M.Phil / MS
Permanent URI for this collectionhttps://repository.cuilahore.edu.pk/handle/123456789/63
This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.
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Item Some New Insights of Exponential Weighted Moving Average Control Chart with Fuzzy Control Lenses(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2018) Muhammad Javed; SP16-RST-001; LHR TP 5249; Dr. Tajammal HussainStatistical process control (SPC) is an approaching path that analyzes processes despite the fact whether they are under statistical control or out of control. So, Control charts are commonly employed for this purpose. Possibly, sample data may possess some uncertainties occurring owing to systems of measurement and conditions of the surrounding environment, for this purpose fuzzy numbers or language variables are usable to seize such form of uncertainties. Thereby, the well-known control charts, exponentially weighted moving average control chart (EWMA) to univariate data are formed up under the environment that is fuzzy one. The fuzzy EWMA control charts (FEWMA) are also usable in order to detect minute changes in the data presented by fuzzy numbers. FEWMA lessens various mistaken and unreliable decisions by catering further flexibleness upon the control limits. As far as the production process is monitored and controlled by dint of FEWMA control chart.Item Development of Fuzzy X ̅-S Control Charts through incorporating Fuzziness in Conventional X ̅-S Control Charts(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2018) Nabila Ali; SP17-RST-006; LHR TP 5324; Dr. Tajammal HussainThe mission to progress the quality and productivity of products and services is spreading across the industry and services sectors. Statistical process control (SPC) is a methodology to monitor an ongoing process and to identify unusual patterns and to indicate the need for correction. The most common SPC tools to be used are control charts. Control charts indicate whether or not the process is stable and resulting quality improvement. Control charts help to distinguish between special and common causes of variation which may occur during manufacturing process and influence the quality of a product.Item Development of Modified MaxAEWMA Control Chart based on Auxiliary Information(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) Zainab Manzoor; SP19-RST-004; LHR TP 6536; Dr. Tajammal HussainGlobalizations and streamlined commerce have opened the entryway of worldwide open market rivalry that changed the organization of working together. Open rivalry has an extreme impact on neighborhood market makers and worldwide firms. From the earliest starting point, quality is considered as a pre-essential definitive component to choose items or administrations. Presently days, the associations put more into observing and improving the nature of the items to draw in more clients. Besides, the basic considering purchasers has changed now they request a higher caliber of items and administrations. Walter A. Shewhart (1920) presented the idea of Statistical Quality Control (SQC), which is a coordinator of the quality control field. The crucial target of SQC is to zero in on the nature of the assembling mechanism to accomplish the most noteworthy creation quality. As per Montgomery (2009) in statistical mechanism control, each made item is not the same as one and another due to normal inborn variety, however with unnoticeable variety. The vast majority of organizations are putting resources into the quality enhancements division to decrease squandered items. The decrease in changeability builds the benefit of association and fulfillment of clients by satisfying their needs. As observed from the shopper's conduct a high variety of items is unsuitable for them, consequently, the objective of associations is to create items by stable mechanism.Item Revisiting the Process Capability Indices (PCIs) for the Uni-variate Variable Control Charts by Incorporating the Concept of Fuzziness(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2019) Muhammad Usman Aslam; FA17-RST-001; LHR TP 5742; Dr. Tajammal HussainWith the passage of time and global development in the industrial world, the competition for the quality improvement of the manufactured product has also increased. To achieve the quality perfection goal the best utilized technique is quality control. The technique of quality control is merged with the statistical methods to obtain a reliable source for updating and improving the product’s quality and services, it also helps to maintain the actual quality standard. This combination of quality control with the statistical methods is called Statistical Quality Control (SQC). The concept of Statistical Quality Control (SQC) was introduced in 1924 by Dr. Shewhart who is well known as the father of quality control analysis. The principle objective of SQC is to focus on the quality of any organization and to achieve the optimum quality of production as well as services by using the sufficient statistical techniques. According to (Montgomery, 2009) any products quality depends upon its fittness for use and it is judged by the appropriate quality characteristics.Item Uncovering the Statistical Foundations of Bibliometric Techniques and Their Role in Exploring the Data Science Research Evolution(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Aleem Ahmad; CIIT/FA23-RST-001/LHR; Dr. Tajammal Hussain; LHR TP 9872Sceinometric and bibliometric techniques are widely used in assessing the quality and quantity of research production in all aspects. In sceinometrics techniques, we focus on evaluating the scientific progress in all fields of science, while in bibliometrics, which is basically is a subpart of sceinometrics, we mainly focus on the quality and quantity of the research production. Both techniques are very important for finding the current research trends. These techniques are widely used by many research-funded institutions, decision makers. and the government. These help them with research funding allocations and identify the emerging research areas. These techniques are very useful in evaluating the journal impact factor, ranking universities, countries, and enhancing research efficiency. Because all research production activity creates data so these techniques are very closely related to data science. In Data Science, we collect, analyze, and process the largest sets of research data. We can find its application in every field, such as healthcare, education, and environmental studies, etc. In this study, we are focusing on the statistical foundation of bibliometric techniques and see that what is their role in exploring the data science research field. Many statistical models, such as discriminant analysis, cluster analysis, and VOSviewer software, are used for viewing the scientific landscape of this research. The present research gives us in-depth insight into the progression and evolution of data science as a prominent research field, after using advanced bibliometric techniques on the dataset of all 4424 journal articles till 31 December 2023. This study concludes that data science is evolving and has a potential research domain.