scholarly journals Analisis Pengendalian Mutu Kadar Air Teh Hitam pada Industri Pengolahan Teh

2021 ◽  
Vol 2 (2) ◽  
pp. 81
Author(s):  
Gustiarini Rika Putri ◽  
Rizki Fadhillah Lubis ◽  
Asri Yenita
Keyword(s):  
Quality Control ◽  
Statistical Process Control ◽  
Process Monitoring ◽  
Control Charts ◽  
Human Error ◽  
Raw Materials ◽  
Improve Quality ◽  
Machine Condition ◽  
Statistical Process ◽  
Tea Quality

Quality control is intended to maintain and improve quality and maintain the safety of the products produced. This study uses Statistical Process Control by using several tools such as check sheets, control charts and fishbone diagrams to determine the cause of the decline in quality in tea with the aim that the next process can minimize the level of product quality decline. This study aims to determine the dominant cause of the decline in tea quality when viewed from the water content in tea. Based on the results of the study, it can be seen that the dominant cause of the decline in tea quality is the highwater content of dry tea. This type of deterioration can be caused by human error and other factors such as machine condition, raw materials and process monitoring.

Statistical Process and Quality Control

2000 ◽  
pp. 233-244
Keyword(s):  
Quality Control ◽  
Quality Improvement ◽  
Quality Management ◽  
Total Quality Management ◽  
Statistical Process Control ◽  
Control Charts ◽  
Statistical Testing ◽  
Total Quality ◽  
Statistical Process ◽  
Sampling Plans

Abstract This chapter provides an introduction to statistical process control and the concept of total quality management. It begins with a review of quality improvement efforts in the extrusion industry and the considerations involved in developing sampling plans and interpreting control charts. It then lays out the steps that would be followed in order to implement statistical testing for billet casting, die performance, or any other process or variable that impacts extrusion quality. The chapter concludes with an overview of the fundamentals of total quality management.

scholarly journals Pengendalian Kualitas Proses Pengemasan Gula Karung Menggunakan Metode Statistical Process Control (SPC)

2020 ◽  
Vol 1 (1) ◽  
pp. 16
Author(s):  
Rizaldi Sardani ◽  
Devi Faradila ◽  
Suci Oktri Viarani M ◽  
Eko Supriadi
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Human Error ◽  
Control Process ◽  
Statistical Process ◽  
Product Packaging ◽  
Packaging Process ◽  
Quality Control Process

Quality is a benchmark to determine the level of good and bad of a product. The level of quality of a product will affect customer satisfaction, hence, to produce high quality products, it is necessary for a company to have a quality control process. Quality control is a process that aims to maintain the quality of products and services that have been promised to consumers. In this study, quality control is carried out in the sugar packaging process. Where in the sugar packaging process found the resulting product has a poor quality, defective and not in accordance with specifications. This study uses the Statistical Process Control (SPC) method which aims to determine the causes of defective products with the intention that the packaging process can further minimize the level of product defects. The SPC method is a statistical analysis technique with seven statistical tools or seven tools. Based on the results of the study it can be seen that the cause of product damage / defects in the product packaging process is caused by three types of damage namely damage due to conveyor (38.17%), damage due to machine pinched (35.82%), and damage due to loose seams (26,00%) This type of damage can be caused by human error and other factors such as engine condition, engine cleanliness and the monitoring process. Proposed improvements recommended for the company are to provide training to employees, make clear work instructions, conduct periodic maintenance for the machines used, supervise all work areas, and carry out quality control for every acceptance of raw materials.

Application of Statistical Process Control Tools to Improve Product Quality in Manufacturing Processes

2011 ◽  
Vol 110-116 ◽  
pp. 4023-4027
Author(s):  
Omar Bataineh ◽  
Abdullah Al-Dwairi
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Process Capability ◽  
Manufacturing Processes ◽  
Statistical Process ◽  
Free Products ◽  
Drug Companies

Quality control and improvement at the process level is a vital activity for the achievement of defect-free products in various manufacturing processes. This study employs statistical process control (SPC) tools such as control charts and process capability ratio for quality control and improvement. The control charts employed are , R and the cumulative-sum (CUSUM). The process capability ratio used is the so called process capability index (PCI). These tools have been implemented with the aid of Minitab® statistical software. In this study, the manufacturing process of gelatin capsules is investigated in terms of quality of the capsules, which are produced and shipped for use by various drug companies. As a result of implementation of SPC tools, an expected reduction in the number of defective capsules by 29% relative to the stage before implementation was achieved.

scholarly journals Application of Statistical Quality Control in Monitoring the Production, Packaging and Marketing Process of Sachet Water

