Statistical Quality Research Articles

Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

Objectives: To prepare the percentile-based acceptance sampling plans for the Exponentiated Inverse Kumaraswamy Distribution (EIKD) at a specific truncation time to inspect the defective lots corresponding to the desired acceptance level. Methods: The failure probability value is estimated using the cumulative probability function F(.) at time ‘t’ which is converted in terms of the scale parameter σ as 100th percentile using quantile function. The minimum size of the sample, Operating Characteristic (OC) and the minimum ratios are calculated for a required levels of consumer’s as well as producer’s risk. Findings: The percentile-based sampling plans are obtained through the minimal size of the sample ‘n’ under a truncated life test with a target acceptance number c in a manner that the proportion of accepting a lot which is not good (consumer’s risk) would not be more than . These values are calculated at The function of probability of acceptance for variations in the quality of a lot (OC function) L(p) of the sample plan are evaluated for the acceptance values of c=1 and c=5. The minimum ratio values are calculated for the acceptability of the lot with producers’ risk of using the sampling plan. Novelty: The modernity of this study is the designing of the acceptance sampling plans to a non-normal data using an asymmetrical distribution that has all three shape parameters. Also, the monitor of the implementation and suitability of statistical quality control and process control aspects using Exponentiated Inverse Kumaraswamy Distribution when compared to other asymmetrical distributions which has at least one scale parameter. Keywords: Sampling plans, Consumer's risk, Operating characteristics function, Truncated life tests, Producer's risk

Method for determining the number of defective products in a sample based on one measurement result

The most pressing problems in terms of production are increasing labor productivity and the quality of its results. One of the main ways to increase labor productivity is the development of new progressive technological processes. There are methods for controlling batches of products that can reduce the time of its control and increase labor productivity, which include methods of statistical quality control based on an alternative criterion. However, a sample from a batch of products must be fully controlled. When inspecting with one inspection tool, the sample inspection time is no less than the sum of the inspection times of all sample items. The purpose of this work is to develop a method for determining the number of defective products in a sample with one inspection tool, allowing to reduce the sample inspection time to the minimum possible. A method is proposed for determining the number of defective products of a certain class in a sample with one inspection tool using samples, which allows to signifi cantly reduce the sample inspection time. The samples are connected in parallel to the controlled products and are connected in series. All products in the sample with samples are controlled simultaneously, the total value of the controlled parameter is determined for them, and the number of defective products in the sample is determined by the formula. The effectiveness of the method is shown using the example of monitoring electromagnetic relays. The method makes it possible to reduce the sample inspection time to the minimum possible value, equal to the inspection time of one product.

New insights into estimating the cementation exponent of the tight and deep carbonate pore systems via rigorous numerical strategies

One of the main constituents of any reservoir characterization is an accurate forecast of water saturation, which is highly dependent upon the cementation exponent. Even though there have been a lot of studies, the most common correlations depend on total porosity. This means that they do not work as well in heterogeneous carbonate reservoirs, especially tight formations with total porosities less than 10%. This study aims to develop accurate and universal models for estimating the cementation exponent in deep and tight carbonate pore systems located in West Asia. Two heuristic algorithms, including the radial basis function neural network optimized by ant colony optimization (RBFNN-ACO) and gene expression programming (GEP), were employed to calculate the cementation exponent. To do this, we prepared a databank incorporating cementation exponents, total porosity, and various pore types. Then, the databank is classified into the test subset (for model prediction checking) and the train subset (for model construction). The reliability of the new recommended models is inspected by applying several statistical quality measures associated with graphical analyses. So, the consequences of the modeling disclose the large precision of the above-mentioned RBFNN-ACO, GEP Model-I, and GEP Model-II by average absolute percentage relative deviations (AAPRD%) of 6.28%, 6.39%, and 7.45%, respectively. Based on the outliers analysis, nearly 95% of the databank and model estimations are, respectively, valid and reliable. Additionally, the three input variables, including moldic porosity (with a + 70% impact value), non-fabric-selective dissolution (connected) porosity (with a -30% impact value), and interparticle porosity (with a -23% impact value), exhibit the main affecting parameters on the cementation exponent. Comparing current results with traditional literature correlations demonstrates the supremacy of the RBFNN-ACO model (AAPRD = 6.28% and root mean squared error (RMSE) = 0.17) over the examined literature correlations such as Borai’s equation (AAPRD = 12.30% and RMSE = 0.41). In addition, RBFNN-ACO can give better results than Borai’s Eqn. for tight (porosity less than 10%) and deep carbonate samples.

