Statistical Control Research Articles

Transcranial Alternating Current Stimulation over Frontal Eye Fields Mimics Attentional Modulation of Visual Processing.

Attentional control over sensory processing has been linked to neural alpha oscillations and related inhibition of cerebral cortex. Despite the wide consensus on the functional relevance of alpha oscillations for attention, precise neural mechanisms of how alpha oscillations shape perception and how this top-down modulation is implemented in cortical networks remain unclear. Here, we tested the hypothesis that alpha oscillations in frontal eye fields (FEFs) are causally involved in the top-down regulation of visual processing in humans (male and female). We applied sham-controlled, intermittent transcranial alternating current stimulation (tACS) over bilateral FEF at either 10 Hz (alpha) or 40 Hz (gamma) to manipulate attentional preparation in a visual discrimination task. Under each stimulation condition, we measured psychometric functions for contrast perception and introduced a novel linear mixed modeling approach for statistical control of neurosensory side effects of the electric stimulation. tACS at alpha frequency reduced the slope of the psychometric function, resulting in improved subthreshold and impaired superthreshold contrast perception. Side effects on the psychometric functions were complex and showed large interindividual variability. Controlling for the impact of side effects on the psychometric parameters by using covariates in the linear mixed model analysis reduced this variability and strengthened the perceptual effect. We propose that alpha tACS over FEF mimicked a state of endogenous attention by strengthening a fronto-occipitoparietal network in the alpha band. We speculate that this network modulation enhanced phasic gating in occipitoparietal cortex leading to increased variability of single-trial psychometric thresholds, measurable as a reduction of psychometric slope.

A variable sampling interval EWMA control chart for urinary tract infections data

Control chart is an important method in Statistical Process Control, which is used to study how a process changes over time. The exponential distribution is one of the commonly used models for fitting data, especially in areas such as component life, aviation accidents, or health-care processes. In order to further improve the sensitivity of the control chart, we propose an exponentially weighted moving average control chart with a variable sampling interval scheme, denoted as VSIEWMA-T control chart, for monitoring exponentially distributed quality characteristics (e.g. Urinary Tract Infections data). In this paper, the average time to signal property of the proposed control chart is investigated using the Markov chain method. In addition, parameter optimization algorithms for known or unknown shift levels are provided. Subsequently, numerical analysis shows that the proposed control chart outperforms other competitive control charts. Finally, an example of urinary tract infections data is provided for illustration.

Monitoring the Dynamic Networks of Stock Returns with an Application to the Swedish Stock Market

AbstractIn this paper, two approaches for measuring the distance between stock returns and the network connectedness are presented that are based on the Pearson correlation coefficient dissimilarity and the generalized variance decomposition dissimilarity. Using these two procedures, the center of the network is determined. Also, hierarchical clustering methods are used to divide the dense networks into sparse trees, which provide us with information about how the companies of a financial market are related to each other. We implement the derived theoretical results to study the dynamic connectedness between the companies in the Swedish capital market by considering 28 companies included in the determination of the market index OMX30. The network structure of the market is constructed using different methods to determine the distance between the companies. We use hierarchical clustering methods to find the relation among the companies in each window. Next, we obtain a one-dimensional time series of the distances between the clustering trees that reflect the changes in the relationship between the companies in the market over time. The method from statistical process control, namely the Shewhart control chart, is applied to those time series to detect abnormal changes in the financial market.

Optimizing the Use of Dose Error Reduction Software on Intravenous Infusion Pumps.

