In this paper, we show that concept of Statistical Process Control tools was thoroughly examined and the definitions of quality control concepts were presented. This is significant because of it is anticipated that this study will contribute to the literature as an exemplary application that demonstrates the role of statistical process control (SPC) tools in quality improvement in the evaluation and decision-making phase.

This is significant because of this study is to investigate applications of quality control, to clarify statistical control methods and problem-solving procedures, to generate proposals for problem-solving approaches, and to disseminate improvement studies in the ready-to-wear industry. The basic Statistical Process Control tools used in the study, the most repetitive faults were detected and these faults were divided into sub-headings for more detailed analysis. In this way, it was tried to prevent the repetition of faults by going down to the root causes of any detected fault. With this different perspective, it is expected that the study will contribute to other fields.

We give consent for the publication of identifiable details, which can include photograph(s) and case history and details within the text (“Material”) to be published in the Journal of Quality Technology. We confirm that have seen and been given the opportunity to read both the Material and the Article (as attached) to be published by Taylor & Francis.

ABSTRACT For the release of pharmaceutical products into the drug market; most of the pharmaceutical companies depend on acceptance criteria - that are set internally, regulatory and/or pharmacopeially. However, statistical process control monitoring is underestimated in most quality control in cases; although it is important not only for process stability and efficiency assessment but also for compliance with all appropriate pharmaceutical practices such as good manufacturing practice and good laboratory practice, known collectively as GXP. The current work aims to investigate two tablet inspection characteristics monitored during in-process control viz. tablet average weight and hardness. Both properties were assessed during the compression phase of the tablet and before the coating stage. Data gathering was performed by the Quality Assurance Team and processed by Commercial Statistical Software packages. Screening of collected results of 31 batches of an antibacterial tablet - based on Fluoroquinolone -showed that all the tested lots met the release specifications, although the process mean has been unstable which could be strongly evident in the variable control chart. Accordingly, the two inspected processes were not in the state of control and require strong actions to correct for the non-compliance to GXP. What is not controlled cannot be predicted in the future and thus the capability analysis would be of no value except to show the process capability retrospectively only. Setting the rules for the application of Statistical Process Control (SPC) should be mandated by Regulatory Agencies.

This file contains Appendices for the article titled as "A Multiphase Acceptance Sampling Model by Attributes to Investigate the Production Interruptions in Batch Production within Tobacco Industry" published in International Journal of Quality & Reliability Management.

The dataset refers to the measurement of axes of Ti-6Al-4V cylindrical surfaces obtained by lathe turning. The machined surfaces were measured using a Coordinate Measuring Machine (CMM) and the axis of each cylinder was derived from the CMM measures.

The dataset consists of a MAT-file including the CMM measurements and a Matlab function “LoadData.m” to extract and convert the data into Cartesian coordinates.

All the details about the dataset can be found in:

Colosimo, B.M., Pacella, M. Analyzing the effect of process parameters on the shape of 3D profiles (2011) Journal of Quality Technology, 43 (3), pp. 169-195.DOI: 10.1080/00224065.2011.11917856 Pacella, M., Colosimo, B.M. Multilinear principal component analysis for statistical modeling of cylindrical surfaces: a case study (2018) Quality Technology and Quantitative Management, 15 (4), pp. 507-525.DOI: 10.1080/16843703.2016.1226710

ABSTRACT In this paper, a new software for Statistical Process Control (SPC) is proposed. The system, the so-called CEP Online, was developed based on statistical computing resources of well-known free softwares, such as HTML, PHP, R and MySQL under an online server with operating system Linux Ubuntu. The main uni and multivariate SPC tools are available for monitoring and evaluation of manufacturing and non-manufacturing production processes over time. Some advantages of the new software are: (i) low operational cost, since it is cloud-based, only needing a computer connected to the Internet; (ii) easy to use with great interaction with the user; (iii) it does not require investment in any specific hardware or software; (iv) real time reports generation on process condition monitoring and process capability. Thus, the CEP Online offers for SPC practitioners fast, efficient and accurate SPC procedures. Therefore, CEP Online becomes an important resource for those who have no access to non-free softwares, such as SAS, SPSS, Minitab and STATISTICA. To the best of our knowledge, the CEP Online is unique with respect to its characteristics.