Integrated GIS-based and water quality index for evaluation of groundwater quality in the coastal slum settlements of Lagos, Nigeria

This study aimed to identify drinking water suitability through a statistical and water quality index (WQI) approach in coastal slum settlements in Lagos, Nigeria. A total of 250 borehole groundwater samples collected for drinking purposes during the wet (125) and dry (125) seasons were analysed for their physical and chemical properties from 2019 to 2020. The physical and chemical characterisation of the region was conducted based on the correlation matrix, scree plot, PCA, Q-mode HCA, and ROC curve to identify the types of weathering, the influence of rock on precipitation and evaporation, and types of reactions that affect groundwater composition. The analytical mean concentration results revealed that SO4, Cl, TH, NO3, TDS, and PO4 surpassed the USEPA and WHO permissible limits in both seasons. The WQI results demonstrate that 7.6% and 6.7% of water samples fall into the excellent category, while 12.4% and 11.5% are moderately tolerable. In contrast, for both seasons, >100% of the samples fell into the unsuitable drinking category across SA1-SA5, SB1-SB5, SC1-SC5, SD1−SD5, and SE1−SE5. Groundwater quality mainly deteriorates due to anthropogenic activities and climatic variability. The spatial variation map indicates that groundwater quality is primarily affected during the wet season and, to a lesser extent, in a few slums during the dry season. Seawater influx in coastline areas has been identified as the main factor threatening the quality and availability of groundwater resources. As a result, the groundwater quality is mostly poor to unsuitable, and this study confirms its unsuitability for drinking. Hence, this study serves as a guide for effective action in sustainable groundwater management.

New Sine Inverted Exponential Distribution: Properties, Simulation and Application

The New Sine Inverted Exponential Distribution, a new distribution model with just one parameter, is suggested in this study. The suggested model has several statistical qualities and reliability properties that have been constructed and explored. The MLE estimations of the parameters were determined using R's adequacy model package. To calculate the bias of the model parameter and the root mean square error, a simulation study was done. The simulation study revealed that the proposed model is well-behaved. The findings also showed that the suggested model outperforms the current listed models on two real datasets when performance was compared.

La necesidad de la cultura y el aseguramiento de la calidad estadística: experiencia de la AGR

This article describes the process through which the General Auditor's Office of the Republic (AGR), in compliance with a constitutional mandate and aiming to strengthen its capacities, obtained certification for the quality of its statistical operation, which verifies and evaluates the management of territorial comptroller offices. The AGR relied on the Technical Standard for the Quality of the Statistical Process NTC PE 1000:2020, issued by DANE, the leader of the National Statistical System (SEN); the first global standard to establish quality requirements for generating statistics, as well as other statistical guidelines and standards. The challenges faced by the entity in each phase of implementation are detailed. With this experience of integrating the statistical process into its Management System, the AGR makes a methodological contribution that can be replicated by other fiscal control bodies, aiming to promote statistical culture and implement measures to ensure statistical quality.

Deli River Water Quality Control In Medan City Using Statistical Methods Quality Control

Clean water is a type of water-based resource that is of good quality and is commonly used by humans for consumption or in carrying out daily activities. Clean water quality that meets standards/quality is very difficult to obtain because river water quality has been polluted by various kinds of waste from various human activities, so that the potential impact on river quality decreases both in terms of quantity and quality. 70% of the Deli River pollution is solid and liquid waste, domestic waste, industrial waste, and along the Deli River it has affected the quality of the river water. To quantitatively identify air quality, the Statistical Quality Control method can be used. Statistical quality control is a collection of strategies, techniques, and actions taken to ensure that they produce a quality product. The aim of this research is to determine the control of the water quality of the Deli River in Medan City using Statistical Quality Control. Based on the data obtained, the water quality standards of the Deli River in the Sumatra II River Basin Agency from January 2023 - December 2023 have not been statistically controlled because there are several data samples that are out of control. Then, Deli River water quality control was carried out based on graphic control using SQC (Statistical Quality Control). The results of quality control using SQC show that SQC provides different controls, because in SQC TDS control on data on controlled 3 times, while the and R data on DO, the and R data on and and R data for fatty oil are controlled.

