Statistical Quality Control Methods Research Articles

Importance of Quality Control Implementation in the Production Process of a Company

The concept of quality has gained increasing importance over the last decades. Regarding the production process of a company, the quality control implementation allows companies to offer a higher quality product, which has positive influence on customer satisfaction. This paper aims to reflect the importance of statistical methods for quality control. Based on the two broad areas of statistical inference, parameter estimation and hypothesis testing, we demonstrate the usefulness of such methods in problem solving when the proportion of defective items is considered.

The Analysis of the Forest Fires in Turkey with Statistical Quality Control Method

<p><span lang="EN-US">Fire is one of the most serious hazards for forests on earth. Despite each kind of technological development and equipment, fire activity has an increasing trend because of especially climate change and socio-economic reasons. Although fire extinguishing organizations, today, try to suppress this increasing risk with a maximum effort, the big fires in some places cause the enormous areas to get burned. The fires as big as natural disasters cannot be extinguished most of the time in spite of any efforts or methods when the extreme fire weather conditions come together with inflammable matters and ignition sources. </span></p><p><span lang="EN-US">In this study, the number and area of forest fires in Turkey were investigated through statistical quality control method. Despite the decreasing trend of forest fires in terms of area size, the possibility of large fires always exists in the whole Mediterranean Region due to the socio-economic conditions such as increasing human population, migration and any changes that could affect fire activity in climate conditions. As a result of the study, it is seen that there is an overall increase in the number of fires while the burned area decreases. Out-of-control behaviors in control graphs are not in a continuous trend but sometimes exceed the control limits. This condition is seen to be positive as a trend but also points to the possibility of unexpected annual burned area and the number of fires.</span><strong></strong></p>

Economic Implications of Statistical Quality Control: Lessons for Manufacturers in Nigeria

This study examined the economic implications of statistical quality control. It applied the literature study method. The study highlights the methods of statistical quality control as well as the economic benefits derivable from the use of and adherence to the processes of quality control in general and scientific and statistical quality control in particular. Quality consciousness, consumers’ satisfaction, cost reduction and optimum utilization of resources are some of the numerous economic benefits of scientific and statistical quality control. While wastages, decrease in sales and decrease in profitability are some adverse economic implementations of the absence of or neglect to use statistical quality control in an organization. The campaign for quality assurance should be driven to the grass root for all and sundry, especially the manufacturing sector, to become conversant with the need for quality products, services and results delivery. This will make their product compete favourably with foreign products.

Prognostics and Health Management for Rechargeable Batteries

After numerous successful applications of statistical quality control and reliability methods in manufacturing industries in the past several decades, the quality paradigm has shifted from manufacturing application to field operation in many industries. This shift was triggered by continuous concerns in product reliability, system safety, and failure prevention, and made possible by latest advancement in data collection technologies and development of powerful modelling algorithms. This general field of research provides tremendous opportunities for interdisciplinary research and has been classified as prognostics and system health management (PHM). In this talk we will share our experience of PHM research in the application of rechargeable batteries through methods in data mining, diagnostics and prognostics, anomaly detection and monitoring.

STATISTICAL CONTROL OF ACCURACY AT MACHINING

This research examines the statistical method for quality control. The accuracy of parts is controlled statistical evaluation - an average and a dispersion of the indicator for accuracy. This paper reports a method for quality control of parts of average indicators and algorithm for quality control of the average and dispersion of samples of small size. It proposes a criterion of applicability of statistical adjustment of accuracy by sampling for control of the average data of the quality indicator. It proves the influence of the dispersion of the quality indicator for impairing the quality of the process.

Prediction of Bacterial Contamination Outbursts in Water Wells through Sparse Coding

Maintaining water quality is critical for any water distribution company. One of the major concerns in water quality assurance, is bacterial contamination in water sources. To date, bacteria growth models cannot predict with sufficient accuracy when a bacteria outburst will occur in a water well. This is partly due to the natural sparsity of the bacteria count time series, which hinders the observation of deviations from normal behavior. This precludes the application of mathematical models nor statistical quality control methods for the detection of high bacteria counts before contamination occurs. As a result, currently a future outbreak prediction is a subjective process. This research developed a new cost-effective method that capitalizes on the sparsity of the bacteria count time series. The presented method first transforms the data into its spectral representation, where it is no longer sparse. Capitalizing on the spectral representation the dimensions of the problem are reduced. Machine learning methods are then applied on the reduced representations for predicting bacteria outbursts from the bacterial counts history of a well. The results show that these tools can be implemented by the water quality engineering community to create objective, more robust, quality control techniques to ensure safer water distribution.

