Statistical Quality Control Methods Research Articles

Quality 4.0: Learning quality control, the evolution of SQC/SPC

This article marks a significant advancement in the field of quality management, specifically focusing on the evolution from traditional Statistical Quality Control (SQC) and Statistical Process Control (SPC) methods to a more advanced Learning Quality Control (LQC) approach. The research introduces Quality 4.0 (Q4.0) as a novel paradigm that fuses the technologies of the fourth industrial revolution, Manufacturing Big Data (MBD), Industrial Internet of Things (IIoT), Cloud Storage and Computing (CSC) and Artificial Intelligence (AI), with traditional quality management practices. The central theme of this study is exploring the limitations inherent in conventional quality control methods when faced with the complexities of modern manufacturing environments. The authors propose LQC systems as a solution, employing binary classification algorithms to predict and detect defects in manufacturing processes. This represents a shift from reactive to proactive quality measures enabled by AI’s real-time data processing capabilities. The document delves into the evolution of manufacturing data across industrial revolutions, highlighting the exponential growth of unstructured data and its challenges. Through case studies, the authors illustrate the practical applications of LQC systems, demonstrating their ability to learn complex patterns in hyperdimensional spaces and automate tasks traditionally performed visually.

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)

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.

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.

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.

Quality control analysis of chiffon cake pandan in Holland Bakery

The advancement of business development affects economic competition. Companies with strong competitive advantages must compete with other companies in the same field. One way to compete with the same competitors is to favor the quality of the products produced. Holland Bakery is one of the cake and bread manufacturers. Holland Bakery continues to strive to produce quality products, but there is still damage that exceeds the standard limit by 2.13% in 2022 with the standard limit set, which is 2%. One way to do quality control is to use the Statistical Quality Control (SQC) method. This study aims to analyze the quality of one of Holland Bakery's products, namely Chiffon Cake Pandan Sponge Cake, which is still within the tolerance limit or not, and what types of damage occur most often. This research was conducted from September 21 - October 20, 2023, with the results obtained that the level of damage is still within the tolerance limit. However, there is still damage exceeding the UCL line on the 10th day of production by 10% due to burning, the 19th day by 6.67% due to non-standard shape, the 23rd day by 11.11% due to burning, and the 29th day by 10% due to burning. The most dominant damage is due to burning as many as 16 pieces. Then, the cause-and-effect diagram shows that damage factors occur due to humans (man), environment (environment), and methods (method). Improvements from various aspects such as humans, environment, and methods can be made to minimize damage so that quality is always maintained. It is expected that Holland Bakery can review the production method of Chiffon Cake Pandan, monitor the condition of workers, and add air ventilation in the production room.

Consistency Analysis of Rendement and Quality of CPO (Crude Palm Oil) Palm Oil Processing at PT. Agricinal North Bengkulu

The yield and quality of CPO is influenced by the condition of unripe and overripe FFB (fresh fruit bunches), which can cause an increase in ALB, water content and dirt content. The quality of CPO is also influenced by FFB from the community. Analysis of the consistency of the yield and quality of CPO was carried out due to the age of the plants that were too old and the performance of the factory machines decreased due to the age of the machines. Analysis of yield consistency and quality was carried out using statistical quality control methods, namely quality control using a statistical approach using control charts and causal diagrams. This study uses secondary data on the yield and quality of CPO for the past year (July 2021-June 2022). The research results show, there are data that are outside the upper control limit, yield in July 2021, free fatty acid content in May 2022 and dirt content in October 2021. While the water content is statistically controlled (in statistical control). The yield and quality of ALB are influenced by type of raw material, production capacity and oil losses. Moisture content and dirt content are affected by treatment of production process and machine conditions.