This dataset provides analytical and other data in support of an analysis of lead and manganese in untreated drinking water from Atlantic and Gulf Coastal Plain aquifers, eastern United States. The occurrence of dissolved lead and manganese in sampled groundwater, prior to its distribution or treatment, is related to the potential presence of source minerals and specific environmental factors including hydrologic position along the flow path, water-rock interactions, and associated geochemical conditions such as pH and dissolved oxygen (DO) concentrations. A DO/pH framework is proposed as a screening tool for evaluating risk of elevated lead or manganese, based on the occurrence of elevated lead and manganese concentrations and the corresponding distributions of DO and pH in 258 wells screened in the Atlantic and Gulf Coastal Plain aquifers. Included in this data release are the Supplementary Information Tables that also accompany the Applied Geochemistry journal article: Table of details on construction and hydrologic position of wells (percent distance from outcrop and percent depth to well centroid) sampled in Atlantic and Gulf Coastal Plain aquifers, 2012 and 2013. Table of general chemical characteristic and concentrations of major and trace elements and calculated parameters for groundwater samples from wells in Atlantic and Gulf Coastal Plain aquifers, 2012 and 2013. Table of mineral saturation indices (SI) and partial pressures of CO2 (PCO2 ) and O2 (PO2) computed with PHREEQC (Parkhurst and Appelo, 2013) for 258 groundwater samples from wells in Atlantic and Gulf Coastal Plain aquifers, 2012 and 2013. Table of spearman's rank correlation coefficient (r) matrix of principal components (PC1-PC6) and chemical data for 258 groundwater samples from wells in Atlantic and Gulf Coastal Plain aquifers, 2012 and 2013. Table of results of blank analysis for major and trace elements analyzed for 258 groundwater samples from wells in Atlantic and Gulf Coastal Plain aquifers, 2012 and 2013. Table of criteria and threshold concentrations for identifying redox processes in groundwater (after McMahon and Chapelle, 2008). Table of principal components analysis model of major factors affecting the chemistry of groundwater samples from wells in Atlantic and Gulf Coastal Plain aquifers, 2012 and 2013.

Quarterly Journal of Economics Abstract & Indexing - ResearchHelpDesk - The Quarterly Journal of Economics is a peer-reviewed academic journal published by the Oxford University Press for the Harvard University Department of Economics. Its current editors-in-chief are Robert J. Barro, Lawrence F. Katz, Nathan Nunn, Andrei Shleifer, and Stefanie Stantcheva (Harvard University). It is the oldest professional journal of economics in the English language and covers all aspects of the field—from the journal's traditional emphasis on micro theory to both empirical and theoretical macroeconomics. According to the Journal Citation Reports, the journal has a 2015 impact factor of 6.662, ranking it first out of 347 journals in the category "Economics". It is generally regarded as one of the top 5 journals in economics, together with the American Economic Review, Econometrica, the Journal of Political Economy, and the Review of Economic Studies. The Quarterly Journal of Economics is the oldest professional journal of economics in the English language. Edited at Harvard University's Department of Economics, it covers all aspects of the field. QJE is invaluable to professional and academic economists and students around the world. Scope of the Journal The Quarterly Journal of Economics is the oldest professional journal of economics in the English language. Edited at Harvard University's Department of Economics, it covers all aspects of the field-from the journal's traditional emphasis on micro theory, to both empirical and theoretical macroeconomics. QJE is invaluable to professional and academic economists and students around the world. Impact Factor and Ranking Year Impact Factor Ssi: Economics 2020 15.563 1 out of 377 2019 11.375 1 out of 371 2018 11.775 1 out of 363 2017 7.863 1 out of 353 2016 6.662 1 out of 347 2015 5.538 2 out of 344 2014 6.654 1 out of 333 2013 5.966 3 out of 332 2012 5.278 2 out of 332 2011 5.920 2 out of 320 2010 5.940 2 out of 304 2009 5.647 2 out of 245 This information is taken from the Journal Citation Reports™ (Clarivate, 2021). Abstracting & Indexing Services The Quarterly Journal of Economics is covered by the following abstracting and indexing services: ABI-INFORM Book Review Digest Plus CAB Abstracts Coal Abstracts Criminal Justice Abstracts Current Contents: Social & Behavioral Sciences Current Index to Statistics Dietrich's Index Philosophicus Documentation in Public Administration EconLit Emerald Management Reviews Environmental RouteNet Environmental Sciences & Pollution Management Database Expanded Academic ASAP Family Index Historical Abstracts Human Resources Abstracts IBZ: International Bibliography of Periodical Literature Index of Economic Articles in Journals & Collected Volumes Index to Periodical Articles Related to Law International Bibliography of Humanities & Sociological Literature Leisure, Recreation, and Tourism Abstracts Leisure Tourism Database LexisNexis Operations Research - Management Science Peace Research Abstracts ProQuest Central Public Administration Abstracts Quality Control & Applied Statistics RePec Risk Abstracts SCOPUS Social Science Source Social Sciences Citation Index/Social SciSearch Social Sciences Index Social Work Abstracts Wilson Business Abstracts World Agricultural Economics & Rural Sociology Abstracts Zentralblatt MATH

