An Assorted Design for Joint Monitoring of Process Parameters: An Efficient Approach for Fuel Consumption

Due to high fuel consumption, we face the problem of not only the increased cost, but it also affects greenhouse gas emission. This paper presents an assorted approach for monitoring fuel consumption in trucks with the objective to minimize fuel consumption. We propose a control charting structure for joint monitoring of mean and dispersion parameters based on the well-known max approach. The proposed joint assorted chart is evaluated through various performance measures such as average run length, extra quadratic loss, performance comparison index, and relative average run length. The comparison of the proposed chart is carried out with existing control charts, including a combination of X and S, the maximum exponentially weighted moving average (Max-EWMA), combined mixed exponentially weighted moving average-cumulative sum (CMEC), maximum double exponentially weighted average (MDEWMA), and combined mixed double EWMA-CUSUM (CMDEC) charts. The implementation of the proposed chart is presented using real data regarding the monitoring of fuel consumption in trucks. The outcomes revealed that the joint assorted chart is very efficient to detect different kinds of shifts in process behaviors and has superior performance than its competitor charts.Deanship of Scientific Research, King Saud University, King Fahd University of Petroleum and MineralsScopu

Online monitoring of climatic parameters: a statistical study about environmental changes in Qatar

Twentieth century has witnessed unprecedented changes in the climate whose profound effects are also observed on ecosystem and human life. The source of these changes are presumed to be increasing concentration of greenhouse gases which result into rise in temperature worldwide. Unwanted effects have also been observed in the Gulf region in terms of reduced but intensive and unpredictable rainfall, average increase in temperature, sea level rise, lack of drinking water and regular drought. Qatar, being a richest country whose economic growth depends on petroleum and natural gas industry, is paying focus on its environmental development programs, which is also a goal of recent national vision. In this study, we have focused on monitoring of temperature and rainfall pattern in Qatar through different control charting schemes, i.e., memory less (Shewhart) and memory type (EWMA and CUSUM) control charting structures; while time series analysis was performed for the period of 1990-2012. It has been observed that temperature have increasing trend while rainfall depicts decreasing trend in last decades. Furthermore, forecasting of average weather is made by memory type structures which may serve as principle tool in environmental development initiatives.qscienc

Monitoring non-parametric profiles using adaptive EWMA control chart

To monitor the quality of a process in statistical process control (SPC), considering a functional relationship between a dependent variable and one or more independent variables (which is denoted as profile monitoring) is becoming an increasingly common approach. Most of the studies in the SPC literature considered parametric approaches in which the functional relationship has the same form in the in-control (IC) and out-of-control (OC) situations. Non-parametric profiles, which have a different functional relationship in the OC conditions are very common. This paper designs a novel control chart to monitor not only the regression parameters but also the variation of the profiles in Phase II applications using an adaptive approach. Adaptive control charts adjust the final statistic with regard to information of the previous samples. The proposed method considers the relative distance of the chart statistic to the control limits as a tendency index and provides some outcomes about the process condition. The results of Monte Carlo simulations show the superiority of the proposed monitoring scheme in comparison with the common non-parametric control charts. 2022, The Author(s).The publication of this article was funded by Qatar National Library.Scopu

Multivariate Mixed EWMA-CUSUM Control Chart for Monitoring the Process Variance-Covariance Matrix

The dispersion control charts monitor the variability of a process that may increase or decrease. An increase in dispersion parameter implies deterioration in the process for an assignable cause, while a decrease in dispersion indicates an improvement in the process. Multivariate variability control charts are used to monitor the shifts in the process variance-covariance matrix. Although multivariate EWMA and CUSUM dispersion control charts are designed to detect the small amount of change in the covariance matrix but to gain more efficiency, we have developed a Mixed Multivariate EWMA-CUSUM (MMECD) chart. The proposed MMECD chart is compared with its existing counterparts by using some important performance run length-based properties such as ARL, SDRL, EQL, SEQL, and different quantile of run length distribution. A real application related to carbon fiber tubing process is presented for practical considerations. 2013 IEEE.This work was supported by the Deanship of Scientific Research (DSR) at the King Fahd University of Petroleum and Minerals (KFUPM) under Project IN171011.Scopu

On Phase-I monitoring of process location parameter with auxiliary information-based median control charts

