for a more complex edifice for crossing the established borders between disciplines. [ABSTRACT FROM AUTHOR]

Control charts based on Time Between Events (TBE) have been shown to be effective in high quality processes, where the defects or failures (events) occur at a very low probability. The occurrences of events are usually modeled as a homogeneous Poisson process. The TBE data is likely to follow a skewed distribution, such as the gamma distribution. In order to monitor high quality processes, this study focuses on the development of modified one-sided Exponentially Weighted Moving Average (EWMA) TBE charts. The Monte-Carlo simulation method is used to evaluate the Run Length (RL) properties of the proposed schemes. The results show that the proposed schemes are more sensitive to process shifts than some competitive procedures. Finally, a real data example is provided to illustrate the implementation of the proposed charts. [ABSTRACT FROM AUTHOR]

Abstract A nonparametric process monitoring scheme with Variable Sampling Intervals (VSI) is investigated to monitor the median in this paper. The proposed scheme is based on the sign test statistic and used a new adaptive-type exponentially weighted moving average control chart. A discrete-state Markov Chain method is presented, and the exact Average Time to Signal (ATS) properties are discussed. The comparative results indicate that the proposed chart can reduce the time in detecting shifts than the corresponding schemes for the fixed sampling interval and provide higher sensitivity for detecting shifts with various magnitudes. The proposed chart’s in-control robustness is demonstrated for different continuous distributions using numerical results based on the Monte-Carlo simulation. The implementation of this VSI nonparametric chart is also explained through an illustrative example. [ABSTRACT FROM AUTHOR]

Compared with the traditional "dynamic‐static" load rockburst induced by working face mining, a new typical disaster with concealment characteristics has appeared in deep thick coal seam roadways, namely, static creep rockburst, the occurrence mechanism of which remains unclear. Through the method of combining theory with practice, this paper elucidated the mechanical mechanism of static creep rockburst of deep thick coal seam roadways, along with the CT inversion of its rockburst risk. Next, by establishing the creep model and three‐dimensional creep formula under static conditions, it was observed that the main conditions for the unstable creep of deep thick coal seam roadway were high stress and thick coal seam. In addition, by analyzing the unstable creep failure process of surrounding rock in static roadways, it was found that the weakening of surrounding rock strength and stress relief were the reasons for starting rockburst and reducing impedance. The mechanical conditions of creep rockburst caused by stress superposition in weak areas of the roadway under static conditions were proposed, and the criterion of rockburst possibility was given. Finally, according to the characteristics of spontaneity and time delay of such a rockburst disaster, the static creep rockburst evaluation of thick coal seam roadway before mining was achieved by CT inversion, and the research conclusions were thoroughly verified. [ABSTRACT FROM AUTHOR]

A dynamic coupled elastoplastic damage model for rock-like materials is proposed. The model takes unified strength theory as the strength criterion. To characterize the different damage between compression and tension, two damage variables both in compression and in tension are introduced into the model. The former is represented by the generalized shear plastic strain and volumetric plastic strain and the latter is expressed with the generalized shear plastic strain. Furthermore, the model takes the strain rate effect into account to reflect the strength enhancement under dynamic loading. Because of the difference in plastic hardening between compression and tension, a modified hardening function is adopted. At the same time, the volume strain from HJC model is modified to be consistent with one of continuum mechanics. The developed model is numerically implemented into LS-DYNA with a semi-implicit algorithm through a user-defined material interface (UMAT). The reliability and accuracy of the developed model are verified by the simulation of four basic experiments with different loading conditions. The proposed model was found to be applicable to different mechanical behaviors of rock-like materials under static and dynamic loading conditions. [ABSTRACT FROM AUTHOR]

In statistical process control (SPC), the ratio of two normal random variables (RZ) is a valuable statistical indicator to be taken as the charting statistic. In this work, we propose a triple exponentially weighted moving average (TEWMA) chart for monitoring the RZ. Additionally, the variable sampling interval (VSI) strategy has been adopted to different control charts by researchers. With the application of this strategy, the VSI-TEWMA-RZ chart is then developed to further improve the performance of the proposed TEWMA-RZ chart. The run length (RL) properties of the proposed TEWMA-RZ and VSI-TEWMA-RZ charts are obtained by the widely used Monte-Carlo (MC) simulations. Through the comparisons with the VSI-EWMA-RZ and the VSI-DEWMA-RZ charts, the VSI-TEWMA-RZ chart is statistically more sensitive than the VSI-EWMA-RZ and the VSI-DEWMA-RZ charts in detecting small and moderate shifts. Moreover, it turned out that the VSI-TEWMA-RZ chart has better performance than the TEWMA-RZ chart on the whole. Furthermore, this paper illustrates the implementation of the proposed charts with an example from the food industry. [ABSTRACT FROM AUTHOR]

In this study, based on the example of the ground vibration damage response of a thick and hard rock layer fracture type mine quake, and by applying the theories of mine pressure, rock mechanics and vibration energy principle, the concept of "vibration damage boundary" of mine quake ground, which uses particle vibration velocity to evaluate the vibration damage, is proposed. In addition, the quantitative prediction method of the ground vibration damage boundary is preliminarily established. The research results reveal that the elastic deformation of the fixed support end of the thick and hard rock layer structure in the stope is the main energy source for the formation of mine quakes, and that the particle vibration velocity caused by the propagation of focal energy to the ground can reasonably reflect the response degree of vibration damage. The proposed prediction method considers the "instantaneous" motion characteristics of mining thick and hard rock layer and the dynamic load effect of "mine quakes." The method can deepen our understanding of mining ground damage prediction, and increase the reliability of ground damage boundary prediction. Finally, the results are used to predict the ground vibration damage boundary of limestone primary fracture in the longwall 16101 face of the Fuping Coal Mine. [ABSTRACT FROM AUTHOR]