2020 ◽  
pp. 32-45
Author(s):  
Terna Godfrey Ieren ◽  
Samson Kuje ◽  
Abraham Iorkaa Asongo ◽  
Innocent Boyle Eraikhuemen
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Statistical Quality Control ◽  
Statistical Control ◽  
Statistical Process ◽  
Marketing Process ◽  
Product Sales ◽  
Sachet Water

Statistical process control is a technique employed to enhance the quality and productivity of processes and the distribution or marketing of its products. Sachet water is a product that has become popular and is being used as a replacement for lack of potable water. It is an alternative that is readily available, affordable but with questions about its purity, production and marketing processes. The objective of this study is to apply statistical control charts in monitoring the production, packaging and distribution or marketing processes of sachet water in Nigeria. This paper employed statistical quality control approach to monitor process stability in a Table Water manufacturing company. Quality control tools such as p-chart, u-chart, X-bar and R charts as well as process capability chart were use to observed field data obtained from the sachet water manufacturing company on important processes of sachet water production and marketing for 30 working days. This was done to check if the processes were in control or out of control and to verify the capability of the marketing process of the product meeting preset specifications. With this, the statistical control charts suitable for the processes were constructed using package “qcc” in R software version 3.6.1. The results from p-chart and u-chart showed that the production and packaging process of the product is not in control and hence the need for further investigations and corrective measures to prevent variability in the process and thus allowing improvement in the quality of the product. Also, the results from X-bar and R charts showed that the marking process was in statistical process control in respects of the product sales recorded by the four independent marketers, with no assignable cause of variation. It also revealed that, the product marketing process has low capability of successfully attending the preset specification limits in respect of the product sales and hence generating low profit for the company.

scholarly journals Analisis Pengendalian Kualitas Produk Air Minum Dalam Kemasan dengan Menggunakan Statistical Process Control (SPC) dan Kaizen Pada PT. Tujuh Impian Bersama Kabupaten Jember

2018 ◽  
Vol 5 (2) ◽  
pp. 164
Author(s):  
Marga Area Refangga ◽  
Eka Bambang Gusminto ◽  
Didik Pudjo Musmedi
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Raw Materials ◽  
Research Model ◽  
Statistical Research ◽  
Statistical Process ◽  
Damage Type ◽  
Control Limits ◽  
Selection Of

This research aims to analyze the level of damage and identify factors causing damage AMDK 220ml that occurred on March 13 to 11 April 2017 at PT. Tujuh Impian Bersama. The company is engaged in bottled drinking water industry (AMDK) with Al Qodiri brand. This research uses descriptive statistical research model. The analysis used is Statistical Process Control (SPC) and Kaizen. The results of the analysis show that the quality control of the product is beyond the control limits set. The most damage type is dent pack as much as 239pcs. From the causal diagram can be known factors causing damage from the most dominant include machinery, raw materials, humans, and methods. Based on the kaizen implementation tools, the recommendations for improvement are routine maintenance and re-adjustment of production machines, more rigorous selection of suppliers with more stringent standards, and improved human resource performance through supervision and briefing. Keywords: Bottled Water, Kaizen, Quality Control, Statistical Process Control  

Research on Statistical Process Control of Packaging & Printing Quality Management

2011 ◽  
Vol 467-469 ◽  
pp. 13-18
Author(s):  
Ying Zhe Xiao ◽  
Ya Nan Huang
Keyword(s):  
Quality Control ◽  
Quality Management ◽  
Statistical Process Control ◽  
Control Chart ◽  
Control Charts ◽  
Basic Tool ◽  
Statistical Process ◽  
Printing Quality ◽  
And Control ◽  
Development Course

This paper states not only the development course of quality management but also the actuality that the packaging & printing enterprise confronts. In addition, it explains the necessity of applying SPC. The first, it is discussed and studied the basic tool of SPC-control chart for statistical process. Based on this way, -R control chart is used to analyze and control the overprint precision. According to these control charts, the spot staffs can find the deficiencies in the quality control itself by finding the correlative process fluctuation and the slow variation in time. In addition, SPC provides objective bases for the quality management personnels to assess semi-products or products quality.

scholarly journals STUBBLE DAMAGE AND UNSETTLING INDEXES FOR DIFFERENT CUTTING AND LOADING SYSTEMS

2021 ◽  
Vol 35 (4) ◽  
pp. 493-506
Author(s):  
Eduardo Prisco Angelo ◽  
Carla Segatto Strini Paixão Voltarelli ◽  
Murilo Aparecido Voltarelli ◽  
Rouverson Pereira da Silva ◽  
Cristiano Zerbato
Keyword(s):  
Quality Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Statistical Design ◽  
Statistical Process ◽  
Harvesting Time ◽  
Agricultural Mechanization ◽  
Mechanical Cutting ◽  
Sugarcane Ratoon