Intravenous infusions have the potential to cause significant harm in patients and are associated with a high rate of adverse drug events and medication errors. Infusion pumps with dose error reduction software (DERS) can be used to reduce errors by establishing safe infusion parameters. In 2019, a quality improvement project was initiated with the aim to increase DERS compliance from 46% to 75% at our specialty institution by October 1, 2022. An interdisciplinary group was tasked with improving compliance with DERS by identifying key drivers, including informed staff, engaged staff, and an accurate smart pump library. We used the Model for Improvement framework to guide this improvement project, and Plan-Do-Study-Act (PDSA) cycles were used to plan for interventions. PDSA cycles included drug library updates, education, and unit-level compliance reporting. Weekly average DERS compliance was monitored as the outcome measure, and weekly pump alerts per 100 infusions were monitored as a balancing measure; statistical process control charts were used to monitor measures from 2018 to 2022. Over the course of 25 months, 8 PDSA cycles resulted in 5 centerline improvements from a baseline mean of 46% to a final mean of 78%. Pump alerts per 100 infusions decreased from 15.9 to 6.4 with the first PDSA cycle and then continued to decrease to 3.9 with subsequent interventions. Although features like DERS can help ensure safe medication administration, continuous improvement efforts to increase DERS compliance without increasing alert burden are needed to ensure that benefits of this technology are optimized.

Increasing the Use of Enteral Antibiotics in Hospitalized Children With Uncomplicated Infections.

Route of administration is an important component of antimicrobial stewardship. Early transition from intravenous to enteral antibiotics in hospitalized children is associated with fewer catheter-related adverse events, as well as decreased costs and length of stay. Our aim was to increase the percentage of enteral antibiotic doses for hospital medicine patients with uncomplicated common bacterial infections (community-acquired pneumonia, skin and soft tissue infection, urinary tract infection, neck infection) from 50% to 80% in 6 months. We formed a multidisciplinary team to evaluate key drivers and design plan-do-study-act cycles. Interventions included provider education, structured discussion at existing team huddles, and pocket-sized printed information. Our primary measure was the percentage of antibiotic doses given enterally to patients receiving other enteral medications. Secondary measures included antibiotic cost, number of peripheral intravenous catheters, length of stay, and 7-day readmission. We used statistical process control charts to track our measures. Over a 6-month baseline period and 12 months of improvement work, we observed 3183 antibiotic doses (888 in the baseline period, 2295 doses during improvement work). We observed an increase in the percentage of antibiotic doses given enterally per week for eligible patients from 50% to 67%. We observed decreased antibiotic costs and fewer peripheral intravenous catheters per encounter after the interventions. There was no change in length of stay or readmissions. We observed increased enteral antibiotic doses for children hospitalized with common bacterial infections. Interventions targeting culture change and communication were associated with sustained improvement.

Max-mixed EWMA control chart for joint monitoring of mean and variance: an application to yogurt packing process

The Max-Mixed EWMA Exponentially Weighted Moving Average (MM EWMA) control chart is a statistical process control technique used for joint monitoring of the mean and variance of a process. This control chart is designed to detect small and moderate shifts in the mean and variance of a process by comparing the maximum of two statistics, one based on the mean and the other on the variance. In this paper, we propose a new MM EWMA control chart. The proposed chart is compared with existing control charts using simulation studies, and the results show that the chart performs better in detecting small and moderate shifts in both the mean and variance. The proposed chart can be helpful in quality control applications, where joint monitoring of mean and variance is necessary to ensure a product’s or process’s quality. The real-life application of the proposed control chart on yogurt packing in a cup data set shows the outperformance of the MM EWMA control chart. Both simulations & real-life application results demonstrate the better performance of the proposed chart in detecting smaller shifts during the production process.

Quality Control Analysis of Painting Results in Steel Construction Projects Using Statistical Quality Control Methods and Failure Mode Effect Analysis at PT. BSB

PT BSB is a company engaged in construction specialising in steel fabrication. There are various projects carried out at the company, namely bridges, steel structures, buildings, towers, and others. The research was conducted to analyse the quality of results in the painting process at PT BSB using statistical quality control (SQC) and failure mode effect analysis (FMEA) methods. Data collection is done by collecting primary and secondary data used in this study. The four types of painting defects obtained from the research results are Sagging/Runs, Orange Peel, Pin Hole and Seeds/Dirt. Based on the FMEA method, the level of defects can be determined based on the cumulative percentage value produced, where the highest defect value is 1750 Sagging/Runs defects. One of the factors causing the defect is the uneven spraying of paint, causing a layer of paint that is too thick, resulting in excessive accumulation of paint in certain parts that flow vertically and unevenly. From this research, it can be concluded that the company must use the SQC method to determine the causes of defects in the painting process and analyse improvements that must be prioritised. Keywords: Failure Mode Effect Analysis (FMEA), Painting Process Analysis, Statistical Quality Control (SQC)