In many fields such as baking industry and cosmetic factory, the ratio of two normal random variables (RZ) is one of the key quality characteristics that needs to be monitored. In this paper, we study the properties of three double exponentially weighted moving average (DEWMA) schemes for monitoring the RZ. The run length (RL) properties, average run length (ARL) and standard deviation of run length (SDRL), and charting parameters of the proposed DEWMA RZ schemes are simulated for different correlation parameter between the two normal variables. These numerous simulation results are presented in tables and figures to make comparisons with the existing exponentially weighted moving average (EWMA) RZ scheme. The comparisons show that the proposed DEWMA RZ schemes are more effective than the EWMA RZ in detecting small changes. Additionally, the proposed three one-sided DEWMA RZ schemes' properties are compared in detail. A food industry example details the implementation of the proposed RZ schemes. [ABSTRACT FROM AUTHOR]

• Adopting a Durkheim-Bernsteinian approach to explain how a strongly framed moral system is established to promote performance. • Discussing the limitations of Bourdieu's and Foucault's frameworks to specify the moralities of Chinese schooling. • Understanding the operation of Chinese schooling through the lens of collective cultural beliefs in society. • Depicting how rituals for high-achieving students serve to facilitate commitment, while disengaging low-achieving students. This paper contributes to the discussion on how Chinese 'unpromising' pedagogic practices featured with strong framing over teacher-student relations contribute to students' educational involvement. Based on semi-structured interviews with 120 students from 4 secondary schools in Eastern China, this qualitative study employs Bernstein's concept of the 'regulative order' to examine the regulative dimension of schooling inscribed in school rituals. The Bernsteinian approach offers both an internal perspective on specific configurations of school rituals and an external perspective on socio-cultural meanings attached to them. The present study finds that the regulative order in China's schooling comes to be in a double-faced position. On the one hand, the regulative order imbued with the notion of 'impersonality', enacted through consensual rituals that make explicit authority relationships, serves as a 'semiotic mediator' in effecting a desirable separation from home and commitment to the school code. On the other hand, it imposes 'symbolic violence' on low-achieving students, through differentiating rituals which deepen existing academic divisions. It argues that the strongly framed regulative order is encapsulated within Confucian educational ideals and the distribution of its different aspects among students reflects a moral order characteristic with exam-oriented meritocracy in society. [ABSTRACT FROM AUTHOR]

Exponentially weighted moving average (EWMA) type charts are very popular and efficient in monitoring various kind of statistics. Much researches have been done on the EWMA X ¯ chart with known process parameters. But, in practice, the process parameters used to set the control chart limits are often unknown and they need to be estimated from different Phase I samples. Moreover, because the shape of the run length distribution for the EWMA X ¯ chart changes with the mean shift, the median run length (MRL) can serve as a good alternative to evaluate the performance of the EWMA X ¯ chart. In this article, we will investigate the conditional properties of the EWMA X ¯ chart with unknown process parameters based on the MRL metric. In order to investigate the chart's properties, the average MRL (AMRL) and the standard deviation of MRL (SDMRL) will be used together when the process parameters are unknown. To prevent too many lower in-control MRL values, the adjusted control limits of the MRL based EWMA chart are obtained by using a bootstrap type approach and the results show that the adjusted control limits can give a good tradeoff between the in-control and out-of-control MRL performances. [ABSTRACT FROM AUTHOR]

Rock dynamic constitutive model plays an important role in understanding dynamic response and addressing rock dynamic problems. Based on elastoplastic mechanics and damage mechanics, a dynamic constitutive model of rock coupled with elastoplastic damage is established. In this model, unified strength theory is taken as the yield criterion; to reflect the different damage evolution law of rocks under tension and pressure conditions, the effective plastic strain and volumetric plastic strain are used to represent the compressive damage variable and the equivalent plastic strain is used to represent the tensile damage variable; the plastic hardening behavior and strain rate effect of rocks are characterized by piecewise function and dynamic increase factor function, respectively; Fortran language and LS-DYNA User-Defined Interface (Umat) are used to numerically implement the constitutive model; the constitutive model is verified by three classical examples of rock uniaxial and triaxial compression tests, rock uniaxial tensile test, and rock ballistic test. The results show that the constitutive model can describe the dynamic and static mechanical behavior of rock comprehensively. [ABSTRACT FROM AUTHOR]

In high-quality processes, events related to non-quality rarely occur and the times between these events (TBE) is likely to follow a skewed distribution like the gamma distribution. In order to monitor TBE data, an Adaptive Exponential Weighted Moving Average (AEWMA) control chart is proposed in this paper. This chart is designed to perform well over a range of shifts instead of being only efficient for a particular shift. An extensive performance analysis shows that, for most shifts, the Average Run Length (ARL) of the proposed chart performs better than other already existing control charts. In order to help the quality practitioner, some guidelines for choosing the most effective scheme in practice are provided. Finally, an illustrative example of the proposed scheme is also presented. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

