Building an ontological information-analytical system to manage quality of double-glazed windows in the production of solar panels

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.219946

Keywords:

solar energy complexes, multi-layered double-glazed windows, quality management, ontological approach, efficiency evaluation metrics

Abstract

This paper reports an ontological approach to designing intelligent decision support to control the quality of multi-layered double-glazed windows within the framework of a virtual instrument-building enterprise (VIE) that produces solar energy complexes. It is shown that improving the efficiency in solving the tasks related to managing the quality of VIE products necessitates the application of an ontological engineering toolset to create a unified knowledge space that would cover the manufacturing phase of a product's life cycle. The methodical basis for making an ontological information-analytical system (OIAS) to manage product quality was the tool platform "TODOS" (Ukraine) whose means were used to synthesize a set of ontological models that make up the intelligent core of OIAS. The OIAS knowledge-based inference procedure has been described when making a decision about a deviation in the manufacturing process that led to the emergence of damage. This procedure implies the implementation of direct and reverse inference based on the knowledge in the ontological environment and makes it possible to identify the sources of defects and damage and generate a solution to eliminating these sources. Procedures have been devised to assess the effectiveness of the development and application of OIAS to automate the quality management of multi-layered double-glazed windows. These procedures employ a set of indicators that reflect both the technical and economic components of the quality control process. It has been shown that during 2019 a typical subcontractor enterprise that applied the developed system managed to reduce the number of defective products by about 73 %. Further research areas have been identified, including the development of methodical means and, based on them, the toolsets for the deployment of industrial ontological quality management systems

Author Biographies

Andrii Sobchak, National Aerospace University "Kharkiv Aviation Institute" Chkalova str., 17, Kharkiv, Ukraine, 61070

Doctor of Technical Sciences, Associate Professor

Department of Mechatronics and Electrical Engineering

Serhii Mykhalkiv, Ukrainian State University of Railway Transport Feierbakha sq., 7, Kharkiv, Ukraine, 61050

PhD, Associate Professor

Department of Maintenance and Repair of Rolling Stock

Mykhailo Babaiev, Ukrainian State University of Railway Transport Feierbakha sq., 7, Kharkiv, Ukraine, 61050

Doctor of Technical Sciences, Professor

Department of Electrical Power Engineering, Electrical Engineering and Electromechanics

Elena Zinchenko, Ukrainian State University of Railway Transport Feierbakha sq., 7, Kharkiv, Ukraine, 61050

PhD, Associate Professor

Department of Electrical Power Engineering, Electrical Engineering and Electromechanics

Olha Ananieva, Ukrainian State University of Railway Transport Feierbakha sq., 7, Kharkiv, Ukraine, 61050

Doctor of Technical Sciences, Associate Professor

Department of Automation and Computer Television Control of Train Traffic

Nataliie Kovshar, National Aerospace University "Kharkiv Aviation Institute" Chkalova str., 17, Kharkiv, Ukraine, 61070

Postgraduate Student

Department of Mechatronics and Electrical Engineering

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Published

2020-12-31

How to Cite

Sobchak, A., Mykhalkiv, S., Babaiev, M., Zinchenko, E., Ananieva, O., & Kovshar, N. (2020). Building an ontological information-analytical system to manage quality of double-glazed windows in the production of solar panels. Eastern-European Journal of Enterprise Technologies, 6(3 (108), 60–69. https://doi.org/10.15587/1729-4061.2020.219946

Issue

Vol. 6 No. 3 (108) (2020): Control processes

Section

Control processes

License

Copyright (c) 2020 Andrii Sobchak, Serhii Mykhalkiv, Mykhailo Babaiev, Elena Zinchenko, Olha Ananieva, Nataliie Kovshar

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