Copula deep learning control chart for multivariate zero inflated count response variables

With the increasing popularity of big data analysis, research on zero-inflated count data with the copula method has garnered significant attention because zero-inflated count data do not follow a normal distribution and have high correlation among variables. Within the domain of quality control, there has been limited emphasis on multivariate statistical process control (SPC) techniques that specifically address the challenge of multicollinearity within regression models for multivariate zero-inflated count responses. In this paper, we explain a computational challenge in handling big data with parametric generalized linear models, such as the zero-inflated Poisson model. This challenge motivates us to introduce a copula-based deep learning and neural network model involving multivariate zero-inflated count response variables with highly correlated explanatory variables. This approach builds upon existing deep learning and neural network models designed for univariate count responses, expanding them to encompass multivariate count response models through the integration of a copula regression framework. To evaluate the performance of our proposed methodology, we conduct a comparative analysis of accuracies using the zero-inflated Poisson model, univariate deep learning and neural network models, multivariate count response deep learning and neural network models, and our proposed copula deep learning and neural network models. This assessment involves employing metrics such as root mean square error (RMSE), weighted mean absolute percentage error (WMAPE), and mean absolute deviation (MAD). We include both copula-based asymmetrical zero-inflated simulated data and real-world data. We also propose a temporal dependence control chart for assessing the temporal dependence between bivariate zero-inflated count response variables. Our proposed copula deep learning and neural network temporal control charts can check time-varying dependence and outliers by leveraging the Shewhart statistical process control chart and t-copula ARMA-GARCH dynamic control correlation.

Enhanced recovery program in ambulatory pediatric urology: A quality improvement initiative

Enhanced Recovery After Surgery (ERAS) was established in 2001 for adult patients undergoing complex procedures. ERAS in adult ambulatory surgery later followed with similar positive outcomes. For the pediatric population, ERAS implementation has shown promising results in complex surgeries such as bladder reconstruction. Its application in pediatric ambulatory surgery has only recently been reported. We hereby report a Quality Improvement initiative in implementing an Enhanced Recovery Protocol (ERP) for pediatric urology in an ambulatory surgery center. A project was launched to evaluate and implement enhanced recovery elements into an institutional Enhanced Recovery Protocol (ERP). These included reliance on peripheral nerve blocks for all inguinal and genital cases and reduction of opioids intraoperatively and postoperatively. Improvements were placed into a project plan broken into one preparation phase to collect baseline data and three implementation phases to enhance existing and implement new elements. The implementation phase went through iterative Plan-Do-Study-Act (PDSA) cycles for all sub-projects. Team countermeasures were based on available evidence. A consensus process was used to resolve disagreement. Monthly meetings were held to share real-time data, gather new feedback, and modify plans as needed. The primary outcome measures selected were percent intraoperative opioid use, percent opioid prescribing, mean PACU length of stay, and average number of opioid doses prescribed. Secondary outcome measures were mean maximum pain score in PACU, PACU rescue rate for PONV, and patient/family satisfaction scores. Post-implementation data for 18 months was included for evaluation. Statistical process control methodology was used. The total number of participants was 3306: 561 (baseline), 220 (Phase 1) 356 (Phase 2) and 527 (Phase 3), 1642 (post-implementation). Intraoperative opioid use was eliminated in >99% of cases. Post-operative opioid prescribing was reduced from 30% to 15% of patients. The number of opioid doses was also reduced from an average of 7.6 to 6.1 doses. There was no change for the mean maximum pain score in the recovery room despite elimination of opioids. Patient/family satisfaction scores were high and sustained throughout the period of study (9.8/10). Balancing measures such as return to the operating room within 30 days and return to the emergency department within 7 days were unchanged. This QI project demonstrated the feasibility of a pediatric enhanced recovery protocol in a urology ambulatory surgery setting. With implementation of this protocol, intraoperative opioid use was virtually eliminated, and opioid prescribing was reduced without affecting pain scores or post-operative complications.