This study investigated the mechanism, prevention measures, and control methods for earthquake disasters typically occurring in mines with thick and hard rock strata. A mine stope with large faults and thick hard rock strata in Hebei Province was taken as the background study object. Then, theoretical analysis and numerical simulation methods were adopted in conjunction with field monitoring to explore how horizontal stress evolves in the thick and hard hanging roofs of such mines, potentially leading to mining earthquakes. Then, based on the obtained results, a mining design method was proposed to reduce the horizontal stress levels of earthquake mitigation. The results showed that, under the control of large faults, semiopen and semiclosed stopes with thick hard rock strata are formed, which cause influentially pressurized and depressurized zones during the evolution of the overburden movements and horizontal stress. It was determined that the stress concentrations mainly originated from the release and transfer of horizontal stress during the rock fractures and movements in the roof areas, which were calculated using a theoretical estimation model. The horizontal stress concentrations formed "counter torques" at both ends of the thick and hard strata, which prevented the support ending due to tensile failures. As a result, the limit spans were increased. This study proposed a mining strategy of using narrow working faces, strip mining processes, and reasonable mining speeds, which could effectively reduce horizontal stress concentrations and consequently prevent and control mining earthquakes. This study's research results were successfully applied to the mining practices in working face 16103. [ABSTRACT FROM AUTHOR]

As a useful tool in statistical process control (SPC), the exponential control chart is more and more popular for monitoring high‐quality processes. Considering both known and estimated parameter cases, the one‐sided exponential cumulative sum (CUSUM) charts are studied in this paper through a Markov chain approach. Because the shape of the run length (RL) distribution of the one‐sided exponential CUSUM charts is skewed and it also changes with the mean shift size and the number of Phase I samples used to estimate the process parameter, the median run length (MRL) is employed as a good alternative performance measure for the charts. The optimal design procedures based on MRL of the one‐sided exponential CUSUM charts with known and estimated parameters are discussed. By comparing the MRL performance of the chart with known parameters with the one of the chart with estimated parameters, we investigate the effect of estimated process parameters on the properties of the chart. Finally, an application is illustrated to show the implementation of the chart. [ABSTRACT FROM AUTHOR]

In statistical process control (SPC), t charts play a vital role in the monitoring of the process mean, especially when the process variance is unknown. In this paper, two separate upper-sided and lower-sided exponentially weighted moving average (EWMA) t charts are first proposed and the Monte Carlo simulation method is used to obtain their run length (RL) properties. Compared with the traditional one-sided EWMA t charts and several run rules t charts, the proposed charts are proven to have better performance than these competing charts. In addition, by adding the variable sampling interval (VSI) feature to the proposed charts, the new VSI one-sided EWMA t charts are shown to detect different shift sizes in the process more efficient than the chart without VSI feature. Finally, an example of a milk filling process illustrates the use of the charts. [ABSTRACT FROM AUTHOR]

Recent researches on the control charts with unknown process parameters have noticed the large variability in the conditional in-control average run length (ARL) performance of control charts, especially when a small number of Phase I samples is used to estimate the process parameters. Some research works have been conducted on the conditional ARL performance of different types of control charts. In this paper, by simulating the empirical distribution of the conditional ARL and especially using the exceedance probability criterion (EPC), we study the conditional ARL performance of the synthetic X¯ chart. Our results show that a large amount of Phase I samples is needed to obtain a specified EPC of the synthetic chart. For the available number of Phase I samples, the control limits of the synthetic chart are adjusted using the EPC method to improve its conditional in-control performance. It is shown that, for small mean shift sizes, a tradeoff should be made between the conditional in-control and out-of-control performances. For moderate to large shifts, the conditional performance of the synthetic chart using the adjusted control limits is generally satisfied. By comparing the results with the ones using the bootstrap approach, it can also be concluded that the conditional performances of both approaches are comparable. While the method proposed in this paper requires much less computation work than the bootstrap approach. [ABSTRACT FROM AUTHOR]

Synthetic‐type charts are efficient tools for process monitoring. They are easy to design and implement in practice. The properties of these charts are usually evaluated under the assumption of known process parameters. This assumption is sometimes violated in practice, and process parameters have to be estimated from different phase I data sets collected by different practitioners. This fact causes the between‐practitioners variability among the properties of the synthetic‐type charts designed for each practitioner. In fact, the shape of the run length distribution of the synthetic‐type charts changes with the mean shift size. As a good alternative, the median run length (MRL) metric is argued to evaluate the properties of different control charts. In this paper, the MRL is used as a measure of the synthetic X¯ chart's performance, and the conditional MRL properties of the synthetic X¯ chart with unknown process parameters are investigated. Both the average MRL (AMRL) and the standard deviation of MRL (SDMRL) are used together to investigate the chart's properties when the process parameters are unknown. If the available number of phase I samples is not large enough to reduce the variability of the in‐control MRL values to an acceptable level, a bootstrap‐type approach is suggested to adjust the control limits of the synthetic X¯ chart and to further prevent many unwanted lower in‐control MRL values. [ABSTRACT FROM AUTHOR]