Quarterly Journal of Economics Impact Factor 2024-2025 - ResearchHelpDesk - The Quarterly Journal of Economics is a peer-reviewed academic journal published by the Oxford University Press for the Harvard University Department of Economics. Its current editors-in-chief are Robert J. Barro, Lawrence F. Katz, Nathan Nunn, Andrei Shleifer, and Stefanie Stantcheva (Harvard University). It is the oldest professional journal of economics in the English language and covers all aspects of the field—from the journal's traditional emphasis on micro theory to both empirical and theoretical macroeconomics. According to the Journal Citation Reports, the journal has a 2015 impact factor of 6.662, ranking it first out of 347 journals in the category "Economics". It is generally regarded as one of the top 5 journals in economics, together with the American Economic Review, Econometrica, the Journal of Political Economy, and the Review of Economic Studies. The Quarterly Journal of Economics is the oldest professional journal of economics in the English language. Edited at Harvard University's Department of Economics, it covers all aspects of the field. QJE is invaluable to professional and academic economists and students around the world. Scope of the Journal The Quarterly Journal of Economics is the oldest professional journal of economics in the English language. Edited at Harvard University's Department of Economics, it covers all aspects of the field-from the journal's traditional emphasis on micro theory, to both empirical and theoretical macroeconomics. QJE is invaluable to professional and academic economists and students around the world. Impact Factor and Ranking Year Impact Factor Ssi: Economics 2020 15.563 1 out of 377 2019 11.375 1 out of 371 2018 11.775 1 out of 363 2017 7.863 1 out of 353 2016 6.662 1 out of 347 2015 5.538 2 out of 344 2014 6.654 1 out of 333 2013 5.966 3 out of 332 2012 5.278 2 out of 332 2011 5.920 2 out of 320 2010 5.940 2 out of 304 2009 5.647 2 out of 245 This information is taken from the Journal Citation Reports™ (Clarivate, 2021). Abstracting & Indexing Services The Quarterly Journal of Economics is covered by the following abstracting and indexing services: ABI-INFORM Book Review Digest Plus CAB Abstracts Coal Abstracts Criminal Justice Abstracts Current Contents: Social & Behavioral Sciences Current Index to Statistics Dietrich's Index Philosophicus Documentation in Public Administration EconLit Emerald Management Reviews Environmental RouteNet Environmental Sciences & Pollution Management Database Expanded Academic ASAP Family Index Historical Abstracts Human Resources Abstracts IBZ: International Bibliography of Periodical Literature Index of Economic Articles in Journals & Collected Volumes Index to Periodical Articles Related to Law International Bibliography of Humanities & Sociological Literature Leisure, Recreation, and Tourism Abstracts Leisure Tourism Database LexisNexis Operations Research - Management Science Peace Research Abstracts ProQuest Central Public Administration Abstracts Quality Control & Applied Statistics RePec Risk Abstracts SCOPUS Social Science Source Social Sciences Citation Index/Social SciSearch Social Sciences Index Social Work Abstracts Wilson Business Abstracts World Agricultural Economics & Rural Sociology Abstracts Zentralblatt MATH

SDRL values of robust estimators based on CUSUM- charts under G(2,1) environment when ARLO = 500.

This dataset is the result of a study on the quality of official datasets available for COVID-19. This study uses comparative statistical analysis to evaluate the measurement errors and improve the accuracy of COVID-19 official data collections namely “Chinese Center for Disease Control and Prevention (Chinese CDC)” reports, pdf report files of World Health Organization (WHO) and European Centre for Disease Prevention and Control (ECDC). The result is an improved data-set for the COVID-19 studies. More information can be found in this manuscript: “A study on the quality of Novel Coronavirus (COVID-19) official datasets”, published in the Statistical Journal of the IAOS (Journal of the International Association for Official Statistics).