Improving Access to Care, Patient Costs, and Environmental Impact Through a Community Outreach Lung Cancer Rapid Assessment Clinic.

In Southeastern Ontario, increased patient distance from the regional lung cancer diagnostic assessment program (LDAP) is associated with a lower likelihood of patient care via LDAP while receiving care via LDAP is associated with improved survival. We implemented an LDAP outreach clinic to provide specialist assessment for patients with suspected lung cancer at a regional community hospital and assessed the impact on timeliness and accessibility of care. The Kingston Health Sciences Centre LDAP team engaged with community hospital partners to develop and launch the LDAP outreach clinic. We performed a retrospective chart review of LDAP patients (N = 1,070) before (August-November 2021; n = 234) and after implementation of the outreach clinic (November 2021-October 2022; n = 836). Descriptive data are reported as No. (%). Unpaired t tests and statistical process control charts assess for significance. A cost analysis of out-of-pocket patient costs related to travel and parking is presented in 2022 Canadian dollars (CAD). Compared with a 3-month matched time period before (August-October 2021) and after outreach clinic (August-October 2022), the mean time from referral to assessment and time from referral to diagnosis decreased from 20.3 to 14.4 days (P = .0019) and 40.0 to 28.9 days (P = .0007), respectively. Over 12 months, the total patient travel was reduced by 8,856 km, which combined with parking cost-savings, resulted in patient out-of-pocket savings of CAD $5,755.60 (CAD $47.60/patient). Accounting for physician travel, the total travel saved was 5,688 km, corresponding to reduced CO2 emissions by 1.9 tCO2. Implementation of a lung cancer outreach clinic led to improved timeliness of care, patient cost-savings, and reduced carbon footprint while serving patients in their community.

Statistical Analysis and Control of Influencing Factors of PM2.5 in Xuzhou

Coal has been an important industry pillar in Xuzhou since ancient times. With the rapid economic growth of the whole country after the reform and opening up, Xuzhou is not willing to lag behind in developing its own industrial economy, but behind the rapid economic development. However, a large amount of pollution emissions seriously damage the environment. Especially in recent years, the data of pm2.5 has gradually entered people's eyes, which makes us realize that the air environment in Xuzhou is already very bad, and it is urgent to protect the local environment. In this paper, a multivariate linear regression model is established by collecting the pm2.5 data from 2009 to 2017 and six related factors affecting the air environment in Xuzhou City, and the specific relationship between them and pm2.5 is analyzed. On this basis, the pm2.5 governance policy, human and technical countermeasures. According to the actual situation of Xuzhou and the experiences of other regions and developed countries, the corresponding countermeasures and reasonable suggestions are put forward.

Quality Improvement in Neonatal Care: Successful Adoption of the Eat, Sleep, Console Protocol in a Rural Hospital Setting.

The United States faces a growing burden of neonatal opioid withdrawal syndrome in rural hospitals. Traditional treatments often extend hospital stays and medication use. The Eat, Sleep, and Console (ESC) approach offers a new management strategy but is challenging in resource-limited settings. This study aimed to apply ESC in rural hospitals to reduce neonatal intensive care unit admissions, decrease length of stay (LOS) to under 7 days, and lower medication use by more than 80% within a year. Our quality improvement initiative at rural hospitals implemented a multimodal approach for in utero opioid-exposed infants, involving staff education, electronic medical record updates, and nonpharmacological care strategies. Data from January 2020 to December 2023 assessed treatment impact, including pharmacotherapy need and hospital stay lengths, using statistical process control for analysis. After ESC implementation, the percentage of opioid-exposed infants receiving pharmacological treatment significantly decreased from 60.7% to 7.9%. The average LOS was reduced from 14.5 days to 5.25 days. These improvements persisted for 24 months, with no readmissions within 30 days of discharge. This approach also reduced hospital charges by over $5 million, demonstrating its clinical and financial effectiveness. The multidisciplinary approach successfully implemented ESC in a resource-limited setting, significantly reducing both the LOS and medication exposure for opioid-exposed infants while also saving significant healthcare costs. This successful model has been adopted by at least four regional rural hospitals, thus broadening the program's impact.

