scholarly journals KONSEP DAN TEKNIK MANAIEMEN MUTU TERPADU

2017 ◽  
pp. 94-101
Author(s):  
Saut Pruba
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Employee Empowerment ◽  
Just In Time ◽  
Statistical Process

Quality is a term that has diflferent meanings to different people. Quality set out in this paper are the features and characteristics of the total of a product or service associated with its ability to satisfij the needs of the visible or disguised. The quality of the environment requires an establishment of TQM because quality can not be examined only in a product. In this paper also discussed the concept of the seven TQM: continuous improvement, Six Sigma, employee empowerment, benchmarking, just in time, the concept of Taguchi TQM techniques and knowledge. TQM is the seventh technique check sheet, scatter diagrams, cause-effect diagrams, Pareto charts, flow charts, histograms, and statistical process control.

scholarly journals Fertilizer deposition as a function of angular velocity and inclination of the helical dosing mechanism

2022 ◽  
Vol 26 (3) ◽  
pp. 226-235
Author(s):  
Gabriel G. Zimmermann ◽  
Samir P. Jasper ◽  
Daniel Savi ◽  
Leonardo L. Kmiecik ◽  
Lauro Strapasson Neto ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Process Control ◽  
Statistical Process Control ◽  
Industrial Process ◽  
Descriptive Statistics ◽  
Flow Data ◽  
Statistical Process ◽  
Flow Rates ◽  
Angular Velocities

ABSTRACT The establishment of grain crops in Brazil is an important industrial process in the agricultural chain, requiring the correct deposition of granular fertilizer over the sowing furrow and more efficient, precise, and sustainable assessments in the operation, which can be achieved with the statistical process control. This study aimed to assess the effect of the angular velocity on different inclinations of the helical metering mechanism on the granular fertilizer deposition. An automated electronic bench was used to assess the deposition quality of granular fertilizers considering different angular velocities (1.11, 1.94, and 2.77 m s-1) and longitudinal and transverse inclinations (+15, +7.5, 0, −7.5, and −15°), with the helical doser by overflow. Flow data were collected and submitted to descriptive statistics and statistical process control. The metering mechanism showed expected variations, with acceptable performance under process control. The values of the flow rates of the granular fertilizer increased as velocity increased, standing out longitudinal inclinations of +7.5 and +15°, providing higher fertilizer depositions.

A Case Study in Quality Improvement of Precision Turned Components

1996 ◽  
Vol 210 (6) ◽  
pp. 589-595 ◽  
Author(s):  
L Carter ◽  
C Butler
Keyword(s):  
Quality Improvement ◽  
Process Control ◽  
Statistical Process Control ◽  
Batch Size ◽  
Just In Time ◽  
Statistical Process ◽  
Measurement Capability ◽  
Analysis Measurement ◽  
Engineering Company ◽  
Batch Sizes

The company participating in this study had recently reorganized its factory layout, moving from a traditional layout to machining cells. The company was a light engineering company; the cells consisted of turning centres, each cell catering for a different family grouping of components. An associated change in production methods was the move to ‘just-in-time manufacture’. The consequences of these changes were that the batch sizes had reduced considerably so that now the maximum batch size was 20 and the average only 3 or 4. The company had previously used statistical process control (SPC), but with such small batch sizes the practice had fallen into disuse as the traditional software was no longer appropriate. The general objective of the study was therefore to investigate their current situation and recommend a systematic approach to quality improvement. The study employed non-conformance analysis, measurement capability studies and analysis of variance leading to an appropriate statistical process control methodology. The company initially employed near to 100 per cent inspection; nevertheless, significant quality improvement was achieved.

QUALIDADE NA COLHEITA MECANIZADA DE MILHO SEMEADO EM DIFERENTES VELOCIDADES

2016 ◽  
Vol 15 (3) ◽  
pp. 582 ◽  
Author(s):  
ANTONIO TASSIO SANTANA ORMOND ◽  
MURILO APARECIDO VOLTARELLI ◽  
CARLA SEGATTO STRINI PAIXÃO ◽  
ALINE SPAGGIARI ALCÂNTARA1 ◽  
ELIZABETH HARUNA KAZAMA ◽  
...  
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Plant Density ◽  
Plant Population ◽  
Longitudinal Distribution ◽  
Statistical Control ◽  
Individual Values ◽  
Sowing Time ◽  
Statistical Process

