Tahir Mahmood

• Doctor of Philosophy
• Assistant Professor (UK Lecturer) at University of the West of Scotland

The Statistical Process Control (SPC) toolkit is extensively utilized to identify variations in processes, with control charts serving as the most efficient and commonly employed instrument for real-time process monitoring. Control charts evaluate whether a process is stable or unstable, detecting special cause fluctuations. Monitoring process vari...

This study designs a statistical process control tool that effectively detects small and moderate shifts in process parameters, to address challenges in quality monitoring. The proposed control chart employs advanced statistical detection techniques to enhance sensitivity while reducing false alarms, thus improving detection performance in various...

Normal probability distribution is central to most statistical methods and their applications. In many real scenarios, the normality of the underlying phenomenon is not obvious. However, a deeper investigation can lead to normality through some useful links among various models. The current study aims to present one such approach to the Gaussian mo...

Electric energy production frequently uses combined cycle power plants (CCPPs) to handle peak loads. CCPPs must be continuously monitored for power performance to enhance the electrical output power. The electrical output datasets often show asymmetric behavior; therefore, the Birnbaum-Saunders (BS) distribution is one of the potential models for f...

Mortality modeling is critical for healthcare policy and resource allocation. Multilayer parameterization and static features are not needed for deep learning (DL) models. To enhance prediction accuracy, DL models like LSTM, Bi-LSTM, and GRU have shown promise. However, research on using DL models to mortality modeling remains restricted. Hence, th...

Statistical process control is always intrigued by the design of effective control charts for monitoring production processes and determining assignable causes of variations. It can be challenging to keep track of a positive asymmetric response variable while considering the impact of the input variables. The current work incorporates the Reparamet...

In the era of digitalization, the large availability of data and innovations in machine learning algorithms provide new potential to improve the prediction of energy efficiency in buildings. The building sector research in the Kingdom of Saudi Arabia (KSA) lacks actual/measured data-based studies as the existing studies are predominantly modeling-b...

Advancements in sensor technology have brought a revolution in data generation. Therefore, the study variable and several linearly related auxiliary variables are recorded due to cost-effectiveness and ease of recording. These auxiliary variables are commonly observed as quantitative and qualitative (attributes) variables and are jointly used to es...

Forecasting mortality rates is crucial for evaluating life insurance company solvency, especially amid disruptions caused by phenomena like COVID-19. The Lee–Carter model is commonly employed in mortality modelling; however, extensions that can encompass count data with diverse distributions, such as the Generalized Autoregressive Score (GAS) model...

Nowadays, manufacturers face intense pressure to maintain a high standard of quality. Due to the damage to machine components, manufacturing processes degrade over time, resulting in substandard products. Generally, statistical process control tools such as control charts aid in identifying patterns and trends indicative of process changes. This in...

High-dimensional data refers to a dataset that contains many variables or features, typically with many more features p ð Þ than observations n ð Þ (i.e. n < p). With technological advancements in sensors, high-dimensional data are becoming increasingly common in process-monitoring applications. Therefore, this study presents a comprehensive overvi...

Quality testing and monitoring advancements have allowed modern production processes to achieve extremely low failure rates, especially in the era of Industry 4.0. Such processes are known as high-yield processes, and their data set consists of an excess number of zeros. Count models such as Poisson, Negative Binomial (NB), and Conway-Maxwell-Poiss...

High-dimensional data, characterized by having more attributes or variables than observations, presents unique challenges in industrial operations surveillance. Traditional multivariate control charts, like Hotelling’s ${T^2}$ chart, perform adequately with lower-dimensional data. However, they often fail to detect variations in process means as da...

The study proposed and compared the biased estimators for the Poisson-Inverse Gaussian regression model to deal with correlated regressors. The limitations of each biased estimator are also discussed. Additionally, some biasing parameters for the Stein estimator are proposed. The performance of estimators is evaluated with the help of a simulation...

Ceramics are made up of water, clay, and powders. These are categorized as non-metallic and inorganic materials. It is revealed in the literature that Longquan celadon glaze had irregular cracks in glaze layers due to the relatively high content of N a2O. Therefore, it is necessary to monitor the influence of N a2O in the ceramic process. Control c...

In industries, quality monitoring tools are necessary for producing good quality products. Control charts are the most important tools for monitoring a single variable. Sometimes, there exists the explanatory variable (s) along with the study variable, which is linearly related, and monitoring them is called linear profiling. However, there is a st...

