Search

In many situations, the quality of a process or product can be characterized by a functional relationship or profile. It is well-known that the independence assumptions of the error terms within or between profiles are not always valid and could be violated due to within or between profile autocorrelation. Since most of the process capability indices (PCIs) have been developed for simple linear profiles (SLPs) without considering autocorrelation, this paper provides some novel methods to analyze the capability of SLP under each of the two different autocorrelation effects separately, as well as the case where both autocorrelation effects are present. We assume that the first-order autoregressive AR(1) model explains the within- and between-profile autocorrelation in error terms. To evaluate the process capability, a new functional index called C p ‴ (P r o f i l e) is introduced for SLP with independent errors, and then it is modified to include the three possible cases of within, between, and simultaneous autocorrelation. The simulation results demonstrate that the proposed schemes outperform existing schemes regarding bias and mean square error (MSE) criteria. Moreover, bootstrap confidence intervals for the proposed index are obtained. Finally, an illustrative example in the chemical industry is used to demonstrate the applicability of the proposed method. [ABSTRACT FROM AUTHOR]

Designing and implementing appropriate pavement structures in the era of coexisting automated vehicles (AVs) and human-driven vehicles (HDVs) is a significant concern for researchers and road practitioners. This necessitates investigating the pavement performance subjected to the various loading distribution scenarios induced by different lateral movement patterns of AVs. It is known that the pavement layers' thickness and material influence pavement performance. This study used a finite element method (FEM) to model AVs' loading distributions and simulate the rutting performance of a full-depth flexible pavement structure constructed in different layers' thicknesses and materials. The results revealed that the layers' thickness and material contribution depend on the lane distribution scenario and the AVs' wander mode. In some AV scenarios, improving the layers' material and increasing the thickness could help reduce the pavement rutting damage compared to HDV scenarios, with the extent of this effect influenced by AVs' wander mode. [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 deployment of automated vehicles (AVs) with the gradual market penetration rate increase and different potential lateral movement patterns combined with the lane width effect would lead to different load distribution scenarios, impacting the pavement performance. This study compares pavement rutting damages induced by different load distribution scenarios by setting out different penetration rates (i.e. 0, 20, 40, 60, 80, and 100%), wander modes (i.e. zero-, normal-, uniform-time-, and uniform-frequency-wander), and lane widths (i.e. 3, 3.25, and 3.5 m). A finite element model of a full-depth flexible pavement was developed using ABAQUS software to evaluate the pavement rutting. The results showed that the significance level of differences between rutting damages induced by different wander modes and lane widths is substantially influenced by the AVs' penetration rate. For instance, in the higher penetration rates, the differences between the rutting performance of different wander modes are more significant than in the lower penetration rates. Furthermore, the lane width effect becomes more significant in the segregated scenario than in the integrated scenarios in normal- and uniform-wander modes. Accordingly, AVs' penetration rate is a decisive factor in the practical decision-making process in the wander mode determination and lane width design for AVs. [ABSTRACT FROM AUTHOR]

Control charts, which are one of the major tools in the Statistical Process Control (SPC) domain, are used to monitor a process over time and improve the final quality of a product through variation reduction and defect prevention. As a novel development of control charts, referred to as profile monitoring, the study variable is not defined as a quality characteristic; it is a functional relationship between some explanatory and response variables which are monitored in such a way that the major aim is to check the stability of this model (profile) over time. Most of the previous works in the area of profile monitoring have focused on the development of different theories and assumptions, but very little attention has been paid to the practical application in real-life scenarios in this field of study. To address this knowledge gap, this paper proposes a monitoring framework based on the idea of profile monitoring as a data-driven method to monitor the internet usage of a telecom company. By definition of a polynomial model between the hours of each day and the internet usage within each hour, we propose a framework with three monitoring goals: (i) detection of unnatural patterns, (ii) identifying the impact of policies such as providing discounts and, (iii) investigation of general social behaviour variations in the internet usage. The results shows that shifts of different magnitudes can occur in each goal. With the aim of different charting statistics such as Hoteling T2 and MEWMA, the proposed framework can be properly implemented as a monitoring scheme under different shift magnitudes. The results indicate that the MEWMA scheme can perform well in small shifts and has faster detection ability as compared to the Hoteling T2 scheme. [ABSTRACT FROM AUTHOR]