Statistical Control Methods Research Articles

PENGURANGAN DEFECT PADA PRODUK SEPATU DENGAN MENGINTEGRASIKAN STATISTICAL PROCESS CONTROL (SPC) DAN ROOT CAUSE ANALYSIS (RCA) STUDI KASUS PT. XYZ

PT. XYZ is a foreign capital investment companies are located in one area of town of Sidoarjo which has more than 7000 employees in it and of course want to have a high quality product . PT footwear products. XYZ is the world quality products that promote the quality and comfort of the wearer. Problems that occur in the production process of PT . XYZ of 7 -injection engine that has the most number of engine defect is 5.6 and 7. Quality products at heavily influence the shoe production to consumers. If damaged, then the product can not be distributed to consumers .Therefore , the quality of the shoes must be maintained for the successful marketing of the product. From our previous improvements made in reducing the defect in the production process , but the result is less than optimal , so do research that aims to make improvements again with another method . The method used in this research is to apply the methods of Statistical Processing Control (SPC) and Root Cause Analysis (RCA). The results of the check sheet analysis and Pareto diagram can be seen the frequency of product defects (defects) over roughing most occurred in March 2016 as many as 345 shoes (62%) of the total production of 489 products. Then the second frequency in February 2016 as many as 214 shoes (38%) of the total production of 357 products. And from the image Control Chart P can be concluded that the data are in a state of uncontrolled. Because of all these 50 data, there is one data point that is outside the control limits (out of control), on the 4th point the data has a value of the proportion of 1, beyond the limits Upper Control Limit (UCL) is equal to 0.938. During the dots located within the boundaries of a controller, a process is under controlled conditions, and no action required. However, one point that lies outside the control limit is interpreted as the fact that the quality control in the production process (injection) PT. XYZ uncontrolled or still experiencing irregularities. Whereas the causes of the failure of a critical process in the production process are humans, machines, methods and materials.

Применение статистических методов контроля для оценки стабильности производства молочной продукции

The article presents the results of an estimation of defectiveness level of sour-milk production (on an example kefir), developed on one of dairy factories of region. To assess the level of defect, statistical methods of control are used - a checklist for the registration of defective products, a control p-chart and Ishikava diagram. The initial data were obtained at the stage of quality control of finished product and entered in the developed form of the control sheet for product defects. The most common defect in the production is established - the leakage of the package, which can be assessed visually, and not with the help of measuring instruments. For evaluation and subsequent analysis of the reasons for the appearance of the established defect, a control p-chart was used on an alternative basis, which makes it possible to control the quality of manufactured products by the number of defective products. As a result of the analysis of the obtained data, it was established that the technological process, from the point of view of statistical forecasting, is acceptable, but this does not mean a high production stability and does not exclude the appearance of defective products. The analysis of the main reasons for the emergence of unsealed packaging products, among them the qualification of personnel, the quality of the used materials and the conditions for their storage, the production environment, compliance with production technology, and others. A subsequent study of the impact of each of these factors will prevent the appearance of defective products and ensure the production of consistently high quality products.

ANALYSIS OF THE REQUIREMENTS FOR THE QUALITY CHARACTERISTICS OF COLD-FORMED REINFORCEMENT OF CLASS ВР500

The main requirements for a new class of cold-formed reinforcement V500 are considered in the article. The requirements to the performance characteristics of such fittings in comparison with the reinforced wire of class Bp-1 in accordance with GOST 6727-80 have been estimated. Along with the requirements for plasticity or deformation of the reinforcement for the new class requirements are introduced for the relative bearing surface, fatigue endurance, mandatory marking, etc. To ensure reliability the characteristic values of Cv, determined by statistical control methods with long-term quality assessment are introduced. The size range of the reinforcement was significantly expanded.

Evaluation of diagnosis methods in PCA-based Multivariate Statistical Process Control

Multivariate Statistical Process Control (MSPC) based on Principal Component Analysis (PCA) is a well-known methodology in chemometrics that is aimed at testing whether an industrial process is under Normal Operation Conditions (NOC). As a part of the methodology, once an anomalous behaviour is detected, the root causes need to be diagnosed to troubleshoot the problem and/or avoid it in the future. While there have been a number of developments in diagnosis in the past decades, no sound method for comparing existing approaches has been proposed. In this paper, we propose such a procedure and use it to compare several diagnosis methods using randomly simulated data and from realistic data sources. This is a general comparative approach that takes into account factors that have not previously been considered in the literature. The results show that univariate diagnosis is more reliable than its multivariate counterpart.