When product quality follows the Gamma distribution and is related to one or more covariate(s), then Gamma regression model (GRM) profiling will be used. The Gamma profiling is generally based on a maximum likelihood estimator (MLE). In GRM profiling, when two or more covariates are linearly related, the MLE-based GRM profiling is unsuitable. In th...

Background Anal cancer, mainly attributed to human papillomavirus (HPV) infection, is rising in prevalence among the general population in Pakistan. This study aimed to examine the knowledge, attitudes, and practices (KAP) towards anal cancer screening and HPV of the general population in Pakistan. Method We surveyed anal cancer KAP using social m...

Early detection of changes in the frequency of events is an important task in many fields, such as disease surveillance, monitoring of high-quality processes, reliability monitoring, and public health. This article focuses on detecting changes in multivariate event data by monitoring the time-between-events (TBE). Existing multivariate TBE charts a...

In this era of Industry 4.0, efficient and affordable monitoring solutions are needed for the surveillance of manufacturing/service operations. In general, memory-type control charts outperform memoryless control charts when it comes to determining the changes in location and dispersion parameters of symmetrically distributed processes. Before moni...

One important application of statistical models in the industry is statistical process control. Many control charts have been developed and used in the industry. They are easy to use but have been developed based on statistical principles. However, for today’s high-quality processes, traditional control-charting techniques are not applicable in man...

In statistical process control, the control charts are an effective tool to monitor the process. When the process is examined based on an exponential family distributed response variable along with a single explanatory variable, the generalized linear model (GLM) provides better estimates and GLM-based charts are preferred. This study is designed t...

In manufacturing systems, statistical process control (SPC) is used to detect unusual observations in the process. Most control charts are composed based on the normality assumptions of the observations. However, checking the normality assumption in multivariate control systems cannot be practical in real-life applications. As a result, we propose...

Nonparametric control charts are more practical tools for statistical process control (SPC), as they are robust in situations in which the underlying distribution is unknown. Comprehensibility and simplicity of exceedance statistics provide great convenience to analysts in multivariate SPC applications. By using the exceedance statistics, analysts...

Toxoplasmosis, a parasitic disease caused by Toxoplasma gondii, results in congenital disorders and miscarriages among livestock and humans worldwide. This systematic review and meta-analysis were conducted to determine the prevalence of T. gondii infection in sheep and goats in Pakistan from 2000 to 2020. We searched the PubMed, Scopus, EMBASE, an...

Fascioliasis is a parasitic infection that affects both livestock and humans. Understanding the distribution of Fasciola spp. can help the development of preventive measures to control fascioliasis. This systematic review and meta-analysis aimed to estimate the status of fascioliasis among livestock and humans in Pakistan between 2000 and 2020. Bas...

Toxoplasma gondii is an intracellular obligate parasite that causes toxoplasmosis, a zoonotic infection that affects warm-blooded animals and humans worldwide. To comprehensively characterize the disease condition in Pakistan for future reference, we ascertained the prevalence of Toxoplasma infection and predisposing factors in the Pakistani popula...

In the recent literature of process monitoring, homogeneously weighted moving average (HWMA) type control charts have become quite popular. These charts are quite efficient for early detection of shifts, especially of smaller magnitudes, in process parameters such as location and dispersion. A recent study pointed out a few concerns related to HWMA...

The COVID-19 pandemic affected the world through its ability to cause widespread infection. The Middle East including the Kingdom of Saudi Arabia (KSA) has also been hit by the COVID-19 pandemic like the rest of the world. This study aims to examine the relationships between meteorological factors and COVID-19 case counts in three cities of the KSA...

Control charts are widely used tool that provides quality inspectors with sensitive information for maintaining manufacturing process productivity. Numerous model‐based techniques have been presented in the literature to monitor industrial operations that focus on the normal response variable. However, non‐normal response results can occur as a res...

Innovations in technology assist the manufacturing processes in producing high-quality products and, hence, become a greater challenge for quality engineers. Control charts are frequently used to examine production operations and maintain product quality. The traditional charting structures rely on a response variable and do not incorporate any aux...

In many experiments, our interest lies in testing the significance of means from the grand mean of the study variable. Sometimes, an additional linearly related uncontrollable factor is also observed along with the main study variable, known as a covariate. For example, in Electrical Discharge Machining (EDM) problem, the effect of pulse current on...

The magnificent seven statistical process control (SPC) tools are commonly used to monitor the variation in the process. Control charts are the most efficient and real-time monitoring tool from the SPC toolkit. A control chart visually differentiates the effect of special or inherent cause variations and indicates the process as out-of-control when...