Lost in translation: Implementation of the right to a translator through the use of machine translators in the light of EU and Polish Law

Both national and EU law provide for the right of an accused person to receive essential procedural documents in a language they understand and to participate in the proceedings in the presence of an interpreter. The need to implement these procedural guarantees raises several problems, such as the limited availability of interpreters and the cost to the State. This prompts the search for other solutions to implement the indicated individual rights. This article aims to answer the question of the admissibility and legitimacy of using machine translators to implement the right to an interpreter for defendants in criminal proceedings, and to indicate the opportunities and risks associated with the use of AI-based systems in this regard. The article presents the result of a linguistic, systematic and purposive interpretation of the relevant provisions of national laws and the provisions of Directive 2010/64/EU. Formal-dogmatic and statistical methods were used. The results of research into the quality of machine translations and statistics on the costs of translations are presented. The results support the recognition of the admissibility and legitimacy of the use of machine translators in criminal proceedings in order to implement the indicated rights. The text presents possible ways of applying these solutions in judicial practice and formulates a demand to the Ministry of Justice to begin work on the programme without delay. However, currently, both law enforcement and justice authorities can use publicly available machine translation software.

Intelligent Detection and Odor Recognition of Cigarette Packaging Paper Boxes Based on a Homemade Electronic Nose.

The printing process of box packaging paper can generate volatile organic compounds, resulting in odors that impact product quality and health. An efficient, objective, and cost-effective detection method is urgently needed. We utilized a self-developed electronic nose system to test four different cigarette packaging paper samples. Employing multivariate statistical methods like Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Statistical Quality Control (SQC), and Similarity-based Independent Modeling of Class Analogy (SIMCA), we analyzed and processed the collected data. Comprehensive evaluation and quality control models were constructed to assess sample stability and distinguish odors. Results indicate that our electronic nose system rapidly detects odors and effectively performs quality control. By establishing models for quality stability control, we successfully identified samples with acceptable quality and those with odors. To further validate the system's performance and extend its applications, we collected two types of cigarette packaging paper samples with odor data. Using data augmentation techniques, we expanded the dataset and achieved an accuracy rate of 0.9938 through classification and discrimination. This highlights the significant potential of our self-developed electronic nose system in recognizing cigarette packaging paper odors and odorous samples.

Geometry-driven and dark-matter-sustained Milky Way rotation curves with Gaia DR3

ABSTRACT Thanks to Gaia DR2, we proved for the first time that a general relativistic Milky Way rotation curve is statistically indistinguishable from its state-of-the-art dark matter analogue. Those results supported the ansatz that gravitational dragging can explain the observed flatness of the Milky Way rotation curve with a consistent radial matter density profile. To challenge again such a scenario, we select 719 143 young disc stars within |z| < 1 kpc and up to R ≃ 19 kpc from Gaia DR3 providing a much larger sample of high-quality astrometric and spectrophotometric data of unprecedented homogeneity. This sample comprises 241 918 OBA stars, 475 520 RGB giants, and 1705 Cepheides that we use to fit, as with DR2, both a classical velocity profile model, i.e. with a dark matter halo, and a general relativistic analogue derived from a dust disc-scale metric. Once more, further corroborating our earlier findings, both models are found to explain, with similar statistical quality, the new observed rotational velocities derived from different combinations of the selected sets of stars belonging to the disc of our Galaxy. The geometrical effect is found to drive the velocity profile from 10 kpc outwards, while being responsible for ∼30–37 per cent of this profile already at the Sun distance, similarly to the halo contribution in the classical model. This confirms our previous results on the contribution of Einstein’s geometry and pushes to further investigate the role of General Relativity in tracing the Milky Way rotation curve; notably, the origin of this gravitational dragging remains undetermined, necessitating a dedicated in-depth exploration.