Transforming into a Learning Health System: A Quality Improvement Initiative.

The Institute of Medicine introduced the Learning Healthcare System concept in 2006. The system emphasizes quality, safety, and value to improve patient outcomes. The Bellevue Clinic and Surgical Center is an ambulatory surgical center that embraces continuous quality improvement to provide exceptional patient-centered care to the pediatric surgical population. We used statistical process control charts to study the hospital's electronic health record data. Over the past 7 years, we have focused on the following areas: efficiency (surgical block time use), effectiveness (providing adequate analgesia after transitioning to an opioid-sparing protocol), efficacy (creating a pediatric enhanced recovery program), equity (evaluating for racial disparities in surgical readmission rates), and finally, environmental safety (tracking and reducing our facility's greenhouse gas emissions from inhaled anesthetics). We have seen improvement in urology surgery efficiency, resulting in a 37% increase in monthly surgical volume, continued adaptation to our opioid-sparing protocol to further reduce postanesthesia care unit opioid administration for tonsillectomy and adenoidectomy cases, successful implementation of an enhanced recovery program, continued work to ensure equitable healthcare for our patients, and more than 85% reduction in our facility's greenhouse gas emissions from inhaled anesthetics. The Bellevue Clinic and Surgical Center facility is a living example of a learning health system, which has evolved over the years through continued patient-centered QI work. Our areas of emphasis, including efficiency, effectiveness, efficacy, equity, and environmental safety, will continue to impact the community we serve positively.

Reducing Time from Pediatric Emergency Department Arrival to Dexamethasone Administration in Wheezing Patients.

Asthma exacerbations are common presentations to pediatric emergency departments. Standard treatment for moderate-to-severe exacerbations includes administration of oral corticosteroids concurrently with bronchodilators. Early administration of corticosteroids has been shown to decrease emergency department length of stay (LOS) and hospitalizations. Our SMART aim was to reduce the time from arrival to oral corticosteroids (dexamethasone) administration in pediatric patients ≥2 years of age with an initial Pediatric Asthma Severity Score >6 from 60 to 30 minutes within 6 months. We used the model for improvement with collaboration between ED physicians, nursing, pharmacy, and respiratory therapists. Interventions included nursing education, dosage rounding in the electronic medical record, supplying triage with 1-mg tablets and a pill crusher, updates to an asthma nursing order set and pertinent chief complaints triggering nurses to document a Pediatric Asthma Severity Score in the electronic medical record and use the order set. Our primary outcome measure was the time from arrival to dexamethasone administration. Secondary outcome measures included ED LOS for discharged patients and admission rate. We used statistical process control to analyze changes in measures over time. From October 2021 to March 2022, the average time for dexamethasone administration decreased from 59 to 38 minutes. ED LOS for discharged asthma exacerbation patients rose with overall ED LOS for all patients during the study period. There was no change in the admission rate. Using quality improvement methodology, we successfully decreased the time from ED arrival to administration of dexamethasone in asthma exacerbation patients from 59 to 38 minutes over 10 months.

Imaging in a Pandemic: How Lack of Intravenous Contrast for Computed Tomography Affects Emergency Department Throughput.