Multivariate charts for process dispersion detect changes in the variance-covariance matrix of a process. Most of the existing multivariate charts for monitoring the dispersion of individual observations were designed based on exponentially weighted moving average (EWMA) charting schemes. However, an alternative to the EWMA scheme is the cumulative...

The control charts are essential instruments that can impart crucial insights to quality controllers for maintaining the productivity of manufacturing processes. The conventional charting designs are based on a single study variable without exerting auxiliary information. Control charts derived from simple linear regression, generally with normalit...

Early detection of changes in the frequency of events is an important task, in, for example, disease surveillance, monitoring of high-quality processes, reliability monitoring and public health. In this article, we focus on detecting changes in multivariate event data, by monitoring the time-between-events (TBE). Existing multivariate TBE charts ar...

Advancement in technology brings a revolutionary change in the quality of the final product or items. Most of the manufacturing processes produce a large number of conforming items along with a few non-conforming items. For real-time monitoring of these highly efficient processes , monitoring of time-between-events is a well-known approach adopted...

In recent years, advancement in technology brought a revolutionary change in the manufacturing processes. Therefore, manufacturing systems produce a large number of conforming items with a small amount of non-conforming items. The resulting dataset usually contains a large number of zeros with a small number of count observations. It is claimed tha...

With the development of modern acquisition techniques, data with several correlated quality characteristics are increasingly accessible. Thus, multivariate control charts can be employed to detect changes in the process. This study proposes two multivariate control charts for monitoring process variability (MPVC) using a progressive approach. First...

Contact lenses are widely used for visual corrections. However, while wearing contact lenses, eyes typically face discomforts (itching, irritation, burning, etc.) due to foreign object sensation, lack of oxygen permeability, and tear film disruption as opposed to a lack of wetting agents. Eyes are also prone to ocular infections such as bacterial k...

In this industry 4.0 revolution, most of the manufacturing processes are equipped with the digital devices which are continuously recording the data. To monitor the quality of a manufacturing system, variable about number of conforming or nonconforming items is usually used and statistical analysis based on it is further utilized for developing the...

Statistical modeling of historical crash data can provide essential insights to safety managers for proactive highway safety management. While numerous studies have contributed to the advancement from the statistical methodological front, minimal research efforts have been dedicated to real-time monitoring of highway safety situations. This study a...

Toxicant testing is a major component of the environmental solution testing program. This test system aims to evaluate the sensitivity of the test species, evaluate comparability between laboratory test results, and classify possible variability sources such as healthy organisms, organism batches, laboratory water, and food quality changes. For the...

Background Across the globe, lockdowns have been enforced as a pandemic response to COVID-19. Such lockdown coupled with school closures and stay-at-home orders made women more vulnerable in terms of higher responsibility and spending more time with an abusive partner, if any. Methods This study investigates the situation of women during COVID-19...

Control chart is a useful tool to monitor the performance of the industrial or production processes. Control charts are mostly adopted to detect unfavorable variations in process location (mean) and dispersion (standard deviation) parameters. In the literature, many control charts are designed for the monitoring of process variability under the ass...

Control charts are commonly applied for monitoring and controlling the performance of the manufacturing process. Usually, control charts are designed based on the main quality characteristics variable. However, there exist numerous other variables which are highly associated with the main variable. Therefore, generalized linear model (GLM)-based co...

Coronaviruses are single-stranded RNA viruses that cause severe respiratory, enteric, and systemic infections in a vast range of hosts, including man, fish, mammals, and avian. Scientific interest has heightened on coronaviruses after the emergence of the 2019 novel Coronavirus (SARS-CoV-2). This review provides current perspectives on morphology,...

We review methods for monitoring multivariate time-between-events (TBE) data. We present some underlying complexities that have been overlooked in the literature. It is helpful to classify multivariate TBE monitoring applications into two fundamentally different scenarios. One scenario involves monitoring individual vectors of TBE data. The other i...

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 cal...

Linear profiles are quite popular in establishing relationships among different variables associated with each other in an ongoing process. Control charting methodologies for these linear profiles are used to monitor and improve the performance of a process. The commonly used Phase I methodologies of linear profiles are mostly based on simple rando...

Emerge in technology brought well‐organized manufacturing systems to produce high‐quality items. Therefore, monitoring and control of products have become a challenging task for quality inspectors. From these highly efficient processes, produced items are mostly zero‐defect and modeled based on zero‐inflated distributions. The zero‐inflated Poisson...

Cumulative sum control charts that are based on the estimated control limits are extensively used in practice. Such control limits are often characterized by a Phase I estimation error. The presence of these errors can cause a change in the location and/or width of control limits resulting in a deprived performance of the control chart. In this stu...