Traditional process monitoring control charts (CCs) focused on sampling methods using fixed sampling intervals ( $ \mathrm {FSI} $ FSI s). The variable sampling intervals ( $ \mathrm {VSI} $ VSI s) scheme is receiving increasing attention, in which the sampling interval ( $ \mathrm {SI} $ SI ) length varies according to the process monitoring statistics. A shorter $ \mathrm {SI} $ SI is considered when the process quality indicates the possibility of an out-of-control (OOC) situation; otherwise, a longer $ \mathrm {SI} $ SI is preferred. The $ \mathrm {VSI} $ VSI multivariate exponentially moving average for compositional data ( $ \mathrm {VSI} $ VSI - $ \mathrm {MEWMA}\,\mathrm {CoDa} $ MEWMA CoDa ) CC based on a coordinate representation using isometric log-ratio ( $ \operatorname {ilr} $ ilr) transformation is proposed in this study. A methodology is proposed to obtain the optimal parameters by considering the zero-state ( $ \mathrm {ZS} $ ZS ) average time to signal ( $ \mathrm {ZATS} $ ZATS ) and the steady-state (SS) average time to signal ( $ \mathrm {SATS} $ SATS ). The statistical performance of the proposed CC is evaluated based on a continuous-time Markov chain ( $ \mathrm {CTMC} $ CTMC ) method for both cases, the $ \mathrm {ZS} $ ZS and the SS using a fixed value of in-control (IC) $ \mathrm {ATS}_0 $ ATS 0 . Simulation results demonstrate that the $ \mathrm {VSI} $ VSI - $ \mathrm {MEWMA}\,\mathrm {CoDa} $ MEWMA CoDa CC has significantly decreased the OOC average time to signal ( $ \mathrm {ATS} $ ATS ) than the $ \mathrm {FSI}\,\mathrm {MEWMA}\,\mathrm {CoDa} $ FSI MEWMA CoDa CC. Moreover, it is found that the number of variables (d) has a negative impact on the $ \mathrm {ATS} $ ATS of the $ \mathrm {VSI} $ VSI - $ \mathrm {MEWMA}\,\mathrm {CoDa} $ MEWMA CoDa CC, and the subgroup size (n) has a mildly positive impact on the $ \mathrm {ATS} $ ATS of the $ \mathrm {VSI} $ VSI - $ \mathrm {MEWMA}\,\mathrm {CoDa} $ MEWMA CoDa CC. At the same time, the $ \mathrm {SATS} $ SATS of the $ \mathrm {VSI} $ VSI - $ \mathrm {MEWMA}\,\mathrm {CoDa} $ MEWMA CoDa CC is less than the $ \mathrm {ZATS} $ ZATS of the $ \mathrm {VSI} $ VSI - $ \mathrm {MEWMA}\,\mathrm {CoDa} $ MEWMA CoDa CC for all the values of n and d. The proposed $ \mathrm {VSI} $ VSI - $ \mathrm {MEWMA}\,\mathrm {CoDa} $ MEWMA CoDa CC under steady-State performs effectively compared to its competitors, such as the $ \mathrm {FSI} $ FSI - $ \mathrm {MEWMA}\,\mathrm {CoDa} $ MEWMA CoDa CC, the $ \mathrm {VSI} $ VSI - $ T^2\,\mathrm {CoDa} $ T 2 CoDa CC and the $ \mathrm {FSI} $ FSI - $ T^2\,\mathrm {CoDa} $ T 2 CoDa CC. An example of an industrial problem from a plant in Europe is also given to study the statistical significance of the $ \mathrm {VSI} $ VSI - $ \mathrm {MEWMA}\,\mathrm {CoDa} $ MEWMA CoDa CC. [ABSTRACT FROM AUTHOR]

The exponentially weighted moving average (EWMA) chart is often designed assuming the process parameters are known. In practice, the parameters are rarely known and need to be estimated from Phase I samples. Different Phase I samples are used when practitioners construct their own control chart's limits, which leads to the "Phase I between-practitioners" variability in the in-control average run length (ARL) of control charts. The standard deviation of the ARL (SDARL) is a good alternative to quantify this variability in control charts. Based on the SDARL metric, the performance of the EWMA median chart with estimated parameters is investigated in this paper. Some recommendations are given based on the SDARL metric. The results show that the EWMA median chart requires a much larger amount of Phase I data in order to reduce the variation in the in-control ARL up to a reasonable level. Due to the limitation of the amount of the Phase I data, the suggested EWMA median chart is designed with the bootstrap method which provides a good balance between the in-control and out-of-control ARL values. [ABSTRACT FROM AUTHOR]

Abstract: Control charts are usually investigated under the assumption of known process parameters. In practice, however, the process parameters are rarely known and they have to be estimated from different Phase I data sets. The properties of control charts with estimated parameters are usually investigated with the unconditional average of the average run length. Control chart's performance is known to vary among practitioners because of the use of different Phase I data sets. Considering the between‐practitioners variability in control chart's performance, the standard deviation of the average run length is developed to reevaluate the properties of the synthetic X ¯ chart with estimated parameters. Because of the limited amount of Phase I data in practice, the bootstrap method is used as a good adjustment technique for the synthetic X ¯ chart's parameters. [ABSTRACT FROM AUTHOR]

A common assumption for most control charts is the fact that the process parameters are supposed to be known or accurately estimated from Phase I samples. But, in practice, this is not a realistic assumption and the process parameters are usually estimated from a very limited number of samples that, in addition, may contain some outliers. Recently, a median chart with estimated parameters has been proposed to overcome these issues and it has been investigated in terms of the unconditional Average Run Length (ARL). As this median chart with estimated parameters does not take the 'Phase I between-practitioners' variability into account, in this paper, we suggest to revisit it using the Standard Deviation of the ARL as a measure of performance. The results show that this Standard Deviation of the ARL-based median chart actually requires a much larger amount of Phase I data than previously recommended to sufficiently reduce the variation in the chart performance. Due to the practical limitation of the number of the Phase I data, the bootstrap method is recommended as a good alternative approach to define new dedicated control chart parameters. [ABSTRACT FROM AUTHOR]

The variable sample size (VSS) [ABSTRACT FROM AUTHOR]