Variable selection methods in multivariate statistical process control: A systematic literature review

Abstract Technological advances led to increasingly larger industrial quality-related datasets calling for process monitoring methods able to handle them. In such context, the application of variable selection (VS) in quality control methods emerges as a promising research topic. This review aims at presenting the current state-of-the-art of the integration of VS in multivariate statistical process control (MSPC) methods. Proposals aligned with the objective were identified, classified according to VS approach, and briefly presented. Research on the topic has considerably increased in the past five years. Thirty methods were identified and categorized in 10 clusters, according to the objective of improvement in MSPC and the step of process monitoring they were aimed to improve. The majority of the propositions were either targeted at exclusively monitoring potential out-of-control variables or improving the monitoring of in-control variables. MSPC improvements were centered in principal component analysis (PCA) projection methods, while VS was mainly carried out using the Least Absolute Shrinkage and Selection Operator (LASSO) method and genetic algorithms. Fault isolation was the most addressed step in process monitoring. We close the paper proposing five topics for future research, exploring the opportunities identified in the literature.

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.

Innovative management of food enterprises in terms of import substitution and import dependence

The article discusses the new policy of import substitution in Russia. The replacement of imports by domestic counterparts is a priority of Federal and regional authorities. Innovative management should primarily take into account the new economic conditions which exist and will soon operate a food company. Describes the factors that have a negative impact on the efficiency of innovative management of dairy plants: the drop in oil prices, decline in exports, domestic oil prices, the devaluation of the ruble. The analysis of the indicators of import dependence and import substitution in the dairy group food. The analysis of indicators of the food industry showed that the indicator of self-sufficiency in the last 10 years have been below the 0.90 standard. In 2007, the industry reached self-sufficiency ratios 0.8146 that is still below the required standard more than 10%. These calculations allowed us to attribute the production of dairy products to import-dependent food industry. Therefore, in this industry were conducted further research based on the indicators “import” and “self-sufficiency”. Used methods of statistical control showed that the inverse correlation between these indicators does not exist. So, the volume of the imported imports depends on other factors and only increasing their own production, this figure does not decrease. Therefore, in the production of milk and dairy products need more reforms to improve the indicators of self-sufficiency. Providing the population of our country milk and dairy products in need of rapid change to increase its own production of dairy products. Thus, features of innovative management of dairy enterprises are determined by the modern conditions of import substitution.

Система менеджмента качества как элемент эффективности подготовки инженерных кадров в системе высшего образования

The Russian system of the economy requires new qualities of labor resources, so the provision of high quality education continues to remain a priority of state policy. Also the quality of education in Russia is connected with the reform and modernization of the education system at the state level, with the development and improvement of scientific, educational and production potential of the University. To guarantee quality and competitiveness in schools must carry out a number of activities associated with quality assurance. The success of educational institutions depends on effective management system and implemented the quality management system. The article presents problems of higher school in the training of engineers, proposed methods of use of the quality management system, discusses statistical methods of control and analysis, quality monitoring of educational activities.

Статистические методы управления технологическими процессами

Статистические методы управления технологическими процессами

Heritability of growth traits in South African Abalone (Haliotis midae L.) using the ‘internal reference’ method

The South African Abalone Haliotis midae is a vital aquaculture species, accounting for the highest percentage of total aquaculture production revenue. Improving the growth rate and thus, reducing operational costs with associated benefits in production efficiency and profitability is a priority of producers. The industry has been reluctant to implement anything but the most rudimentary breeding practices, due to unreliable tagging methods and the cost of using DNA markers. As such, the current study aimed to estimate genetic parameters for growth traits in the absence of individual tagging or DNA markers using the ‘internal reference’ method. The requirements of the internal reference method are evaluated and the merits and demerits considered. Heritability estimates were low to moderate in magnitude for wet weight (0.06–0.21) and shell length (0.11–0.16). It is concluded that substantial genetic gains can be achieved through selection and further work into developing strategies employing individual identification and DNA markers are warranted. Statement of relevanceWe adapted an existing statistical control method in an innovative way to estimate genetic parameters for growth traits in abalone, without individual tagging or DNA markers. This method facilitates the transition from simple family selection programs to combined selection programs by providing the necessary inputs for bio-economic modelling to inform the design of more advanced breeding programs.