In SPC, the most effective and magnificent tool is the control chart. The structure of control charting schemes required the assumption that the process is free from disturbances with known parameters or correctly estimated from the in-control process. These assumptions need to full fill for monitoring location parameter with mean control charts. B...

A profile is a functional relationship, between two or more variables, used to monitor the process performance and its quality. The relationship may be linear or nonlinear depending upon the situation. Linear profiling methods with a fixed-effect model are commonly used under simple random sampling (SRS). In this article, we propose linear profiles...

In the modern era of digitalization, manufacturing industries needed monitoring methods to timely detect an abrupt change in the process. Control charts are widely used online monitoring method and used in several sectors for the surveillance of the process. Usually, control charts are developed for a single study variable, but there exists auxilia...

We review methods for monitoring multivariate time-between-events (TBE) data. We present some underlying complexities that have been overlooked in the literature. It is helpful to classify multivariate TBE monitoring applications into two fundamentally different scenarios. One scenario involves monitoring individual vectors of TBE data. The other i...

A profile is a functional relationship between two or more variables used to monitor the process performance and its quality. Sometimes, the aforementioned relationship is linear or nonlinear depending upon the situation. A monitoring method based on the linear profiles is known as linear profiling which is commonly used due to its simplicity and e...

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 monitor the shifts in the process covarian...

As product quality has increased rapidly in recent years, monitoring and control of products have become more and more difficult. The items were produced with zero defects, and zero‐inflated distributions are used to fit the defect count data. Recently, many studies were designed for the estimation and monitoring methods based on the zero‐inflated...

Control charts are often used for the monitoring of quality characteristics of interest. There may exist some other characteristics that are associated with the main quality characteristic. A model that quantifies the relationship between them is termed as a profile, for instance, the relation between charge and capacitance. The monitoring of the m...

Background: All-in-one station-based health monitoring devices are implemented in elder homes in Hong Kong to support the monitoring of vital signs of the elderly. During a pilot study, it was discovered that the systolic blood pressure was incorrectly measured during multiple weeks. A real-time solution was needed to identify future data quality...

Quality issue: All-in-one-station-based health monitoring devices are implemented in elder homes in Hong Kong to support the monitoring of vital signs of the elderly. During a pilot study, it was discovered that the systolic blood pressure was incorrectly measured during multiple weeks. A real-time solution was needed to identify future data qualit...

In many manufacturing industries, quality of an item depends on different characteristics and their relationship may be modeled by profiles. For instance, in photo-voltaic (PV) system, output voltage is dependent on the capacitance level of capacitors, used in the Z-source inverter. Control chart is a dynamic tool that works under two different pha...

In many industrial processes, the quality characteristic of interest has a relation (linear or non-linear) with other supporting variable(s). Simple linear profile is a well-known term used for the quality characteristic, which is linearly associated with another descriptive variable, and the monitoring of simple linear profile parameters (i.e., sl...

Control charts are the most popular tool of statistical process control for monitoring variety of processes. The detection ability of these control charts can be improved by introducing various transformations. In this study, we have enhanced the performance of CUSUM charts by introducing a link relative variable transformation technique. Link rela...

Monitoring of manufacturing, production or industrial processes through statistical process control (SPC) can improve the quality of products. Control chart is a significant tool of SPC which is used for the monitoring of abnormal changes in industrial process as well as in health, agricultural and other sectors. Usually, control charts are designe...

In industries, univariate control charts are applied to monitor single study variable (qualitative or quantitative) of the manufacturing process. Usually, there exist other variables that have linear relationship with study variable. For example; in tape production process, outlet concentration of the product is associated with inlet concentration...

Process monitoring is a continuous phenomenon and it needs careful attention for an improved quality of output. Location and dispersion parameters play a vital role in regulating every process and it requires a timely detection of any change in their stable behaviors. Nowadays, practitioners prefer a single charting setup that offers better ability...

Virtually, detection of shifts in dispersion parameter of the process is more valuable before monitoring the location parameter of the process. For the monitoring of dispersion parameter, S² chart is a common choice in the literature. In this study, we proposed a modified S²chart based on modified successive sampling (MSS) which is cost effective r...

Shewhart-Cucconi and Shewhart-Lepage are two nonparametric control charts used to monitor joint shifts in the process location and scale parameters. This study investigates impact of the light and heavy tailed distributions on the performance of these charts. The effect of reference and test samples is also a part of this study.