Measurement errors often exist in quality control applications. In this paper, the performance of the synthetic ... chart is investigated when measurement errors exist using a linearly covariate error model. It is shown that the performance of the synthetic ... chart is significantly affected in the presence of measurement errors. The effect of taking multiple measurements for each item in a subgroup on the performance of synthetic N X chart is also investigated in this paper. An example is provided in order to illustrate the application of the synthetic ... chart with measurement errors. [ABSTRACT FROM AUTHOR]

Much research has been conducted on two-sided Exponentially Weighted Moving Average (EWMA) control charts, while less work has been devoted to the one-sided EWMA charts. Traditional one-sided EWMA charts involve resetting the EWMA statistic to the target whenever it falls below or above the target, or truncating the observations above or below the target and further applying the EWMA statistic to the truncated samples. In order to further improve the performance of traditional one-sided EWMA mean ( X ¯ ) charts, this paper studies the performance of the Modified One-sided EWMA (MOEWMA) X ¯ charts to monitor a normally distributed process. The Monte-Carlo simulation method is used to obtain the zero- and steady-state Run Length ( R L ) properties of the proposed control charts. Through extensive simulations and comparisons with other charts, it is shown that the proposed MOEWMA X ¯ charts compare favorably with some existing competing charts. Moreover, by attaching the variable sampling intervals (VSI) feature to the MOEWMA X ¯ charts, it is shown that the VSI MOEWMA charts outperform the corresponding charts without the VSI feature. Finally, a real data example from manufacturing process shows the implementation of the proposed one-sided charts. [ABSTRACT FROM AUTHOR]

• Uneaten feed pellets were detected in real time from underwater images. • The YOLO-V4 network is improved by modifying the feature map, DenseNet and de-redundancy. • The average precision is improved by 27.21%, and the amount of computation is reduced by approximately 30%. • More scientific feeding strategies can be formulated based on the detected uneaten feed pellets. In aquaculture, the real-time detection and monitoring of feed pellet consumption is an important basis for formulating scientific feeding strategies that can effectively reduce feed waste and water pollution, which is a win-win scenario in terms of economic and ecological benefits. However, low-quality underwater images and extremely small targets present great challenges to feed pellet detection. To overcome these challenges, this paper proposes an uneaten feed pellet detection model using an improved You Only Look Once (YOLO)-V4 network for aquaculture. The specific implementation methods are as follows: (1) The feature map responsible for large-scale information in the original YOLO-V4 network is replaced by a finer-grained YOLO feature map by modifying the connection mode of the feature pyramid network (FPN) + path aggregation network (PANet). (2) The residual connection mode in CSPDarknets is modified via a DenseNet, which further improves the feature reuse and the network performance. (3) Finally, a de-redundancy operation is carried out to reduce the complexity of the YOLO-V4 network while ensuring the detection accuracy. Experimental results in a real fish farm showed that the detection accuracy is better than that of the original YOLO-V4 network, and the average precision is improved from 65.40% to 92.61% (when the intersection over union is 0.5), for an increase of 27.21%. Additionally, the amount of computation is reduced by approximately 30%. Therefore, the improved YOLO-V4 network can effectively detect underwater feed pellets and is applicable in actual aquaculture environments. [ABSTRACT FROM AUTHOR]

The adaptive exponential weighted moving average (AEWMA) monitoring technique has recently received increasing attention as a robust alternative requiring no knowledge of the actual shift magnitudes. In this paper, we develop a discrete state nonparametric AEWMA chart based on the Wilcoxon signed‐rank statistics. The major characteristic of this monitoring scheme is that it takes into account the discrete nature in terms of the statistics being used as well as the chart structure design. Moreover, an accurate evaluation of the chart's statistical properties is provided using an appropriate Markov chain approach. Simulation results show that this AEWMA signed‐rank scheme performs robustly across a diverse variety of distributions, and it can also provide an effective performance for detecting both small and large shifts. Finally, a real data example is cited for showing practical implications of our monitoring scheme. [ABSTRACT FROM AUTHOR]

Many control charts have been developed for monitoring the time between adverse events (TBE) to improve the quality of processes. In practice, the decrease in the TBE mean usually implies a deterioration of the process, while the increase indicates an improvement of the process. In this paper, an improved lower‐sided EWMA control chart is developed based on the power of the TBE observations to detect the decreasing TBE mean. Furthermore, an optimization model is developed to design the proposed EWMA chart, including the determination of the power and smoothing parameters to ensure the best overall performance. Simulation studies show the proposed EWMA chart is best among several charts for monitoring small shifts, and performs better than most alternative methods in detecting moderate shifts. Moreover, the in‐control performance of the proposed method with parameter estimation is studied via many numerical simulations. Finally, a real data example is given to further illustrate the application and sensitiveness of the improved EWMA chart. [ABSTRACT FROM AUTHOR]

The usual practice in Statistical Process Monitoring (SPM) techniques assumes that the data distribution is known and the related parameters are accurately estimated. In practice, the underlying distribution and its parameters are rarely known, and control charts need to be constructed with parameters being estimated. Such issues have recently received an increasing attention in evaluating the properties of both parametric and nonparametric charts. However, the same study is seldom conducted for the control charts based on the data‐driven tools. In this paper, we investigated the in‐control performance of a nonparametric control chart based on the Support Vector Data Description (SVDD) theory. More specifically, we discuss the conditional effect of the training Phase‐I samples on the Phase‐II efficiency when different distributions are considered. Simulation results show that the conditional performance of the SVDD‐based chart can be strongly affected by the Phase‐I samples. It this situation, adjusted control limits with a specific number of available training sample is suggested. [ABSTRACT FROM AUTHOR]