A new statistical-quality-control methodology for panel line monitoring in shipyards

The construction of cruise ship hulls is a complex process that involves various stages: it begins with the fabrication of panels, which involves marking, cutting, and shaping metal plates of considerable length, followed by the welding of rigid structural components onto these panels. To minimize delays and cost overruns, it is crucial to detect any anomalies early on and rectify them through appropriate repair work. Therefore, real-time conformity verifications and effective Statistical Quality Control (SQC) methodologies are necessary. This paper proposes a novel SQC methodology, specifically tailored for monitoring the panel line in cruise-ship shipyards. This methodology, while adopting a traditional standardized p control chart with samples of variable size, integrates two original aspects: (i) it accounts for the significant level of customization and specific quality characteristics inherent in the different panels and (ii) it rigorously considers the measurement uncertainty associated with the large-volume metrology instruments (such as state-of-the-art total stations, laser trackers or laser scanners) used for conformity verification, following the ISO 14253-1:2017 standard. The methodology is exemplified through a real-world case study, providing practical insights into its application.

Research on Reform Measures of Labor Wage Statistics

Under the background of the continuous development of our country's market economy system, the internal personnel system of public institutions has also undergone obvious changes. In combination with the actual situation, labor wage statistics is an important part of the internal personnel management system of public institutions in nature, and its statistical quality will have a very direct impact on the overall operation efficiency of public institutions. Based on this, this paper conducts an in-depth study on the status quo and reform measures of labor wage statistics in public institutions, hoping to play a certain role in the development of relevant work. With the deepening of economic and cultural integration, the scope of wushu culture industry is more and more extensive. Factors such as the degree of association and quality among industries are affected by the external ecosystem and change with the change of industry content. The external ecosystem is composed of talent flow, knowledge flow, capital flow, information flow and material flow, which can be divided into four levels. The first is the talent system, which is the key factor for the sustainable development of the martial arts cultural industry.

Does Central Statistical Monitoring Improve Data Quality? An Analysis of 1,111 Sites in 159 Clinical Trials

BackgroundCentral monitoring aims at improving the quality of clinical research by pro-actively identifying risks and remediating emerging issues in the conduct of a clinical trial that may have an adverse impact on patient safety and/or the reliability of trial results. This paper, focusing on statistical data monitoring (SDM), is the second of a series that attempts to quantify the impact of central monitoring in clinical trials.Material and MethodsQuality improvement was assessed in studies using SDM from a single large central monitoring platform. The analysis focused on a total of 1111 sites that were identified as at-risk by the SDM tests and for which the study teams conducted a follow-up investigation. These sites were taken from 159 studies conducted by 23 different clinical development organizations (including both sponsor companies and contract research organizations). Two quality improvement metrics were assessed for each selected site, one based on a site data inconsistency score (DIS, overall -log10P-value of the site compared with all other sites) and the other based on the observed metric value associated with each risk signal.ResultsThe SDM quality metrics showed improvement in 83% (95% CI, 80–85%) of the sites across therapeutic areas and study phases (primarily phases 2 and 3). In contrast, only 56% (95% CI, 41–70%) of sites showed improvement in 2 historical studies that did not use SDM during study conduct.ConclusionThe results of this analysis provide clear quantitative evidence supporting the hypothesis that the use of SDM in central monitoring is leading to improved quality in clinical trial conduct and associated data across participating sites.

Territorial gaps on quality of causes of death statistics over the last forty years in Spain

