Introduction to Statistical Process Control and Nonspatial Cumulative Sum Methods of Surveillance

2008 ◽  
pp. 157-183
Author(s):  
Ikuho Yamada
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Cumulative Sum ◽  
Statistical Process

scholarly journals Distribution-Free CUSUM-Type Control Charts for Monitoring Industrial Processes: An Overview

2021 ◽  
Vol 6 (4) ◽  
pp. 975-1008
Author(s):  
Ioannis S. Triantafyllou ◽  
Mangey Ram
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Crucial Role ◽  
Control Charts ◽  
Industrial Processes ◽  
Cumulative Sum ◽  
Statistical Process ◽  
Distribution Free ◽  
Practical Applications ◽  
Memory Type

In the present paper we provide an up-to-date overview of nonparametric Cumulative Sum (CUSUM) monitoring schemes. Due to their nonparametric nature, such memory-type schemes are proved to be very useful for monitoring industrial processes, where the output does not match to a particular distributional model. Several fundamental contributions on the topic are mentioned, while recent advances are also presented in some detail. In addition, some practical applications of the nonparametric CUSUM-type control charts are highlighted, in order to emphasize their crucial role in the contemporary online Statistical Process Control.

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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