The Poisson distribution assumption often arises in several industrial applications for modeling defects or nonconformities. In this work, we investigate the one‐ and two‐sided performance of a new adaptive EWMA (exponentially weighted moving average)‐type chart for monitoring Poisson count data. An appropriate discrete‐state Markov chain technique is provided to compute the exact ARL (average run length) properties. Moreover, comparative studies are conducted to demonstrate the higher sensitivity of the proposed chart in the detection of shifts with various magnitudes. Advices on how to select the appropriate chart parameters are provided and an illustrative numerical example is proposed. [ABSTRACT FROM AUTHOR]

In order to monitor the process variance, this paper proposes a combined upper-sided synthetic S2 chart for monitoring the process standard deviation of a normally distributed process. This combined upper-sided synthetic S2 chart comprises a synthetic chart and an upper-sided S2 chart. The design and performance of the proposed chart are presented, and the steady-state average run length comparisons show that the combined upper-sided synthetic S2 chart outperforms the standard synthetic S2 chart as well as several run rules S2 charts, especially for larger shifts in the process variance. [ABSTRACT FROM AUTHOR]

Space‐filling and projective properties are probably the two most important features in computer experiment. The existing research works have tried to develop different kinds of sequential Latin hypercube design (LHD) to meet these two properties. However, most if not all of them cannot simultaneously ensure these two properties in their versions of sequential LHD. In this paper, we propose a novel sequential LHD that can simultaneously meet the space‐filling and the projective properties at each stage. A search algorithm is employed to find how many design points should be added in each stage to ensure the projective property; and the "Maximin" criterion is used to meet the space‐filling property. Two kinds of examples for low dimension and higher dimension are presented to illustrate how these sequential sampling processes are realized. The proposed method can be applied to the areas where computationally expensive simulations are involved. [ABSTRACT FROM AUTHOR]

The Adaptive Exponentially Weighted Moving Average (AEWMA) chart is known to combine the Shewhart and the classical EWMA schemes in a smooth way. Its performance has been investigated under the assumptions that the data are free from outliers and the chart's parameters are known or can be accurately estimated from in-control historical samples. However, there are many situations where the process parameters (a) are estimated from a very limited number of samples (b) they can potentially contain unexpected outliers. Therefore, in this article, we develop an AEWMA median chart with known and estimated parameters to monitor the mean value of a normal process. Taking the 'Phase I between-practitioners variability' into account, both the Average of () and the Standard Deviation of the () are used to evaluate the conditional effect of the number of Phase I samples on the Phase II performance. Using a Markov Chain approach, it is shown that (a) the performance of the proposed AEWMA median chart is seriously affected when parameters are estimated compared with the known-parameter case, and (b) it requires a large amount of Phase I data to reduce the variation in the in-control distribution up to a reasonable level. Therefore, a bootstrap-based design approach is applied here and, the performance of the AEWMA median chart is compared with that of the existing Shewhart and EWMA median charts. The comparative results show that the AEWMA median chart represents a good alternative to achieve a reasonable balance for various shift sizes. [ABSTRACT FROM AUTHOR]

In quality control applications, the control chart is a powerful tool but its performance is adversely affected by the contamination from either the inspector or the measuring device leading to measurement errors. In this paper, we investigate the performance of the AEWMA median chart with measurement errors, and a methodology is proposed to obtain the optimal parameters by considering a linearly covariate error model. Several figures and tables show that, with the existence of measurement errors, the efficiency of the AEWMA median chart can be strongly affected, but this negative effect can be compensated by taking multiple measurements at each sample point. Comparisons with the Shewhart and the classical EWMA schemes confirm the superiority of the AEWMA scheme for detecting a wide range of shifts in the case of precise and imprecise data. An example is provided to illustrate the use of the AEWMA median chart with measurement errors. [ABSTRACT FROM AUTHOR]

Camouflaged object, similar to the background, shows indistinct boundaries and low-contrast features, which brings great challenges to the detection task. Moreover, existing models still suffer from coarse object boundaries. Motivated by the complementary relationship between boundaries and camouflaged object regions, we propose an alternate guidance network named AGNet for better interaction between them. Specifically, we first propose feature selective module to select high discriminative features and simultaneously filter out noisy background features. The proposed AGNet follows a locate and refine manner, where multi-scale convolution is applied to expand receptive field for accurate initial coarse localization. Finally, a novel alternate guidance module is designed and embedded into each side-output to refine the previous localization progressively. Contributed by it, the complementary characteristic between the region and boundary features can be well captured, which is beneficial to obtain more complete detection. Experimental results on five COD datasets prove the effectiveness of our model, and it is superior to existing state-of-the-art models in object accuracy and boundary accuracy. [ABSTRACT FROM AUTHOR]

Due to the large-scale variation in objects in practical scenes, multi-scale representation is of critical importance for salient object detection (SOD). Recent advances in multi-level feature fusion also demonstrate its contribution in consistent performance gains. Different from the existing layer-wise methods, we propose a simple yet efficient split-guidance convolution block to improve the multi-scale representation ability at a granular level in this paper. Specifically, the input feature is first split into different subsets; each of them is guided by all the subsets in front of it, in this way to increase the range of receptive fields for each network layer. By embedding it into each side-output stage of the encoder, we build a unified decoder for both RGB SOD and RGB-D SOD. Experimental results on five RGB datasets, five RGB-D datasets and three RGB-T datasets demonstrate that the proposed method without any attention mechanisms and other complex designs performs favorably against state-of-the-art approaches and also shows advantages in simplicity, efficiency and compactness. [ABSTRACT FROM AUTHOR]