PENGENDALIAN KUALITAS DENGAN MENGGUNAKAN METODE STATISTICAL QUALITY CONTROL (SQC) UNTUK MEMINIMUMKAN PRODUK GAGAL PADA TOKO ROTI BAROKAH BAKERY

Quality Control is an activity (company management) to maintain and navigate to product quality (and) services
 companies can be maintained as planned. Quality Control used the company to minimize failed products using methods of Statistical Quality Control (SQC) so that the company can meet the quality products that have been specified businesses and consumers are satisfied in consuming the product. The purpose of that will be achieved in this research is to determine the method of Statistical Quality Control (SQC) with tekhnik control chart and diagram of cause and effect applied the company Bakery Barokah Bakery in quality control to minimize the product failed. Tekhnik data collection that is used is a library research and field research, while data analysis tool that is used control chart and diagram of cause and effect. The results of the analysis of control charts shows that the number of products that are examined as much as 27.710 units, the average of 0,099 product damage or 9.9%. Limitations: UCL supervision of 0,1161 or 11.61%, LCL of 0,0819 or 8,12%. Quality control on the Bakery Barokah Bakery is good because the number of failed products are still within the boundaries of fair is located between UCL and LCL. While the results from the diagram for result (fish bones), the main factor the causes of the failure of the products of bread in the Bakery Barokah Bakery namely human factors. Where people fail in the making of the bread products. So required training to minimize failed products that occurred caused by human factors.

QUALIDADE DO PROCESSO DE SEMEADURA DA CULTURA DO MILHO DE SEGUNDA SAFRA

A semeadura do milho está sujeita a fatores que podem interferir na qualidade da operação. O uso de métodos estatísticos de controle de qualidade em processos agrícolas tem-se mostrado eficiente para detecção de variabilidade no decorrer da operação. Objetivou-se avaliar a qualidade e capabilidade da semeadura do milho de segunda safra por semeadora-adubadora pneumática. A coleta de dados ocorreu no município de Dourados (MS) em área de aproximadamente 30 ha, utilizando-se malha amostral composta de 60 pontos distribuídos na área com uma amostra a cada 0,5 ha. Determinaram-se a quantidade de plântulas emergidas e a distância entre plantas em dois metros consecutivos, a fm de calcular o estande de plantas por metro e a porcentagem de espaçamentos normais, falhos e duplos. Realizou-se, inicialmente, análise descritiva e controle estatístico do processo (CEP) para caracterizar os dados e averiguar a estabilidade da semeadura do milho, que serviram como pressupostos para realizar análise de capabilidade do processo. O estande e a distribuição longitudinal de plantas em espaçamentos normais foram satisfatórios, embora abaixo da capacidade da semeadora-adubadora pneumática. O CEP permitiu avaliar a qualidade das variáveis durante o processo de semeadura, demostrando instabilidade para porcentagem de espaçamentos normais e controle dos demais indicadores de qualidade de semeadura. A análise de capabilidade indicou que a semeadora pneumática não atingiu as metas estabelecidas para estande de plantas (5 plantas m-1) e espaçamentos falhos e duplos (10%), sugerindo necessidade de monitoramento da operação.

The application of statistical methods to control the quality of the contact pairs of electrical connectors

The development of electronic technology in the direction of improving its performance and speed, accompanied by the decrease of its dimensions and mass. This trend requires a new generation of electrical connectors differing from the basic models of a large number of contacts and density of placement on the insulator, having low contact resistance and high insulation resistance, high reliability and long life. The article describes the way of practical application of statistical methods for quality control of contact pairs of electrical connectors. The objects of study of effectiveness of statistical methods of quality management selected two typical details contact pairs received by turning on automatic lathes: pin and socket. The article considers the process of collecting statistical information about the technological process automatic turning of parts of the contact pairs. Shows the results of processing statistical information about the quality of the details of the contact pairs. The use of statistical methods for quality control of contact pairs of electrical connectors allows to correctly configure technological equipment according to the results of making a test batch of parts. Recommendations are made to improve the quality of the contact pairs of connectors. Compiled by technique of quality management of contact pairs according to the results of the statistical analysis of technological processes of their manufacture.

Application of statistical methods for quality control of measurement processes in the enterprises of technical service of agroindustrial complex

The attention to statistical methods of quality control is driven by their reliability in case of the small sample volumes in comparison with continuous control. The article shows the reasons of delaying of introduction of statistical methods in the enterprises of technical service of agroindustrial complex. The value of statistical quality control of test and measurement processes is pointed out. It is confirmed by the standardized requirements to the quality management and by the assessment of impact of this control on failures of products in operation. The use of statistical control allows to stabilize in more short timeframes the production on high-quality level. The analysis of standards and technic specifications for machinery production shows that the acceptance rules for machinery generally indicate the sample volume equal to 2% of batch of machines. This is only 1 machine of daily batch of 50 machines. At that, the risk of the fact that a consumer will receive defective products is 26%. The control of a single machine in the sample shows the imperfection of acceptance rules. Despite the availability of regulations on statistical quality control, it has not become widely used in practice in the field of domestic agricultural and automotive engineering and technical services. It is necessary to determine the problems of statistical quality control of test and measurement processes and the ways of its implementation; to establish the reasons for the lack of attention to statistical quality control. It is required to substantiate the ways for its widespread use in the technical service and production. As research techniques, it is proposed to apply the information retrieval, statistical methods of data collection, analogy methods and morphological analysis.