During the coronavirus 2019 pandemic, hospitals in the United States experienced a shortage of contrast agent, much of which is manufactured in China. As a result, there was a significantly decreased amount of intravenous (IV) contrast available. We sought to determine the effect of restricting the use of IV contrast on emergency department (ED) length of stay (LOS). We conducted a single-institution, retrospective cohort study on adult patients presenting with abdominal pain to the ED from March 7-July 5, 2022. Of 26,122 patient encounters reviewed, 3,028 (11.6%) included abdominopelvic CT with a complaint including "abdominal pain." We excluded patients with outside imaging and non-ED scans. Routine IV contrast agent was administered to approximately 74.6% of patients between March 7-May 6, 2022, when we altered usage guidelines due to a nationwide shortage. Between May 6-July 5, 2022, 32.8% of patients received IV contrast after institutional recommendations were made to limit contrast use. We compared patient demographics and clinical characteristics between groups with chi-square test for frequency data. We analyzed ED LOS with nonparametric Wilcoxon rank-sum test for continuous measures with focus before and after new ED protocols. We also used statistical process control charts and plotted the 1, 2 and 3 sigma control limits to visualize the variation in ED LOS over time. The charts include the average (mean) of the data and upper and lower control limits, corresponding to the number of standard deviations away from the mean. After use of routine IV contrast was discontinued, ED LOS (229.0 vs 212.5 minutes, P = <0.001) declined by 16.5 minutes (95% confidence interval -10, -22). Intravenous contrast adds significantly to ED LOS. Decreased use of routine IV contrast in the ED accelerates time to CT completion. A policy change to limit IV contrast during a national shortage significantly decreased ED LOS.

Strategies to Improve COVID-19 Vaccination in a Pregnant, Marginalized Population: Quality Improvement Project.

Objectives. To improve COVID-19 vaccination rates in pregnant and recently pregnant women from a baseline rate of 30.8% to 60% over 6 months in a marginalized population. Methods. This quality improvement (QI) project was conducted in a federally qualified health center in Western New York between November 2021 and April 2022, using a Lean Six Sigma method. The QI team created a fishbone diagram, process flow map, and driver diagram. Significant barriers were multiple preferred languages, limited health literacy, and a knowledge gap. Increased vaccination rates were the outcome measure. The process measures were attendance at educational events and increased knowledge in community health workers (CHWs) and doulas. Education for CHWs and patients, creating multilingual educational resources, and motivational interviewing sessions for CHWs and patients were the major interventions. We performed data analysis by using weekly run charts and a statistical process control chart. Results. We achieved a sustainable increase in the COVID-19 vaccination rates in women from 30.0% to 48% within 6 months. Conclusions. Patient education in their preferred languages and at health literacy levels and CHWs' engagement played a crucial role in achieving success. (Am J Public Health. 2024;114(S4):S322-S329. https://doi.org/10.2105/AJPH.2024.307665).

Portable spectroscopy, digital imaging colorimetry and multivariate statistical tools in contaminant identification: A case study of mint (Mentha) and basil (Ocimum basilicum)

The advent of portable Fourier-Transform Infrared (FTIR) and Raman spectrometers has revolutionized analysis capabilities, presenting the possibility of on-site contaminant identification without the need for specialized laboratory settings. Compared to laboratory instrumentation, portable spectroscopy is more prone to noise, and appropriate spectral processing procedures need to be established. This paper introduces a comprehensive methodology that integrates acquisition techniques, spectral analysis, and mathematical tools necessary for utilizing handheld spectrometers to diagnose plant contamination. It focuses on determining the efficacy of handheld FTIR, Raman spectroscopy, and digital imaging for detecting contaminants in two food plants, Basil (Ocimum basilicum) and Mint (Mentha). The study examines the impact of three pollutants: iron (II) sulphate (FeSO4), zinc (II) sulphate (ZnSO4), and copper (II) sulphate (CuSO4), on these plants, but also the necessary amount of measurements to spot the pollutants' effects. Measurements were conducted at the start, after 24 hours, and after 48 hours of exposure, on both fresh and dried plant leaves, as well as in solution. Spectral effects of each of the pollutants were identified with the use of multivariate statistical process control techniques. With the help of the developed methodologies, researchers can identify in-situ contaminant effects, exposure times and run diagnostics directly on the leaf both in alive and dried plants.

Neonatal blood pressure by birth weight, gestational age, and postnatal age: a systematic review.