A control chart is often used to monitor the industrial or services processes to improve the quality of the products. Mostly, the monitoring of location parameters, both in Phase I and Phase II, is done using a mean control chart with the assumption that the process is free from outliers or the estimators are correctly estimated from in-control samples. Generally, there are question marks about such kind of narratives. The performance of the mean chart is highly affected in the presence of outliers. Therefore, the median chart is an attractive alternative to the mean chart in this situation. The control charts are usually implemented in two phases: Phase I (retrospective) and Phase II (prospective/monitoring). The efficiency of any control chart in Phase II depends on the accuracy of control limits obtained from Phase I. The current study focuses on the Phase I analysis of location parameters using median control charts. We examined the performance of different auxiliary information-based median control charts and compared the results with the usual median chart. Standardized variance and relative efficacy are used as performance measures to evaluate the efficiency of median estimators. Moreover, the probability to signal measure is used to evaluate the performance of proposed control charts to detect any potential changes in the process. The results revealed that the proposed auxiliary information based median control charts perform better in Phase I analysis. In addition, a practical illustration of an industrial scenario demonstrated the significance of the proposed control charts, in which the monitoring of concrete compressive strength is emphasized.This research fund was supported by the National Science Foundation of China (No. 71774070).Scopu

On designing an assorted control charting approach to monitor process dispersion: an application to hard-bake process

The monitoring of process variability is an important feature to get optimal output from a process. Control charts are vital tools used for efficient process monitoring. The commonly used types of charts include Shewhart, cumulative sum and exponentially weighted moving average (EWMA) control charts. This study focuses on dispersion control charts using some efficient transformation for small and medium instabilities. We intend to propose an assorted method to monitor a range of disturbances in process dispersion, using the well-known max approach. We have used several measures to evaluate the suggested assorted control chart. Based on these measures, we have compared the proposed assorted method with many existing charts. The study proposal outperforms the existing counterparts in detecting various amounts of shifts in process dispersion. Finally, a real-life application of the proposed chart is demonstrated to monitor the flow width measurements in a hard-bake process.The work was partially sponsored by Deanship of Scientific Research (DSR), King Fahd University of Petroleum and Minerals, Dhahran 31261, through project # IN171007. Authors Nasir Abbas, Usman Saeed and Muhammad Riaz are thankful to King Fahd University of Petroleum and Minerals for providing excellent research facilities.Scopu

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A new hwma dispersion control chart with an application to wind farm data

Recently, a homogeneously weighted moving average (HWMA) chart has been suggested for the efficient detection of small shifts in the process mean. In this study, we have proposed a new one-sided HWMA chart to effectively detect small changes in the process dispersion. The run-length (RL) profiles like the average RL, the standard deviation RL, and the median RL are used as the performance measures. The RL profile comparisons indicate that the proposed chart has a better performance than its existing counterpart's charts for detecting small shifts in the process dispersion. An application related to the Dhahran wind farm data is also part of this study.Funding: This research work was supported by the Deanship of Scientific Research (DSR) at the King Fahd University of Petroleum and Minerals (KFUPM) under Project Number SB191030.Scopu

Bayesian Monitoring of Linear Profiles Using DEWMA Control Structures with Random X

The process structures of manufacturing industry are efficiently modeled using linear profiles. Classical and Bayesian set-ups are two well-appreciated schemes for designing control charts for the monitoring of process structures. Mostly in profiles monitoring the independent variables along with the process parameters are assumed fixed. There are manufacturing processes where these conditions may not hold. The advancement in technology and day-to-day changes in process structures caused the parametric uncertainty along with variability in explanatory variables. This paper considered the case of random X and assumes different conjugate and non-conjugate priors to handle parametric uncertainty using double exponentially weighted moving average (DEWMA) control charts. Three univariate DEWMA charts are designed for the monitoring of Y-intercepts, slopes, and error variances. The average run length criterion has been used to evaluate the proposed and competing charts. The wide spread relative study identifies that the proposed Bayesian DEWMA control charts are better than the competing charts based on early detection of out-of-control profiles, particularly for smaller value shifts. The Bayesian DEWMA charts using conjugate priors are the quickest in all as they take less sample points to show out-of-control profile. A case study has been considered to further justify the superiority of Bayesian DEWMA charts over competing charts. 2013 IEEE.The work of S. A. Abbasi was supported by the Qatar University under Project QUST-1-CAS-2018-41.Scopu

An Improved Control Chart for Monitoring Linear Profiles and its Application in Thermal Conductivity

In most of the manufacturing processes, we encounter different quality characteristics of a product and process. These characteristics can be categorized into two kinds; study variables (variable of interest) and the supporting/explanatory variables. Sometime, a linear relationship might exist between the study and supporting variable, which is called simple linear profiles. This study focuses on the simple linear profiles under assorted control charting approach to detect the large, moderate and small disturbances in the process parameters. The evaluation of the proposed assorted method is assessed by using numerous performance measures, for instance, average run length, relative average run length, extra and sequential extra quadratic losses. A comparative analysis of the proposal is also carried out with some existing linear profile methods including Shewhart_3, Hotelling's T{2} , EWMA_3, EWMA/R and CUSUM_3 charts. Finally, a real-life application of the proposed assorted chart is presented to monitor thermal management of diamond-copper composite. 2013 IEEE.This work was supported by the Deanship of Scientific Research (DSR) at King Fahd University of Petroleum and Minerals (KFUPM) under Grant SB191043.Scopu