PENERAPAN SQC DAN FMEA DALAM ANALISIS PRODUK CACAT DI CV. KONVEKSI 3 DARA BANDUNG

In this day and age, business competition is increasingly fierce in responding to diverse consumer demands, strategic action is needed in carrying out company operations. CV. Konveksi 3 Dara Bandung is a micro, small and medium enterprise (MSME) which operates in the field of clothing production including clothes, jackets, robes, shirts and the like. Based on the observations that have been made, the quality of the products produced still does not meet consumer satisfaction, because the products produce many product defects including rejected clothes, broken seams, loose seams and wrinkles on clothes. Therefore, quality control tools are needed to identify the causes of products that do not meet standards, and then provide solutions to correct these problems so that the quality of the products produced can reach the maximum level. The combination of methods between Statistical Quality Control (SQC) and FMEA is expected to help companies in optimizing product quality control. Based on the analysis of the Statistical Quality Control method combined with the FMEA concept, it was concluded that the defects that occurred included rejected clothes (19%), broken stitches (37%), loose stitches (24%), and wrinkles (20%).

Analisis Pengendalian Kualitas Produksi Donat Di Toko Donat Madu Cihanjuang Kota Bekasi, Jawa Barat

This research aims to help reduce defects and improve the production process for the better. The method used in the Quality Control Analysis of Donut production is the Statistical Quality Control (SQC) method to ensure the level of product quality statistically, and by using a quantitative approach in the form of descriptive by collecting data through observation and interview techniques. Since the results of the data found did not exceed the threshold on the P control map with a centre line of 0.036, the results showed that the honey donut products were still within the statistical control limits. A number of variables, such as the influence of people, machines, and methods, have an impact on the cause of product failure. The recommended corrective action is to organise regular meetings to discuss improving the quality of honey donut products, which will be the main reason in determining the most important thing to improve the quality of production.

Study of Statistical Quality Control (SQC) Methods in Analyzing Quality Control of Paving Block Products at PT. X

PT. X is a manufacturing company that produces building materials. PT. X is still often faced with several problems including the frequent occurrence of defective products, especially in paving block products as one of its main products. The defects that often occur include products that are easily crushed, cracked, asymmetrical, not dry and also broken in some parts. The defects that occur affect the quality of the resulting product. The purpose of this study was to determine the most dominant percentage of defects to allow further treatment. The method used in this research is Statistical Quality Control (SQC). The SQC method uses several tools including check sheets, stratification, histograms, paretto diagrams, scatter diagrams, control charts, and cause and effect diagrams. Based on the results of the SQC study, the most dominant defects were easily crushed paving with a percentage of 38.34%, cracked paving with a percentage of 28.86%, broken paving in some parts with a percentage of 13.83%, asymmetrical paving with a percentage of 10.92%, and non-dry paving with a percentage of 8.05%.

Implementation of Statistical Quality Control (SQC) As a Quality Damage Control for Crepes Products in the Indonesian Food Industry

Snacks like crepes are fragile and have a dry texture. This study aims to identify the root causes of defective products, examine how SQC procedures were applied, decide how to reduce the number of defective products, and take efforts to raise product quality. Data collection is the first step in the research procedure, then comes data processing. The SQC method consists of check sheets, histograms, Pareto diagrams, p-control charts, and fishbone charts. Pareto diagrams were used to assess the results of the crepes product quality, which included flaky tip, size, and crushed flaws. The numbers reported on the check sheet for each defect were 156, 99, and 37 units, respectively. The fishbone diagram displays the factors that contribute to defects, including people, machines, materials, methods, and the environment. The upper control limit is 0.523, the lower control limit is 0.126, and the centre line of the p-control chart is 0.324. Because of fluctuations outside the control region, it may be inferred from this research that the production process for crepe products is not under control. Offering workers on-the-job training to equalize skill levels is one of the strategies to reduce product damage.

