Improving the quality of the technological process of packaging shape formation based on the information structure of an automated system

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.205226

Keywords:

quality monitoring algorithm, statistical methods, information structure, shape formation, polyethylene terephthalate, control system

Abstract

Based on the information structure of an automated quality monitoring system, we have designed a system to analyze information on the quality of forming the shape of PET-packaging, with a possibility of statistical control over the technological process using Shewhart control charts. That has been demonstrated using an example of the proposed technique of quality estimation of the finished PET bottles based on the thickness of their walls. Obtaining high-quality PET-packaging directly depends on the degree of perfection of all technological stages, thereby predetermining the necessity to build an effective system to control and manage the technological process of the shape formation of bottles made from polyethylene terephthalate.

An analysis of information about the quality of PET-packaging shape formation based on monitoring the information structure of an automated system would make it possible to ensure operative adjustment of shape forming parameters at the minimized percentage of defects by organizing selective control over the products made. The use of statistical methods based on Shewhart control charts could enable the development of authentic algorithms for monitoring the shape formation quality aimed to track violations of technological parameters and compile recommendations on improving the process quality, as well as resource-use efficiency.

The statistical estimation of cause-effect relations between the main technological parameters and product quality indicators involves the algorithm that monitors the quality of PET-packaging shape formation. This makes it possible to ensure the minimum level of defects in bottles when applying the devised Shewhart control chart.

We have proposed a fuzzy cognitive chart for defining the preventive corrective actions directed at the elimination of the main causes of a defect at bottle shape formation, taking into consideration the interrelations of factors and their consequences on the resulting process quality

Author Biographies

Mariana Sashnova, Kyiv National University of Trade and Economics Kуоtо str., 19, Kуiv, Ukrаinе, 02156

PhD, Associate Professor

Department of Software Engineering and Cybersecurity

Andreii Zahorulko, Kharkiv State University of Food Technology and Trade Klochkivska str., 333, Kharkiv, Ukraine, 61051

PhD, Associate Professor

Department of Processes, Devices and Automation of Food Production

Tetiana Savchenko, Kyiv National University of Trade and Economics Kуоtо str., 19, Kуiv, Ukrаinе, 02156

PhD, Associate Professor

Department of Software Engineering and Cybersecurity

Sergii Gakhovich, Kyiv National University of Trade and Economics Kуоtо str., 19, Kуiv, Ukrаinе, 02156

PhD, Associate Professor, Senior Researcher

Department of Engineering and Technical Disciplines

Ivan Parkhomenko, Taras Shevchenko National University of Kyiv Volodymyrska str., 60, Kуiv, Ukrаinе, 01033

PhD, Associate Professor

Department of Cybersecurity and Information Protection

Dima Pankov, National University of Food Technologies Volodymyrska str., 68, Kyiv, Ukraine, 01601

PhD

Department of Automation and Computer Technology of Control Systems

References

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Published

2020-06-30

How to Cite

Sashnova, M., Zahorulko, A., Savchenko, T., Gakhovich, S., Parkhomenko, I., & Pankov, D. (2020). Improving the quality of the technological process of packaging shape formation based on the information structure of an automated system. Eastern-European Journal of Enterprise Technologies, 3(2 (105), 28–36. https://doi.org/10.15587/1729-4061.2020.205226

Issue

Vol. 3 No. 2 (105) (2020): Information technology. Industry control systems

Section

Information technology

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Copyright (c) 2020 Mariana Sashnova, Andreii Zahorulko, Tetiana Savchenko, Sergii Gakhovich, Ivan Parkhomenko, Dima Pankov

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