Salient object detection is still very challenging especially in images with complex or cluttered background. In this paper, we present an efficient and discriminative framework to address it. In specially, a discriminative similarity metric is first proposed by measuring the chi-square distance in a new constructed feature space. Then, we apply it to calculate a background based coarse saliency map by introducing distribution prior to remove foreground noises in the image boundaries. Based on manifold ranking, a robust saliency propagation mechanism is further developed to highlight salient object and simultaneously suppress background region by setting appropriate sink points. Finally, several simple refinement techniques are utilized to generate pixel-wise and smooth saliency maps. Extensive experimental results show the superior performance of the proposed method in terms of different evaluation metrics. In addition, the proposed framework can be also applied to the existing saliency propagation methods for significant performance boosting. We also believe that it is a good choice for subsequent applications based on the achieved high performance and acceptable computational overhead. [ABSTRACT FROM AUTHOR]

Exponentially weighted moving average (EWMA) control charts for time-between-events (TBE) are commonly suggested to monitor high-quality processes for the early detection of process deteriorations. In this study, an enhanced one-sided EWMA TBE scheme is developed for rapid detection of increases or decreases in the process mean. The use of the truncation method helps to improve the sensitivity of the proposed scheme in the process mean detection. Moreover, by taking the effects of parameter estimation into account, the proposed scheme with estimated parameters is also investigated. Both the average run length (ARL) and standard deviation of run length (SDRL) performances of the proposed scheme with known and estimated parameters are studied using the Markov chain method, respectively. Furthermore, an optimal design procedure is developed for the recommended one-sided EWMA TBE chart based on ARL. Numerical results show that the proposed optimal one-sided EWMA TBE chart is more sensitive than the existing optimal one-sided exponential EWMA chart in monitoring both upward and downward mean shifts. Meanwhile, it also performs better than the existing comparative scheme in resisting the effect of parameter estimation. Finally, two illustrative examples are considered to show the implementation of the proposed scheme for simulated and real datasets. [ABSTRACT FROM AUTHOR]

The bedding and the true stress state have a great effect on the seepage and mechanical properties of coal. In this study, the seepage experiments of coal with different bedding angles were conducted by a true triaxial apparatus. The influences of bedding and stress states on the deformation, seepage, energy, and fracture cracks of coal are discussed. The results indicated that, when the intermediate principal stress is consistent with the bedding dip direction, there is a reversal effect of the intermediate principal strain. While the phenomenon that the intermediate principal strain is smaller than the minimum principal strain after the failure, when the minimum principal stress is consistent with the bedding dip direction. With the increasing in bedding angle (within the range of angle studied in this paper), the peak stress of coal decreases, while the overall permeability and residual strength of coal increases, and the sensitivity of permeability to stress increases. In the SS-A, the peak stress of θ = 30° and 60° were 11.52% and 28.96% lower than that of θ = 0°, while the residual strength increased by 15.11% and 32.25%, respectively. With the increase of bedding angle, the dissipation energy increases. When the bedding angle of coal is large, the main failure mode is shear slip along the bedding plane. However, in the near horizontal bedding, the crack of coal mainly presents X-type conjugate shear slip failure along π/4 angle. The study on the mechanical seepage of coal under different bedding angles and true triaxial stress is helpful to further understand the deformation and gas migration and evolution of coal under different types of coal seams and different mining methods. [ABSTRACT FROM AUTHOR]

Traditional robust parameter design (RPD) is a useful tool for offline quality improvement, which is mainly applied to physical experiment. If the optimal setting for controllable factors is not desirable, the offline PRD cannot utilize the new‐obtained sample to update the optimal setting. In this paper, the offline RPD is extended to online PRD; and the background for RPD is enlarged from physical experiment to computer experiment, where the Kriging model is typically utilized to create a single response surface. In the process of building the incremental Kriging (IKriging), if the optimal setting is not desirable, it can be regarded as a new‐arrival sample with the online measurements of the noise factors to update the Kriging model. While constructing the response surface with the IKriging, it is updated according to the new‐arrival sample rather than the all (n+1) samples, substantially enhancing the efficiency of constructing the response surface. In the proposed IKriging based online RPD strategy, an appropriate algorithm is designed to numerically get the next optimal setting for the controllable factors, and a criterion is established to determine the next site for the noise factors to observe the response. By employing the IKriging model, the response surface can be online constructed efficiently, and furthermore the optimal setting for the controllable factor can be obtained immediately, meeting the requirement of online quality adjustment. The proposed methodology is confirmed using five examples, which illustrate that the underlying optimal settings can be found by utilizing the proposed IKriging based online RPD strategy for the computer experiment, and the IKriging based RPD method is preferable to existing online robust design methods. [ABSTRACT FROM AUTHOR]

RGB-D salient object detection aims at identifying the most attractive parts from a RGB image and its corresponding depth image, which has been widely applied in many computer vision tasks. However, there are still two challenges: (1) how to quickly and effectively integrate the cross-modal features from the RGB-D data; and (2) how to mitigate the negative impact from the low-quality depth map. The previous methods mostly employ a two-stream architecture which adopts two backbone network to process RGB-D data and ignore the quality of depth map. In this paper, we propose a guided residual network to address these two issues. On the one hand, we design a simpler and efficient depth branch only using one convolutional layer and three residual modules to extract depth features instead of employing a pre-trained backbone to handle the depth data, and fuse RGB features and depth features in a multi-scale manner for refinement with top-down guidance. On the other hand, we add adaptive weight to depth maps to control the fusion between them, which mitigates the negative influence of unreliable depth map. Experimental results compared with 13 state-of-the-art methods on 7 datasets demonstrate the validity of the proposed approach both quantitatively and qualitatively, especially in efficiency (102 FPS) and compactness (64.2 MB). [ABSTRACT FROM AUTHOR]

