Guide to the selection of charting methods and capability assessment for use in statistical process control

2015 ◽  
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Statistical Process ◽  
Selection Of

scholarly journals Measures Suitable for SPC: A Systematic Mapping

2016 ◽  
Author(s):  
Daisy Ferreira Brito ◽  
Monalessa Perini Barcellos
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Statistical Process ◽  
High Maturity ◽  
Software Processes ◽  
Selection Of

The growing interest of organizations in improving their software processes has lead them to aim at achieving the high maturity, where statistical process control (SPC) is demanded. Through SPC is possible to know processes behavior, predict their performance in future projects and monitor them in order to meet the stablished goals. One of the challenges to perform SPC is the selection of measures suitable for it. Although the literature suggests measures to be used in SPC, information is dispersed. Aiming to provide a consolidated set of measures useful for SPC, as well as the related processes and goals supported by the measures, we conducted a mapping study. This paper presents the study and discusses the main findings.

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  

scholarly journals APSS – Software Support for Decision Making in Statistical Process Control

2018 ◽  
Vol 22 (3) ◽  
pp. 19
Author(s):  
Darja Noskievicova
Keyword(s):  
Active Learning ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Chart ◽  
Control Charts ◽  
Statistical Process ◽  
Software Support ◽  
Research Activities ◽  
Problem Solving Process ◽  
Selection Of

<p><strong>Purpose:</strong> SPC can be defined as the problem solving process incorporating many separate decisions including selection of the control chart based on the verification of the data presumptions. There is no professional statistical software which enables to make such decisions in a complex way.</p><p><strong>Methodology/Approach:</strong> There are many excellent professional statistical programs but without complex methodology for selection of the best control chart. Proposed program in Excel APSS (Analysis of the Process Statistical Stability) solves this problem and also offers additional learning functions.</p><p><strong>Findings:</strong> The created SW enables to link altogether separate functions of selected professional statistical programs (data presumption verification, control charts construction and interpretation) and supports active learning in this field.</p><p><strong>Research Limitation/implication: </strong>The proposed SW can be applied to control charts covered by SW Statgraphics Centurion and Minitab. But there is no problem to modify it for other professional statistical SW.</p><strong>Originality/Value of paper: </strong>The paper prezents the original SW created in the frame of the research activities at the Department of Quality Management of FMT, VŠB-TUO, Czech Republic. SW enables to link altogether separate functions of the professional statistical SW needed for the complex realization of statitical process control and it is very strong tool for the active learning of statistical process control tasks.

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.

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