BackgroundThe quality of the statistics on causes of death (CoD) does not present consolidated indicators in literature further than the coding group of ill-defined conditions of the International Classification of Diseases. Our objective was to assess the territorial quality of CoD by reliability of the official mortality statistics in Spain over the years 1980–2019.MethodsA descriptive epidemiological design of four decades (1980-, 1990-, 2000-, and 2010–2019) by region (18) and sex was implemented. The CoD cases, age-adjusted rates and ratios (to all-cause) were assigned by reliability to unspecific and ill-defined quality categories. The regional mortality rates were contrasted to the Spanish median by decade and sex by the Comparative Mortality Ratio (CMR) in a Bayesian perspective. Statistical significance was considered when the CMR did not contain the value 1 in the 95% credible intervals.ResultsUnspecific, ill-defined, and all-cause rates by region and sex decreased over 1980–2019, although they scored higher in men than in women. The ratio of ill-defined CoD decreased in both sexes over these decades, but was still prominent in 4 regions. CMR of ill-defined CoD in both sexes exceeded the Spanish median in 3 regions in all decades. In the last decade, women’s CMR significantly exceeded in 5 regions for ill-defined and in 6 regions for unspecific CoD, while men’s CMR exceeded in 4 and 2 of the 18 regions, respectively on quality categories.ConclusionsThe quality of mortality statistics of causes of death has increased over the 40 years in Spain in both sexes. Quality gaps still remain mostly in Southern regions. Authorities involved might consider to take action and upgrading regional and national death statistics, and developing a systematic medical post-grade training on death certification.

Analysis of Furniture Product Quality Control with Statistical Quality Control Methods and Failure Mode and Effect Analysis

PT. Tjakrindo Mas is a manufacturing company based in Indonesia that supports the government, industrial, public, and private sectors. Established in 1984, the company produces home furniture made from various types of wood. During the period from December 2023 to May 2024, the company faced production issues with its furniture products. According to production scheduling data, the furniture production intensity was high, operating 5 days a week. During this period, the highest production rate was for the 2 Door Glass Wardrobe, totaling 5,638 units. However, despite the high production volume, the defect rate for the 2 Door Glass Wardrobe was also high, with 498 defective units, representing a defect rate of 8.83%, which exceeds the company's tolerance standard. The objective of this study is to assess the quality of the Glass Wardrobe product at PT. Tjakrindo Mas and to propose improvements to enhance the product quality. Observations identified that the highest Risk Priority Number (RPN) was associated with the close side rail rupture defect, caused by the operator not being careful when installing the close side rail to the cabinet body, and the work methods used not in accordance with the Standard Operating Procedure (SOP). Recommendations for quality control proposals based on the high RPN value of FMEA Close Side Rail Rupture is to provide supervision and guidance to workers, and Provide briefing to operators about methods that are in accordance with the standard operating procedures (SOP) used by the company.

Analisis Pengendalian Kualitas Produk Raja Kripik’s Di Kabupaten Sigi

This study aims to determine and analyze the quality control of banana chips in an effort to control the level of banana chip defects and whether the level of defects is within the control limits at Raja Kripik's IKM in Sigi Regency. Data collection methods using interviews, observation, and documentation. The data analysis technique uses the Statistical Quality Control (SQC) method using statistical tools in the form of check sheets and p-charts. The results of this study indicate that the product quality control carried out by Raja Kripik's is within the control limits because the value of the proportion of defects is smaller than the Upper Control Limit (UCL) value.

Assessing the interchangeability of linked scores in multivariable statistical analyses.

Using the lens of classical test theory, we examine a linkage's generalizability with respect to use in multivariable analyses, including multiple regression and structural equation modeling, rather than comparison of established subpopulations as is most common in the literature. To aid in this evaluation, we present a structural-equation-modeling based statistical method to examine the suitability of a given linkage for use cases involving continuous and categorical variables external to the linkage itself. Using the PROMIS® Parent Proxy and Early Childhood Global Health measures, we show that, although a high correlation between the scores (here, r = .829) may imply a general suitability for linking, a more detailed investigation of content, measurement structure, and results of the proposed methodology reveal important differences between the measures which can compromise interchangeability in certain use cases. In addition to the statistical quality of a linkage, users of linking methodology should also assess the question of whether the linkage is appropriate to apply to particular use cases of interest.

Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight.