Exponential type charts are useful tools to monitor the time between events in high-quality processes with a low defect rate. Most studies on exponential charts are designed with the average run length (ARL) metric. The only use of ARL in the design of control charts is sometimes criticized because the shape of the run length (RL) distribution of control charts changes with the shift size. In fact, the RL distribution of the exponential exponentially weighted moving average (EWMA) chart is skewed, especially when the process is in-control. Hence, the median run length (MRL) serves as a more meaningful indicator. Moreover, in some situations, the shift size in the process is unknown in advance. Under this case, the expected median run length (EMRL) can be used as the metric. In this paper, the RL properties of both the upper- and lower-sided exponential EWMA charts are studied through a Markov chain approach. Two optimal design procedures are developed for one-sided exponential EWMA charts based on the MRL and EMRL, respectively. The choices of reflecting boundaries for one-sided exponential EWMA charts are discussed through many numerical studies. The MRL and EMRL performances of the one-sided exponential EWMA charts are investigated. [ABSTRACT FROM AUTHOR]

The classical cumulative SUM (CUSUM) chart is commonly used to monitor a particular size of the mean shift. In many real processes, it is assumed that the shift level varies within a range, and the exact level of the shift size is mostly unknown. For detecting a range of shift size, the dual-CUSUM (DC) and dual-Crosier CUSUM (DCC) charts are used to provide better detection ability as compared to the CUSUM and Crosier CUSUM (CC) charts, respectively. This paper introduces a new mixed exponentially weighted moving average (EWMA)-DCC (EDCC) chart to monitor process mean. In addition, AIB-based EWMA-DC (EDC) and EDCC charts (namely, AIB-EDC and AIB-EDCC charts) are suggested to detect shifts in the process mean level. Monte Carlo simulations are used to compute the run length (RL) characteristics of the proposed charts. A detailed comparison of the proposed schemes with other competing charts is also provided. It turns out that the proposed chart provides better performance than the counterparts when detecting a range of mean shift sizes. A real-life application is also presented to illustrate the implementation of the existing and proposed charts. [ABSTRACT FROM AUTHOR]

Several scholarly works intrinsically assume that the frequency and magnitude of events are two independent variables. However, in many practical situations, it is necessary to consider the dependence between these two characteristics of events. In this paper, two Smith–Adelfang–Tubbs (SAT) models, namely, the four‐ and the five‐parameter bivariate Gamma distributions (BGD) with a particular dependency parameter, are first reviewed. Then, a synthetic multivariate exponentially weighted moving average (synthetic MEWMA, or SMEWMA) type scheme is proposed to monitor the individual BGD observations (subgroups of size one) generated from those two specific SAT models. The Monte‐Carlo simulation method is developed to evaluate the run length (RL$\mathrm{RL}$) properties of the recommended SMEWMA BGD scheme in both the zero‐state and the steady‐state cases. Furthermore, we discuss the average run length (ARL) of the proposed SMEWMA BGD scheme with different design parameters, and then compare both the zero‐state and the steady‐state out‐of‐control ARL performances of the recommended SMEWMA BGD scheme with those of the classic MEWMA chart, the paired individual Gamma chart, and the MCUSUM chart. Simulation results suggest that the overall performance of the recommended SMEWMA BGD scheme is superior to the other comparative schemes. Finally, the implementation of the proposed SMEWMA BGD scheme is illustrated with a natural flood event dataset. [ABSTRACT FROM AUTHOR]

Various multivariate control charts (CCs) are applied to monitor compositional data (CoDa) processes post an isometric log-ratio (ilr) transformation aimed at assessing in-control or out-of-control (OOC) conditions. While optimal multivariate CCs effectively detect shifts in the overall mean vector, challenges arise when shifts occur in specific variables rather than the overall mean vector. This complexity in signal interpretation using traditional multivariate CCs prompts the need for improved approaches. To address this issue, this study introduces the application of a multilayer perceptron neural network (MLPNN) with back-propagation (BP) learning to interpret OOC signals in Hotelling's T 2 CC for CoDa. The proposed model aids practitioners in identifying atypical variables responsible for OOC situations instead of focusing solely on mean shifts. This capability to detect atypical variables enhances process control strategies, leading to more efficient industrial operations. The model's performance is assessed through two cases: one involving p = 3 -part CoDa and another with p = 5 -part CoDa. Shifts are introduced by altering variable means using various combinations. For comparison, the study also presents results obtained from multivariate data analysis using MLPNN with BP. The results demonstrate that the MLPNN consistently provides more accurate outcomes in the case of CoDa than multivariate data. Applying the ilr transformation improves the MLPNN's efficacy in accurately interpreting OOC signals within the CoDa domain. An application is reported to interpret the OOC signal during the working hours of machine operators in an industry. • The Hotelling T C 2 CC to CoDa using ilr transformation. • Analysis of OOC signal in T C 2 CC for CoDa using the BP technique in an MLPNN. • Identification of atypical variables responsible for OOC situations. • The performance assessment in diverse scenarios. [ABSTRACT FROM AUTHOR]