Quality Control Analysis of Porcelain Products Using Overall Equipment Effectiveness and Statistical Quality Control Methods

Quality Control Analysis of Porcelain Products Using Overall Equipment Effectiveness and Statistical Quality Control Methods

ANALISIS KUALITAS PRODUK PENYAMAKAN KULIT DENGAN METODE SQC dan FMEA

PT Adi Satria Abadi is a company engaged in tanning. The problem faced by the company is the presence of defective leather during the goat and sheep tanning production process. From these problems, the purpose of this study was to identify the level of product defects, analyze the factors that cause defects, and make recommendations for improvements to improve the quality of goat and sheep tanning products. Data processing in this study uses the SQC (Statistical Quality Control) and FMEA (Failure Mode and Effect Analysis) methods. Based on the identification results, it was found that there were 1,507 holes for holes, 1,066 for thick defects, 1,061 for louse defects, and 1,086 for size defects. The results of the SQC analysis still have uncontrolled data based on the control chart which is on size defects with a total of 1,086 defects, while for hollow defects, too thick defects, and tick defects are under control. The results of the FMEA analysis show that the order of completion with the first priority is spotting bugs with an RPN value of 36. The suggested improvements to the company are by directly selecting raw materials and supervising employees.
 
 Keywords: Quality, Product Defects, Seven Tools, SQC, FMEA.

Analisis Pengendalian Kualitas Paving Block Menggunakan Metode Statistical Quality Control (SQC)

The development of an increasingly competitive industrial world makes companies to be innovative and pay attention to the quality of the products they produce. CV. ABS is a company that produces construction complementary materials in building manufacture. The research aims to reduce the damage level of paving blocks using the Statistical Quality Control method which produces Central Line (CL) = 0.313, Upper Control Limit (UCL) = 0.409, and Lower Control Limit (LCL) = 0.217. The results of the P-Chart graphic data show that there is an average non-conformity or declared in an uncontrolled state at four points below the LCL (0.217) namely on the second day (0.13), seventh (0.18), ninth (0.43 ), and eleventh (0.50) One of the factors causing defective products is the lack of experience of workers, the use of low quality materials, the method of mixing materials is not according to standards and the printing equipment used is in old condition.

Quality Control of Edamame Products Using Statistical Quality Control (SQC) and Failure Mode Effect Analysis (FMEA) Methods in PT. XYZ

PT. XYZ is a company engaged in the frozen food processing industry. One such product is Edamame. In the Edamame production process, defects such as pest defects, color defects, pod defects and mechanical defects that affect quality are still found. The purpose of this study was to determine the proportion of defects that most often occur and the factors that cause defects and to provide suggestions for improving the quality of edamame. The methods used are Statistical Quality Control (SQC) and Failure Mode Effect Analysis (FMEA). The SQC tools include check sheets, statistics, histograms, pareto charts, scatter diagrams, control charts, and fishbone diagrams. Then continue the FMEA analysis for suggestions for corrective action. Based on the results of research on Statistical Quality Control (SQC) it is known that the most dominant defects in edamame are pests (39.9%), then color (25.5%), pods (25.2%), and mechanics (9.4%) ). Based on the results of research on Failure Mode Effect Analysis (FMEA) it is known that the highest cause of problems with RPN 360 is lack of sanitation. Suggestions for improvement that can be proposed namely. Scheduling cleaning of the work environment area and sterilizing production machines and equipment.

Application of statistical quality control methods in a textile manufacturing company

Statistical quality control is an effective method employed to increase the finished product quality of enterprises, and this method is used to increase the quality standards of the textile company presented in this study. The company's knitted fabric quality control data of the previous years are analyzed, and appropriate statistical quality control methods are determined to improve the quality control system currently used. U control chart is considered to assess the quality limits of the fabrics received from the suppliers. A single acceptance sampling plan is structured to standardize the acceptance sampling method applied by the company to the knitted fabric lots. MIL-STD 105 D military standard is considered while creating a single acceptance sampling plan. The operating characteristic (OC Curve) for the sampling plan is designed and the acceptance probabilities of the lots with different defective rates are examined. As stated in the computational results, suppliers need quality improvement efforts and followed by that it would be possible to reach high quality levels in the enterprise.