Human tear fluid contains numerous compounds, which are present in highly variable amounts owing to the dynamic and multipurpose functions of tears. A better understanding of the level and sources of variance is essential for determining the functions of the different tear components and the limitations of tear samples as a potential biomarker source. In this study, a quantitative proteomic method was used to analyze variations in the tear protein profiles of healthy volunteers. High day-to-day and inter-eye personal variances were observed in the tear volumes, protein content, and composition of the tear samples. Several normalization and outlier exclusion approaches were evaluated to decrease variances. Despite the intrapersonal variances, statistically significant differences and cluster analysis revealed that proteome profile and immunoglobulin composition of tear fluid present personal characteristics. Using correlation analysis, we could identify several correlating protein clusters, mainly related to the source of the proteins. Our study is the first attempt to achieve more insight into the biochemical background of human tears by statistical evaluation of the experimentally observed dynamic behavior of the tear proteome. As a pilot study for determination of personal protein profiles of the tear fluids of individual patients, it contributes to the application of this noninvasively collectible body fluid in personal medicine.

PENERAPAN METODE STATISTICAL QUALITY CONTROL DAN FAULT TREE ANALYSIS PADA PROSES STERILISASI DI CV. PASIFIC HARVEST BANYUWANGI

The purpose of this research is to find out the application of Statistical Quality Control and Fault Tree Analysis methods to control the types of defects that occur during the sterilization process, find out the causes of their occurrence, and provide suggestions for improvement. The research methods used were research preparation (literature study), field observations, problem solving, interviews, data collection, data processing, and data analysis. Application of the Statistical Quality Control method to control the types of defects that occur by using the seven tools. While the application of the Fault Tree Analysis method is by making a fault tree and determining the minimum cut set then analyzing it quantitatively. The results of the fishbone diagram analysis found that there are 3 factors that cause defects in the sterilization process, namely machines, materials, and humans. Proposed improvements to reduce the level of defects that often occur, namely carrying out daily inspection and maintenance of the machine, the machine must be calibrated, carrying out more thorough checks on cans sent from suppliers, disciplining employees by holding briefings once a week, conducting training on how to handle them properly and correct every 3 months or 6 months to employees, the seamer operator monitors the time during the draining process to the seamer process, checks the seamer machine before using the production process so as not to hinder the can closing process, and performs temperature sensors on a monthly basisThe purpose of this research is to find out the application of Statistical Quality Control and Fault Tree Analysis methods to control the types of defects that occur during the sterilization process, find out the causes of their occurrence, and provide suggestions for improvement. The research methods used were research preparation (literature study), field observations, problem solving, interviews, data collection, data processing, and data analysis. Application of the Statistical Quality Control method to control the types of defects that occur by using the seven tools. While the application of the Fault Tree Analysis method is by making a fault tree and determining the minimum cut set then analyzing it quantitatively. The results of the fishbone diagram analysis found that there are 3 factors that cause defects in the sterilization process, namely machines, materials, and humans. Proposed improvements to reduce the level of defects that often occur, namely carrying out daily inspection and maintenance of the machine, the machine must be calibrated, carrying out more thorough checks on cans sent from suppliers, disciplining employees by holding briefings once a week, conducting training on how to handle them properly and correct every 3 months or 6 months to employees, the seamer operator monitors the time during the draining process to the seamer process, checks the seamer machine before using the production process so as not to hinder the can closing process, and performs temperature sensors on a monthly basis

The Quality Control Analysis Using Statistical Quality Control (SQC) Methods in Reducing Defective Muslim Clothing Products on CV. Mawaheejra

Introduction/Main Objectives: This study determines the quality control of CV. Mawaheejra, determine the factors causing product defects and the application of Statistical Quality Control (SQC) methods. Background Problems: CV. Mawaheejra has carried out control but the quality control is not optimal because of poor quality and errors often occur in the production process which causes product defects that not comply with the quality standards. Research Methods: This study uses a quantitative method. It carried data collection techniques through observation, interviews, documentation, and literature studies. Data analysis using Statistical Quality Control (SQC) methods of flowcharts, check sheets, Pareto charts, control charts, and fishbone diagrams. Finding/Results: Based on the results of research with check sheet aids found four types of defects. In the Pareto chart found the highest number of product disability percentage of 38.47%. From the control chart result, it found deviations because of the U control chart there are three points that exceed UCL and two points that exceed LCL. From the fishbone diagram, there are five factors that are most prominently caused by human and machine factors. Conclusion: Based on the results of the analysis, the company must conduct supervision of employees and machine maintenance to reduce product defects.