Total quality management (TQM) movement in public health

Purpose – The purpose of this paper is to suggest better methods for monitoring the diagnostic and treatment services for providers of public health and the management of public health services. In particular, the authors examine the construction and use of industrial quality control methods as applied to the public providers, in both the prevention and cure for infectious diseases and the quality of public health care providers in such applications including water quality standards, sewage many others. The authors suggest implementing modern multivariate applications of quality control techniques and/or better methods for univariate quality control common in industrial applications in the public health sector to both control and continuously improve public health services. These methods entitled total quality management (TQM) form the foundation to improve these public services. Design/methodology/approach – The study is designed to indicate the great need for TQM analysis to utilize methods of statistical quality control. All this is done to improve public health services through implementation of quality control and improvement methods as part of the TQM program. Examples of its use indicate that multivariate methods may be the best but other methods are suggested as well. Findings – Multivariate methods provide the best solutions when quality and reliability tests show indications that the variables observed are inter-correlated and correlated over time. Simpler methods are available when the above factors are not present. Research limitations/implications – Multivariate methods will provide for better interpretation of results, better decisions and smaller risks of both Type I and Type II errors. Smaller risks lead to better decision making and may reduce costs. Practical implications – Analysts will improve such things as the control of water quality and all aspects of public health when data are collected through experimentation and/or periodic quality management techniques. Social implications – Public health will be better monitored and the quality of life will improve for all especially in places where public development is undertaking rapid changes. Originality/value – The manuscript is original because it uses well known and scientific methods of analyzing data in area where data collection is utilized to improve public health.

PBS machine interlocks using EWMA

Delivery of pencil beam scanning (PBS) requires the on-line measurement of several beam parameters. If the measurement is outside of specified tolerances and a binary threshold algorithm is used, the beam will be paused. Given instrumentation and statistical noise such a system can lead to many pauses which could increase the treatment time. Statistical quality control methods are typically used on manufacturing lines to monitor a process and give early detection of a gradual problem and stop the process if a deviation is statistically significant. These methods can be used to develop a more intuitive algorithm for (PBS) delivery systems that is robust and safe and leads to decreased treatment times. The Exponentially Weighted Moving Average (EWMA) control scheme monitors deviations in beam properties which are averaged over a specified number of measurements with greater weight applied to the more recent ones. Simulation of an EWMA-style algorithm safely detected shifts in random and systematic delivery errors without false alarms. Binary and EWMA methods can be combined for improved reliability without sacrificing patient safety. In the EWMA method, the mean of a beam property can be related to systematic uncertainties and the standard deviation can be related to random uncertainties. This method allows one to have separate interlock levels for each type of uncertainty and to detect systematic trends.

Numerical Investigation on Uniformity of Heat Distribution of Swirl Anti-Icing System

Heat distribution characteristics e.g. temperature, the local Nusselt number, local heat flux etc., contribute to ice accretion on all critical surfaces of aircraft. The non-uniformity in heat distribution at these surfaces results in low temperatures and runback ice accretion downstream from these surfaces areas. Most of the previous studies merely extracted local temperature or local Nusselt number profiles at certain locations/cross-sectional planes on the surface to describe the uniformity of the temperature, which of two does not represent the overall temperature distribution on the entire surface. This paper proposes using the Coefficient of temperature deviation (Ctem dev), which is obtained using Statistical Quality Control (SQC) and statistical methods, as the measurement of the anti-icing system’s temperature uniformity. The discussion covers the uniformity of the temperature distribution in a nacelle lip, which is produced by Swirl Anti-Icing (SAI) system. This paper also numerically investigates the effects of an SAI system's nozzle length and nozzle rotation angle on the temperature uniformity over several Reynolds numbers (Re) in a D-chamber, ranging between 7.5 x 104 and 4.1 x 105. At Re= 7.58 x 104 and velocity of free stream = 48.75 m/s, Ctem dev decreases by 13.7% as the Nozzle Direction Angle (NRA) changes from 0⁰ to 13⁰, which indicates that changing nozzle direction significantly improves the uniformity of the temperature distribution on a nacelle lip surface. However, according to the numerical results, Ctem dev is insensitive to nozzle length. The results also show that the uniformity of the temperature distribution improves as the Re increases, for NRA values of both 0⁰ and 13⁰.