In many manufacturing processes, study variable is not the only quality characteristic, but there may exist some explanatory variable(s) that are associated with the study variable. This association may be linear or nonlinear depending on the nature of variables. The term profiling is used for such relationships among study and explanatory variable...

This study presents a relationship between two well‐known distributions, namely, geometric and binomial distributions. We will provide the statement of our result supported by its precise proof. In addition, we will give an illustrative example to explain the suggested relationship. We will indicate some industrial applications where the derived co...

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 o...

Nowadays, Linear profiles are more common because of their simplicity and coverage of more common scenarios. The term profiling is used for association among study and predictor variable(s). In this study, we have designed and investigated EWMA-3 chart under the different ranked set sampling strategies such as ranked set, median ranked set, extreme...

In many manufacturing processes, study variable is not the only quality characteristic but there may exist some explanatory variable(s) that are associated with the study variable. This association may be linear or non- linear depending on the nature of variables. The term pro�ling is used for such relationships among study and explanatory variable...

In this article, we have extended the design structures of dual auxiliary information-based control charts under a variety of sampling strategies and runs rules schemes. We have considered the cases of known and unknown skewed distributions by using the skewness correction (SC) method. The design structures under the skewness correction method are...

This current report intends to highlight the importance of considering background assumptions required for the analysis of real datasets in different disciplines. We will provide comparative discussion of parametric methods (that depends on distributional assumptions (like normality)) relative to non-parametric methods (that are free from many dist...

Usage of mobile phone is growing rapidly in all over the world and nowadays, mobile phones have advanced features. The concept of ringtone selection in the coming generation is increasing day by day. This study is conducted about the musical elements (tone color, rhythm, melody and tempo) of ringtone. The objective is to examine the elements that a...

Control charts are important statistical tool used to monitor fluctuations in the process location and dispersion parameters. The issues relating to the appropriate choice of control charts for the effective detection of process variability are addressed, and different control chart structures, such as Shewhart-type, exponentially weighted moving a...

The current study has been designed to investigate the relationship between unemployment and the different factors having impact on unemployment directly or indirectly. The basic purpose of the study is to check that either their effects are significant or insignificant. At first, normality, independence, homoscedasticity and autocorrelation are ch...

Gelling behaviour of a polysaccharide arabinoxylan isolated from Ispaghula, Plantago ovata was investigated and effect of different factors such as concentration of gelling agent, temperature, pH and compatibility with solvents were also studied. Medicated paracetamol and acelofenac gel were formulated by using arabinoxylan as gelling agent. These...

The purpose of the present study was to determine the prevalence of tick infestation in buffalo and goats of Punjab Province (District Sargodha), Pakistan. There were a total of twelve hundred buffalo and goats examined from October 2012 to September 2013 to determine the prevalence of ticks infestation. The results showed that the prevalence of ti...

The use of mobile in Pakistan is growing with fast speed. Pakistan ranks fifth in Asia in mobile phone users as more than hundred million people are using mobile phones in the country. The youth is playing a vital role in adopting the ways towards the advancement of technology. Mobile youth market in Pakistan is saturated. The objective of this stu...

Poverty alleviation is going to become the hot stack in the world. Many of the researchers and policy makers are engaged to over-come this problem. South Asian Association for Regional Cooperation (SAARC) consists of a rich topographic, climatic endowments and varia-tions. The region is blessed with cereals, fruits, ornamental, medicinal and staple...

Water is very essential part of life. But major problem in Pakistan is that about eighty percent of population does not have access to the pure drinking water. Especially in Sargodha region the underground water is highly polluted due to down flow of salts from the Salt Range as well as other minerals in that area. It is the reason that the maximum...

The composition of two macro-minerals (Ca and Na) was examined in soil and forages in two fields of District Sargodha, Pakistan. During win-ter and summer season, soil and forage samples were collected. In both seasons, Na was suffi-cient in soil and forages. As compared to the winter season, the Na and Ca levels in soil were considerably higher in...

The experimental site "Sial Morr Sugar mill, Dis-trict Sargodha" Punjab, Pakistan was selected to carry out present investigation. The forage sam-ples of Eragrostis pilosa, Dactyloctenium ae-gyptium, Parthenium hysterophorus and Calotro-pis procera were collected from the three sites held in this area. The forage samples were cleaned with distilled...

Pakistan's economy mainly depends on cotton crop, commonly known as white gold and then the textile sectors. These both sectors have made almost half of the Pakistan's manufacturing and related segments. Agriculture of Pakistan the main shareholder of the Pakistan's GDP that bear revealed comparative and competitive advantage in cotton lint and tra...