Использование методов статистического контроля для оценки стабильности работы агрегатов

Использование методов статистического контроля для оценки стабильности работы агрегатов

Development and implementation of a real time statistical control method to identify the start and end of the winter surge in demand for paediatric intensive care

Winter surge management in intensive care is hampered by the annual variability in the winter surge. We aimed to develop a real-time monitoring system that could promptly identify the start, and accurately predict the end, of the winter surge in a paediatric intensive care (PIC) setting. We adapted a statistical process control method from the stock market called “Bollinger bands” that compares current levels of demand for PIC services to thresholds based on the medium term average demand. Algorithms to identify the start and end of the surge were developed for a specific PIC service: the North Thames Children's Acute Transport Service (CATS) using eight winters of data (2005–12) to tune the algorithms and one winter to test the final method (2013/14). The optimal Bollinger band thresholds were 1.2 and 1 standard deviations above and below a 41-day moving average of demand respectively. A simple linear model was found to predict the end of the surge and overall demand volume as soon as the start had been identified. Applying the method to the validation winter of 2013/14 showed excellent performance, with the surge identified from 18th November 2013 to 4th January 2014.An Excel tool running the algorithms has been in use within CATS since September 2014. There were three factors which facilitated the successful implementation of this tool: the perceived problem was pressing and identified by the clinical team; there was close clinical engagement throughout and substantial effort was made to develop an easy-to-use Excel tool for sustainable use.

Construction site safety control with medium-accuracy location data

A statistical safety control method is presented that utilizes location data from a relatively inaccurate yet cost-effective system to track workers in real time, and prevent unsafe situations at construction sites. In light of the inac­curacy of the tracking system, buffer areas are defined as statistical zones, at some distance from potential workplace hazards. Statistical alerts are created according to predefined rules when the hazard exposure of workers in those zones crosses a certain threshold. The results of tests of the method demonstrate that the model is able to successfully process the location data in order to compensate for its inaccuracy. This is done without necessitating a significant increase in the areas that are defined as being of high risk, and therefore off-limits for most workers on site. The model can thus ensure the efficiency of the construction work by restricting the size of the areas on site that are off-limits for most work­ers, while at the same time ensuring the safety of workers. The method can also ensure that alerts will not be ignored by using statistical rules to avoid an excessive number of alerts, and by discerning who should be the client of an alert.

A comparative study of two proposed CCC-r charts for high quality processes and their application to an injection molding process

ABSTRACTHigh-quality industrial processes, characterized by a low fraction of non-conforming items, require paying special attention to the statistical control methods employed since traditional Shewhart's control charts are no longer suitable. In this article, CCC-r charts are considered based on the cumulative count of conforming items inspected until r non-conforming items are observed. However, even though these charts have shown to be useful for high-quality processes, they are characterized by a biased average run length (ARL). In order to help engineers interested in this control methodology to select the best option, a computational study of statistical validation was performed to compare the two most outstanding procedures for the cases r = 2, 3, and 4. The performance was evaluated based on the ARL under control. The application of the CCC-r chart to a real process is shown with data from an automobile parts plant. Finally, analysis and discussion of the results are presented.

Methods of Statistical Control for Groundwater Quality Indicators

The article describes the results of conducted groundwater quality control. Controlled quality indicators included the following microelements - barium, manganese, iron, mercury, iodine, chromium, strontium, etc. Quality control charts - X-bar chart and R chart - were built. For the upper and the lower threshold limits, maximum permissible concentration of components in water and the lower limit of their biologically significant concentration, respectively, were selected. The charts analysis has shown that the levels of microelements content in water at the area of study are stable. Most elements in the underground water are contained in concentrations, significant for human organisms consuming the water. For example, such elements as Ba, Mn, Fe have concentrations that exceed maximum permissible levels for drinking water.