A unique fuzzy multi-control approach for continuous quality improvement in a radio therapy department

In this study, a unique fuzzy multi-control approach for continuous quality improvement is introduced and is implemented in radio therapy department. Treatment process is one of the most important concern in healthcare department. To control this process there is a critical issue, because the periods that the patients take to the recovery should be controlled by the physicians. This study tries to control this process using the common statistical quality control methods. In addition, this paper presents a control index for patient condition. Given the decision making situations including diagnosis, determining the medicine and its value and control limit, decision making (DM) models will be used at first step. Then, process control is analyzed using statistical process control (SPC) including histogram, Pareto chart, cause and effect diagram and new fuzzy control chart. This research aims at presenting a unique control approach with fuzzy DM and SPC tools for a real radio therapy department. Moreover, these processes could be controlled and improved continuously using Deming cycle (PDCA). The case study verified and validated the design model. This is the first study that presents a unique integrated fuzzy control approach for improved decision-making process in an actual radio therapy department.

Автоматизированный метод контроля качества посева семян на вырубках

Автоматизированный метод контроля качества посева семян на вырубках

A comparison of automated statistical quality control methods for error detection in historical radiosonde temperatures

This paper presents a comparison of statistical methods for automated random error detection in historic radiosonde temperatures through a rigorous simulation study. We simulate temperature data designed to mimic observed radiosonde temperature time series from ten climate regions and three pressure levels and contaminate this simulated data with errors that are similar to those occurring in the historical record. Robust estimates of centre and spread of the temperatures are used to standardize values and flag potentially erroneous observations, and five approaches for selecting subsets of observations upon which to base these estimates are tested. Two robust estimators, one of which is designed to work well for asymmetric distributions and gives different estimates of standard deviation for each tail of the distribution, are investigated. We use a logistic regression model to assess the effects of climate, pressure level, record length, contamination percentage, error type, and window size on each method combined with each estimator in terms of both correctly and incorrectly identified errors. Temperature distributions are not always symmetric, and based on the simulation, we find that the asymmetric estimator makes fewer mistakes in error identification, and we illustrate its application with a case study at a Russian station.

STATISTICAL VIEW OF QUALITY MANAGEMENT

The modern management paradigmassumes increase of a role of quality ofproduction. In modern enterprises focuseson the application of statistical methodsfor quality control and process control.Assessment of the interdependenceparameters can improve the accuracy ofthe quality control and reduce the defectrate of products.

The reconstruction of abnormal segments in HJ-1A/B NDVI time series using MODIS: a statistical method

HJ-1A/B is the first small satellite constellation built by China for environmental and disaster monitoring and forecasting. The satellite group has a 2-day repetition cycle and 30 m spatial resolution (charge coupled device camera). Thus, HJ-1A/B can provide hyper-temporal normalized difference vegetation index (NDVI) time series with a medium–high spatial resolution. However, the quality of the HJ NDVI time series can be abnormally low due to a number of factors, such as cloud cover, continuous fog, and haze. In the rainy season or in areas with serious atmospheric pollution, low-quality series often appear in succession, which is referred to as an abnormal segment. Neither the composition method nor quality flags satisfactorily solve this problem; therefore, a large amount of noise and long periods of abnormally low values often remain in HJ NDVI time series. This article presents a method to reconstruct the abnormal segments in HJ NDVI time series with the assistance of Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI time series. The cointegration test was adopted to decide whether MODIS can be used for the reconstruction of NDVI time series for the corresponding HJ image pixels. Statistical quality control methods were used for singling out the abnormal segments in the HJ NDVI time series and establishing an error correction model that combines MODIS and HJ NDVI time series to perform the reconstruction. The study area is located in Jiangsu Province, China. Four-year (2009–2012) HJ multispectral images that cover the study area were used. The results show that abnormal segments in the HJ NDVI time series can be corrected using the proposed method. In a particular year, this method can decrease the root mean square error between the HJ NDVI time series and the reference sequence by 52.5%.

Применение статистических методов управления качеством для оптимизации производства по ремонту пути

Применение статистических методов управления качеством для оптимизации производства по ремонту пути

Bayesian hierarchical modeling for monitoring optical profiles in low-E glass manufacturing processes

Low-emittance (low-E) glass manufacturing has become an important sector of the glass industry for energy efficiency of such glasses. However, the quality control scheme in the current processes is rather primitive and advanced statistical quality control methods need to be developed. As the first attempt for this purpose, this article considers monitoring of optical profiles, which are typical quality measurements in low-E glass manufacturing. A Bayesian hierarchical approach is proposed for modeling the optical profiles, which conducts model selection and estimation in an integrated framework. The effectiveness of the proposed approach is validated in a numerical study, and its use in Phase I analysis of optical profiles is demonstrated in a case study. The proposed approach will lay a foundation for quality control and variation reduction in low-E glass manufacturing.