Journal Of Management Research And Analysis Impact Factor 2024-2025 - ResearchHelpDesk - Journal of Management Research and Analysis is a Double-Blind Peer Review journal that provides a specialized academic medium and important reference for the encouragement and dissemination of research and practice in management research. JMRA carries theoretical and empirical papers, case studies, research notes, executive experience sharing, and review articles, and it aims at disseminating new knowledge in the field of different domain areas of management, information technology, and related disciplines. It provides a forum for deliberations and exchange of knowledge among academics, industries, researchers, planners and the practitioners who are concerned with the management, financial institutions, public and private organizations, as well as voluntary organizations. Our editorial policy is that the journal serves the profession by publishing significant new scholarly research in management discipline areas that are of the highest quality. Aim & Scope: Journal of Management Research and Analysis (JMRA) is a quarterly, international, refereed journal published with the aim to provide an online publishing platform for the academia, management researchers, and management students to publish their original works. It aims at getting together intellectuals with the dissemination of original research, new ideas and innovations and practical experience in the concerned fields on a common platform. It also aims at understanding, advancing and promoting the emerging global trends in learning and knowledge assimilation of management researches and imparting the same to the benefit of Industry and academia for further improvisation of education systems at national as well as global level and to evolve the participation of student fraternity in the on-going discussion on socially desirable economic, commerce and management issues. JMRA focuses on publishing scholarly articles from the areas of management, management principles, recent inventions in management, company management, financial management, human resources, accounting, marketing, management control systems, supply chain management, operations management, human resource management, economics, commerce, statistics, international business, information technology, environment, risk management, import-export management, logistics management, hospitality management, health and hospital management, globalization and related areas. Journal of Management Research and Analysis seeks original manuscripts that identify, extend, unify, test or apply scientific and multi-disciplinary knowledge concerned to the management field. The following types of papers are considered for publication: 1. Original research works in the above-mentioned fields. 2. Surveys, opinions, abstracts, and essays related to Operations research. 3. Few review papers will be published if the author had done considerable work in that area. 4. Case studies related to the management domain. Indexing Information: Index Copernicus, Google Scholar, UGC, Crossref etc.

ARL values of robust estimators based on CUSUM- charts in uncontaminated environment N(0,1) when ARLO = 500.

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ABSTRACT The anaerobic digestion (AD) operation complexity raise the importance of stability testing to verify whether the operating conditions are under control and whether the process is working as required. The current method of verifying process stability is by a range of the ratio between volatile fatty acidity and total alkalinity (VFA/ TA) within which stable conditions are brought about; these rates vary with the content of organic material. A few indicators as pH or constant biogas production are also used. Therefore, the aim of this study was to propose the use of Shewhart control chart for individual measures as a stability test for AD, as well as to demonstrate its use in poultry litter AD. The method showed to be advantageous since it standardizes a variation range for the process according to the average and verifies the stability by direct measures, such as organic material removal efficiency and biogas production.

SDRL values of robust estimators based on CUSUM- charts under Logistic(2,1) environment when ARLO = 500.

Parameter values for scenarios considered in the simulation, when the true data-generating process is UL distributed (in-control condition).

Parameter values for scenarios considered in the simulation, when the true data-generating process is beta distributed (in-control condition).

Values for CUSUM- charts in different scenarios with ARLO = 500.

Standardized variance of robust estimators in different scenarios.

ABSTRACT Statistical process control has been widely used in agricultural operations for monitoring and improving process quality. This study aims to evaluate the Shewhart and exponentially weighted moving average (EWMA) control charts to monitor the performance of an agricultural tractor–planter set. The design is completely randomized based on the assumptions of statistical process control and comprises two treatments: day and night shift treatments. The data to assess the performance of the tractor–planter set are collected during the day and night shifts and used to evaluate the operating speed, motor rotation, engine oil pressure and water temperature, and hourly fuel consumption. The dataset comprised 40 samples compiled from the frontal monitor column inside a tractor cab. It is concluded that both Shewhart and MMEP/EWMA control charts can be used to evaluate engine performance based on the quality indicator parameters investigated, regardless of the normality assumption of the datasets.