Blood pressure is a vital hemodynamic marker during the neonatal period. However, normative values are often derived from small observational studies. Understanding the normative range would help to identify ideal thresholds for intervention to treat hypotension or hypertension. Therefore, the aim of this study was to assess observed blood pressure values in neonates who have not received any blood-pressure modifying treatments from birth to three months postnatal age and whether these vary according to birth weight, gestational age and postnatal age. This was a systematic review. A literature search was conducted in MEDLINE, PubMed, Embase, Cochrane Library, and CINAHL from 1946 to 2017 on blood pressure in neonates from birth to 3months of age (PROSPERO ID CRD42018092886). Unpublished data were included where appropriate. Of 3,587 non-duplicate publications identified, 30 were included (one unpublished study). Twelve studies contained data grouped by birth weight, while 23 contained data grouped by gestational age. Study and clinical heterogeneity precluded meta-analyses thus results are presented by subgroup. A consistent blood pressure rise was associated with increasing birth weight, gestational age, and postnatal age. In addition, blood pressure seemed to rise more rapidly in the most preterm and low birth weight neonates. Despite blood pressure increasing with birth weight, gestational age, and postnatal age, there was marked blood pressure variability observed throughout. To better define hypotension and hypertension, future studies should develop consistent approaches for factors related to blood pressure variability, including the method and timing of measurement as well as statistical control of relevant patient characteristics.

Economic Statistical Design of the Variable Sampling Interval CV Chart with Known Shift Size

Control charts are essential in Statistical Process Control (SPC) to enhance the product quality by identifying assignable causes within the process. Extensive study on coefficient of variation (CV) charts has been conducted in recent years, indicating their growing significance in a variety of scientific applications. In order to monitor the quality characteristic, it should be noted that the statistical properties and economic perspectives are both indispensable factors. For the economic design, the optimal design parameters that minimise the expected cost function are obtained. However, this design has a major weakness, where it overlooks the statistical performance of the control chart. Therefore, it is of greater importance to examine the economic statistical design, which includes statistical constraints on the cost model. Although the existing variable sampling interval (VSI) CV chart has excellent statistical qualities, it is deficient in taking into account the economic aspects that are necessary for cost-effective process monitoring. In response, this research proposes the economic statistical design of the variable sampling interval (VSI) CV chart with known shift size. Moreover, the study includes sensitivity analyses of the optimal cost and the optimal design parameters for various input parameters. The effects of misspecification of the shift size on the performance of the VSI CV chart are investigated. Additionally, the comparisons in terms of the economic statistical performance between the VSI CV, Shewhart CV and EWMA CV charts are conducted. In comparison with Shewhart CV and EWMA CV charts, the findings clearly demonstrate that the VSI CV chart performs better in all numerical examples. As a result, this research advocates the use of the economic statistical design of the VSI CV chart in process monitoring and provides insightful information for quality practitioners seeking cost-effectiveness and optimal performance in their processes.

Analisis Pengendalian Kualitas Produk Part Housing SUV Menggunakan Metode Statistical Process Control di PT. Y

In the increasingly advanced world of manufacturing industries, of course, companies need to innovate for tighter competition. The role of product quality will be very influential to get product results with good quality and in accordance with standard operating procedures, must carry out quality control by paying attention to the level of product defects in order to approach zero defects. Therefore, this study aims to analyze quality control to reduce the occurrence of defective products and provide improvement proposals. The method used is Statistical Process Control (SPC) to analyze product defects with the total production of SUV Housing Parts as many as 34740 units. 4 types of defects were produced, namely Coak Blank 40 units, Overlap 37 units, Ngecap Scrap 13 units, and Flatness NG 11 units. The factors causing this type of disability are human factors, machines, materials, environment, and methods. Thus, the improvement proposals given are providing regular training to operators, carrying out routine machine maintenance, using ear plugs while working, measuring material dimensions, and checking materials that will enter the machine. Based on the research conducted, this SPC method can help companies identify product defects and provide suggestions or solutions to problems that occur. Keywords: Defect, Quality Control, Repair, Statistical Process Control