STUBBLE DAMAGE AND UNSETTLING INDEXES FOR DIFFERENT CUTTING AND LOADING SYSTEMS   EDUARDO PRISCO ANGELO1, CARLA SEGATTO STRINI PAIXÃO2, MURILO APARECIDO VOLTARELLI1 ROUVERSON PEREIRA DA SILVA3, CRISTIANO ZERBATO3   1 Centro de Ciências da Natureza, Universidade Federal de São Carlos, Rodovia Lauri Simões de Barros, km 12 - SP-189 - Aracaçu, 18290-000, Buri – SP, Brasil. [email protected] 2 Departamento de Engenharia, Faculdade de Engenharia de Sorocaba, Rodovia Senador José Ermírio de Moraes, 1425 - Jardim Constantino Matucci,18085-784, Sorocaba – SP, Brasil. [email protected] 3 Centro de Ciências da Natureza, Universidade Federal de São Carlos, Rodovia Lauri Simões de Barros, km 12 - SP-189 - Aracaçu, 18290-000, Buri – SP, Brasil. [email protected] 4 Departamento de Engenharia Rural, Universidade Estadual Paulista ‘Júlio de Mesquita Filho’, Via de Acesso Professor Paulo Donato Castelane S/N - Vila Industrial, 14884-900, Jaboticabal, SP, Brasil. [email protected]. 5 Departamento de Engenharia Rural, Universidade Estadual Paulista ‘Júlio de Mesquita Filho’, Via de Acesso Professor Paulo Donato Castelane S/N - Vila Industrial, 14884-900, Jaboticabal, SP, Brasil. [email protected].   ABSTRACT: Simultaneous mechanical cutting and loading of sugarcane may trample the remaining stumbles in the harvested area, thus increasing the damage and unsettling indexes of the stubs remaining in the ground after the harvest, which, in the end, can hamper sugarcane regrowth. To this end, this work aimed to evaluate how cutting and loading systems affect sugarcane ratoon using statistical process control. The experiment was conducted in an agricultural area in Frutal, MG, in June 2014. Mechanical harvesting was conducted at a 1.1 m s-1(4.0 km h-1) average working speed and 1.50m spacing. The statistical design used was completely randomized, based on the concepts of quality control, in which the data were collected during harvesting time. The study treatments were as follows, basal cut, and mechanical sets A, B, C and D according to equipment gauge width. The stubble damage and unsettling indexes were the parameters used to determine the quality of the process under study. Set D with the widest gauge is the best option for mechanical harvesting, loading and transporting sugarcane since it has significantly lower sugarcane stubble damage and unsettling indices compared to sets A, B, and C.   Keywords: agricultural mechanization, control charts, mechanical harvest, stubble trampling, variability.   RESUMO: O corte mecânico e carregamento simultâneo da cana-de-açúcar pode atropelar a palha remanescente na área colhida, aumentando os índices de danos e abalos das socas que permanecem no solo após a colheita, o que, ao final, pode dificultar a rebrota da cana-de-açúcar. Para tanto, o objetivo deste trabalho foi avaliar como os sistemas de corte e carregamento que afetam a soca de cana-de-açúcar por meio do controle estatístico do processo. O experimento foi conduzido em uma área agrícola em Frutal, MG, em junho de 2014. A colheita mecanizada foi realizada a uma velocidade média de trabalho de 1,1m s-1 (4,0 km h-1) e espaçamento de 1,50m. O delineamento estatístico utilizado foi inteiramente casualizado, em que os dados foram coletados na época da colheita. Os tratamentos estudados foram o corte basal e os conjuntos mecânicos A, B, C e D de acordo com a largura de bitola do equipamento. Dessa forma, conclui-se que o Conjunto D com a bitola mais larga é a melhor opção para colheita mecânica, carregamento e transporte da cana-de-açúcar, pois apresenta danos significativamente mais baixos à palha da cana-de-açúcar, além dos índices de abalos, quando comparados aos conjuntos A, B e C.   Palavras-chave: mecanização agrícola, cartas de controle, colheita mecanizada, pisoteio de soqueira, variabilidade.