RESUMO - As perdas na colheita podem estar relacionadas tanto a colhedora, como também a fatores ligados a cultura como: mau preparo do solo, densidade de plantas, inadequação da época de semeadura são alguns deles. O presente estudo objetivou determinar a influência da velocidade de semeadura no processo de colheita mecanizada de milho, por meio do controle de qualidade do processo. O experimento foi conduzido em Latossolo Vermelho, textura argilosa e relevo suave ondulado. O delineamento foi baseado na óptica do Controle Estatístico de ProcessoCEP, onde os dados foram coletados em pontos aleatórios em função do tempo. Os indicadores de qualidade avaliados foram divididos em parâmetros de semeadura (população de plantas e distribuição longitudinal de plântulas); e de colheita (Perdas de grãos e distribuição de palha) em função de seis velocidades de deslocamento (aproximadamente 2,0; 4,0; 6,0; 9,0; 10,0 e 12,0 Km.h-1). Os dados foram submetidos a análise descritiva para análise do comportamento. Como ferramentas do controle estatístico de processo utilizou-se, run charts ou gráfico sequencial e carta de controle de valores individuais para análise da qualidade do processo. A maior velocidade (V6) apresentou a maior variabilidade dos dados para todas as variáveis. A operação da colheita mecanizada de milho foi influenciada por fatores extrínsecos e intrínsecos a ela.Palavras-chave: Controle estatístico de processo, espaçamentos normais, perdas, população de plantas.QUALITY IN MECHANIZED HARVEST OF CORN SOWN IN DIFFERENT SPEEDSABSTRACT - The harvest losses may be associated to harvester as well as factors related to cultivation such as poor soil preparation, plant density, unsuitable sowing time. This study aimed to determine the effect of speed sowing in the mechanized harvest of corn, through the control of the quality of the process. The experiment was conducted in a clayey Oxisol and undulate relief. The design was based on the optics of the Statistical Process Control SPC, and the data were collected at random points in function of time. The quality indicators evaluated were divided into sowing parameters (plant population and longitudinal distribution of seedlings) and harvesting (loss of grain and straw distribution) in function of six displacement speeds (approximately 2.0, 4.0, 6.0, 9.0, 10.0 and 12.0 Km.h-1). The data were submitted to descriptive analysis for behavior analysis. As tools for the statistical control of the process, run charts or sequential graph were used, and control chart of individual values for analysis of the quality of the process. The highest speed (V6) showed the highest variability of the data for all variables. The operation of mechanized harvest of corn was influenced by extrinsic and intrinsic factors.Keywords: statistical process control, normal spacings, losses, plant population.

scholarly journals The Impact of Statistics in Industry and the Role of Statisticians

2016 ◽  
Vol 30 (1) ◽  
pp. 7-20
Author(s):  
Ronald J.M.M. Does ◽  
Albert Trip
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Six Sigma ◽  
Practical Experience ◽  
Successful Implementation ◽  
Statistical Process ◽  
Quality Program ◽  
Quality Programs ◽  
The Impact

The use of statistics in quality management has a long history. Pioneers in this field, such as Walter A. Shewhart and W. Edwards Deming, refer to themselves as industrial statisticians. Statistical thinking in industry means that all work is regarded as a series of interconnected processes, that all processes show variation, and that a reduction in variation is the key for continuous improvement. In literature we find several quantitative quality programs to achieve this. We may mention Statistical Process Control (SPC)and the Six Sigma quality program, among others. We have implemented Statistical Process Control and Six Sigma in several industries. In this paper we briefly describe the philosophies of both programs and the steps needed for a successful implementation. Based on practical experience with both programs we describe the role that a statistician can play in industry. We shall also give an overview of research initiated by the projects we have carried out.

scholarly journals Porcelain Product Quality Analysis in PT XYZ

2015 ◽  
Vol 6 (4) ◽  
pp. 580
Author(s):  
Ho Hwi Chie ◽  
Januar Nasution ◽  
Ketut Gita Ayu ◽  
Nike Septivani ◽  
Yualfin Renaldi
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Management Tools ◽  
Statistical Process ◽  
Tree Analysis ◽  
Porcelain Product ◽  
Product Defect

PT. XYZ is a company engaged in manufacturing porcelain dinner ware such as plates, cups, teapot, bowl, etc Porcelain product is safe for use and product defect will only affect the aesthetic not the functional side. The company always maintain the quality of the products produced as by maintaining a good product, in terms of visuals, will keep customers interested in the product. Good quality products characterized by quality A / B and C, and the product defect characterized by the quality of D, Lost, and BU. Concepts and methods used to analyze is a statistical process control (SPC) which includes Pareto diagram, fraction nonconformities, flow charts and fishbone diagrams and management tools (fault tree analysis). Statistical Process Control (SPC) is one of the methods, which includes Pareto charts, fraction nonconformities, flow chart, and fishbone diagram and also management tools (fault tree analysis). SPC is useful to find the facts from the problems and factors that affect the quality of the products, while fault tree analysis is useful to analyze each of the production process.

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