Pengendalian Mutu Produk Croissant Chocolate Menggunakan Metode Statistical Quality Control (SQC) di PT. Bapak Bakery

One of the products of PT. Bapak Bakery which has the highest market demand is the chocolate croissant. The large demand for this product results in a large number of reject products that are not in accordance with company standards. Therefore, it is necessary to study the production process and quality control using the Statistical Quality Control (SQC) method so that it can be seen whether the number of reject products in this product is still within the company's tolerance limits or not. The purpose of this research is to study the production process and product quality aspects of chocolate croissant PT. Bapak Bakery. The method used in this research is field practice, observation, interviews, literature study, and data processing. In the production process of chocolate croissants at PT. Bapak Bakery is carried out through several stages, namely the preparation of ingredients, weighing of ingredients, mixing, weighing the dough, freezing the dough, sheeter, cutting, filling with chocolate sticks, forming, proofing, greasing, baking, resting, and packaging. The results of the analysis using the Statistical Quality Control (SQC) method showed that the total chocolate croissants reject products were 269 pcs with details as many as 139 pcs (52%) experiencing burnt rejects (overcooked) and as many as 130 pcs (48%) experiencing reject layers that did not come out of the total. 1966 pcs chocolate croissants produced during the research period. The results of the analysis using the SQC method indicate that the number of reject products is still within the tolerance limits set by the company. Two causes of chocolate croissant damage are found in the machine factor, the worker factor, the raw material factor, and the method used during the production process.
 Keywords: Quality Control, Statistical Quality Control (SQC), Croissant, PT. Bapak Bakery

Statistical Methods for Controlling the Quality of Crude Oil Products in Iraq

The purpose of this study is to measure the levels of quality control for some crude oil products in Iraqi refineries, and how they are close to the international standards, through the application of statistical methods in quality control of oil products in Iraqi refineries. Where the answers of the study sample were applied to a group of Iraqi refinery employees (Al-Dora refinery, Al-Nasiriyah refinery, and Al-Basra refinery) on the principles of quality management control, and according to the different personal characteristics (gender, age, academic qualification, number of years of experience, job level). In order to achieve the objectives of the study, a questionnaire that included (12) items, in order to collect preliminary information about the study sample was designed. The data was analyzed statistically and hypotheses were tested using the SPSS statistical package. The study relied on a random sample of 225 individuals, of which 205 were valid. The most important results obtained are: The degree of applying control over quality management in the refineries under study was: 68.8% for the principle of senior management's commitment to quality, 65.2% for the principle of planning for the application of quality standards, and 65.% for the principle of strengthening the culture of quality among workers. The level of quality of some crude oil products in the refineries under study was estimated at 45%. In addition to the existence of a statistically significant correlation between the application of the principles of control over quality management and the quality of some oil products.
 

Portable Instruments Based on NIR Sensors and Multivariate Statistical Methods for a Semiautomatic Quality Control of Textiles

Near-infrared (NIR) spectroscopy is a widely used technique for determining the composition of textile fibers. This paper analyzes the possibility of using low-cost portable NIR sensors based on InGaAs PIN photodiode array detectors to acquire the NIR spectra of textile samples. The NIR spectra are then processed by applying a sequential application of multivariate statistical methods (principal component analysis, canonical variate analysis, and the k-nearest neighbor classifier) to classify the textile samples based on their composition. This paper tries to solve a real problem faced by a knitwear manufacturer, which arose because different pieces of the same garment were made with “identical” acrylic yarns from two suppliers. The sweaters had a composition of 50% acrylic, 45% wool, and 5% viscose. The problem occurred after the garments were dyed, where different shades were observed due to the different origins of the acrylic yarns. This is a challenging real-world problem for two reasons. First, there is the need to differentiate between acrylic yarns of different origins, which experts say cannot be visually distinguished before garments are dyed. Second, measurements are made in the field using portable NIR sensors rather than in a controlled laboratory using sophisticated and expensive benchtop NIR spectrometers. The experimental results obtained with the portable sensors achieved a classification accuracy of 95%, slightly lower than the 100% obtained with the high-performance laboratory benchtop NIR spectrometer. The results presented in this paper show that portable NIR sensors combined with appropriate multivariate statistical classification methods can be effectively used for on-site textile quality control.