APPLICATION OF SPC AND GROWTH MODELS ON THE ECONOMIC TRAJECTORY OF THE LEATHER AND FOOTWEAR INDUSTRY

2020 ◽  
Author(s):  
Mario Lesina ◽  
Lovorka Gotal Dmitrovic
Keyword(s):  
Human Capital ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Growth Models ◽  
Pearson Correlation ◽  
Small Companies ◽  
Statistical Process ◽  
Production Staff ◽  
Footwear Industry

The paper shows the relation among the number of small, medium and large companies in the leather and footwear industry in Croatia, as well as the relation among the number of their employees by means of the Spearman and Pearson correlation coefficient. The data were collected during 21 years. The warning zone and the risk zone were determined by means of the Statistical Process Control (SPC) for a certain number of small, medium and large companies in the leather and footwear industry in Croatia. Growth models, based on externalities, models based on research and development and the AK models were applied for the analysis of the obtained research results. The paper shows using the correlation coefficients that The relation between the number of large companies and their number of employees is the strongest, i.e. large companies have the best structured work places. The relation between the number of medium companies and the number of their employees is a bit weaker, while there is no relation in small companies. This is best described by growth models based on externalities, in which growth generates the increase in human capital, i.e. the growth of the level of knowledge and skills in the entire economy, but also deductively in companies on microeconomic level. These models also recognize the limit of accumulated knowledge after which growth may be expected. The absence of growth in small companies results from an insufficient level of human capital and failure to reach its limit level which could generate growth. According to Statistical Process Control (SPC), control charts, as well as regression models, it is clear that the most cost-effective investment is the investment into medium companies. The paper demonstrates the disadvantages in small, medium and large companies in the leather and footwear industry in Croatia. Small companies often emerge too quickly and disappear too easily owing to the employment of administrative staff instead of professional production staff. As the models emphasize, companies need to invest into their employees and employ good production staff. Investment and support to the medium companies not only strengthens the companies which have a well-arranged technological process and a good systematization of work places, but this also helps large companies, as there is a strong correlation between the number of medium and large companies.

scholarly journals AB1131 STATISTICAL PROCESS CONTROL AND PROCESS MAPPING QUANTIFY THE EFFECTS OF HISTORICAL CHANGES TO THE CONNECTIVE TISSUE DISEASE TESTING ALGORITHM AND IDENTIFY AREAS FOR FUTURE IMPROVEMENT IN A LARGE DIAGNOSTIC IMMUNOLOGY SERVICE

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1855.2-1855
Author(s):  
M. Stevens ◽  
N. Proudlove ◽  
J. Ball ◽  
C. Scott
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Similar Proportion ◽  
Limiting Factor ◽  
List Type ◽  
Process Mapping ◽  
Statistical Process ◽  
Current Testing ◽  
Testing Algorithm

Background:Pathology test turnaround times (TATs) are a limiting factor in patient flow through rheumatology services. Quality improvement (QI) methodologies such as Lean use tools including statistical process control (SPC) and process mapping to study the performance of the whole of a clinical pipeline, expose unnecessary complexity (non-value-adding activity), and streamline processes and staff roles.Objectives:Understand effects of changes made to CTD testing algorithm over last 12 years by measuring some of the effects on TATs. Model current processes and suggest changes to workflow to improve TAT.Methods:High-level flow diagrams of the current testing algorithm, and low-level process maps of analyser and staff processes were drawn.Activity and TATs (working days between report and booking date) for ANA, ENA, DNA and CCP tests were plotted as XmR control charts.Results:Finding 1: Largest referral laboratory does not currently operate a separate DNA monitoring workstream, resulting in unnecessary ANA and ENA testing (figure 1).Figure 1.Current testing strategy (left) and suggested improvement (right)Finding 2:Samples are handed off between 3 different lab benches, each of which may be staffed by a different staff member on a different day, and results processing involves handoff to a further 2 different staff members.Finding 3:ANA demand is close to capacity, ENA demand exceeds current capacity (table 1).Table 1.Demand for ANA, ENA and DNA tests, compared to capacityTestMedian Demand(tests/ day)Approx. Capacity(tests/ day)NotesANA74100Close to 80% recommended by the ILGsENA3836*Less capacity than demand!!DNA34100PlentyFinding 4:Stopping screening DNA requests on ANA result increased the number of DNA tests performed by about 10 samples per day (30%), but decreased turnaround time by a similar proportion (3.3 to 2.3 days, figure 2). It also reduced turnaround times of ANA and ENA tests.Figure 2.Control chart of average TAT of dsDNA antibodies by request dateConclusion:Typically for a QI project, the initially simple CTD testing pipeline has accumulated many changes made without consideration of whole system performance, and is now a struggle to run.Improvement ideas to be explored from this work include:Liaising with main referral lab to develop a DNA monitoring workstream to reduce unnecessary ANA and ENA testingReduce handoffs, sample journey around lab analysers, and staff hands-on time by:changing ANA test methodology to same as DNAcreating new staff roles (analyser operators to perform validation/ authorisation steps)Create more capacity for ENA testing by increasing the frequency of this test on the weekly rotaCreate more capacity for service expansion by running analysers at weekends (staff consultation required)Reduce demand on service by engaging and educating requestorsImprove TAT for DNA by:processing samples the day they are booked in, instead of 1 day laterauto-validating runs…using control charts to measure improvementDisclosure of Interests:None declared

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