A novel method for statistical process control of gate oxide and front-end cleans monitoring in a manufacturing environment

2002 ◽  
Author(s):  
R.G. Cosway ◽  
L.S. Pirastehfar ◽  
R.P. Root ◽  
T.S. Roche ◽  
J.R. Naujokaitis
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Gate Oxide ◽  
Manufacturing Environment ◽  
Statistical Process ◽  
Front End ◽  
Novel Method

Application of a Computer Based System for Statistical Process Control in a Semiconductor Company : A Case Study

2012 ◽  
Vol 59 (2) ◽  
Author(s):  
Nor Kamaliana Khamis ◽  
Baba Md Deros ◽  
Nizaroyani Saibani ◽  
Syamsinar Baizura Ahmad Sabki
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Semiconductor Manufacturing ◽  
Human Error ◽  
Early Stage ◽  
Manufacturing Environment ◽  
Statistical Process ◽  
Computer Based ◽  
Recent Trends

The use of Statistical Process Control (SPC) in the manufacturing process has been historically proven to increase the quality of the product. Recent trends show that companies are becoming increasingly reliant on computer based-SPC because it can save a significant amount of time compared with traditional SPC. In addition, labor-intensive tasks, such as manual data collection and entry, can be eliminated, thus reducing human error. This paper aims to prove the benefits of computer based system for SPC known as e-SPC in a semiconductor manufacturing environment. Specifically, this paper will present the case study‟s finding that show how one semiconductor manufacturing company‟s use of e-SPC can detect a process abnormality at an early stage and in real time compared with manual SPC. The case study involves interviews with the company representatives and observations on the manufacturing environment. This paper will also show how e-SPC can be used to control and then to stabilize the manufacturing operation. In conclusion, this paper demonstrates that e-SPC can significantly improve the performance of a manufacturing environment. Moreover, this paper can also be used as a reference for the implementation of e-SPC in any company.

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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