Change-point detection for shifts in control charts using fuzzy shift change-point algorithms

Knowing the real time of changes, called change-point, in a process is essential for quickly identifying and removing special causes. Many change-point methods in statistical process control assume the distribution and the in-control parameters of the process known, however, they are rarely known accurately. Small errors accompanied with estimated parameters may lead to unfavorable change-point estimates. In this paper, a new method, called fuzzy shift change-point algorithm, which does not require the knowledge of the distribution nor the parameter of the process, is proposed to detect change-points for shifts in process mean. The fuzzy c-partition concept is embedded into change-point formulation in which any possible collection of change-points is considered as a partitioning of data with a fuzzy membership. These memberships are then transferred into the pseudo memberships of observations belonging to each individual cluster, so the fuzzy c-means clustering can be used to obtain the estimates for shifts. Subsequently, the fuzzy c-means algorithm is used again to obtain new iterates of change-point collection memberships by minimizing an objective function concerning the deviations between observations and the corresponding cluster means. The proposed algorithm is nonparametric and applicable to normal and non-normal processes in both phase I and II. The performance of the proposed fuzzy shift change-point algorithm is discussed in comparison with powerful statistical methods through extensive simulation studies. The results demonstrate the superiority and usefulness of our proposed method.

Improving the quality control system of production process

The article is devoted to problems of analysis of the production process of leather manufacturing at the enterprise of automotive industry. The results of experimental studies during the technological processing of leather manufacturing are given. The main tool of statistical process control is control cards by which monitored the distribution of measurable characteristics of the production process, and whether they are within the control. The area on the graph shows the total change in both the manufacturing process and the measurement process.During the research the basis is the use of index reproducibility and process suitability of the quality control system that are effective tools for continuous improvement of quality, performance and management decisions. Statistical control method is used to assess the suitability of the production equipment (CP) and dispersion parameters (CPk) of the production process to explore availability or unavailability of the process.

Study of types of defects in wood chipboard production

Types of defects in wood chipboard production and losses connected with the defects were studied. Faulty products were studied by statistical methods of control; analysis of causes of faulty products at wood chipboards production was carried out. Economical appraisal of losses according to peculiarities of production was given.

On the Effect of Combination of Statistical and Judgemental Stock Control Methods

Stock control is the most important aspect in an inventory system. It determines the safety stock in order to ensure that products are readily available when the customers require them. The decision makers in organizations tend to rely on software solution in obtaining stock control solutions since they have to manage a massive number of Stock Keeping Units (SKUs). However, managers intervene in the system and use their judgement to adjust or decide on various quantitative elements. This research discusses the effects of combination of stock control methods. An extended database of approximately 1,800 SKUs from an electronics company is analyzed. Then, a simulation experiment is performed in order to evaluate in a dynamic fashion what are the effects of applying combined stock control methods. The findings indicate that the combined method of stock control seems to improve the performance of the inventory system, especially in reducing inventory investment.

The Gravity Model on EU Countries – An Econometric Approach

Foreign Direct Investment, play a huge role in the growth of the global businesses. They can provide to a firm, new markets where the firm can operate, new marketing channels, manufacturing facilities, access to technology and to the products, and they also provide techniques and funds previously unknown. For the host country, this source of technologies, capital, processes, techniques, and managerial skills can provide an important impetus to the economic development of the country. Through this study, it has been analyzed how FDI are affected by the distance and by the economic size of the country. Given that such a gravity model (size and distance) on FDI already exists, this research has examined particularly the impact of these two factors on FDI of the EU member states. Through an econometric model it has been examined how economic size and distance affect foreign investment of EU leading countries in some of the world states and which of two factors have had the greatest impact. The hypothesis raised in this paper is related to the fact that the gravity model with its factors is extremely important for the volume of FDI, the size playing a more important role than the distance. By using statistical judgment and econometric analysis it has been explored if the hypothesis rose above, is statistically valid or not. From the model resulted that the impact of the size coefficient on FDI is 0.0042 million Euros, while the distance coefficient is – 0.36 millions. It shows that with the increase of GDP and the distance between countries, FDI increase and decrease respectively with the above coefficients. According to statistical methods of control, economic size was a more determinant factor than the distance, giving us the idea that in recent years with the increased role of globalization the importance of distance has significantly decreased. In this paper it is recommended the gravity models should consider a lot other factors besides size and distance. JEL classification: A1, C01, C12, C31, C51, F21 Keywords: FDI, international trade, gravity model, EU countries, econometric model.