Building an ontological information-analytical system to manage quality of double-glazed windows in the production of solar panels
| Autor: | Olha Ananieva, Serhii Mykhalkiv, Elena Zinchenko, Nataliie Kovshar, Mykhailo Babaiev, Andrii Sobchak |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Quality management
multi-layered double-glazed windows Knowledge space Process (engineering) Computer science efficiency evaluation metrics 020209 energy media_common.quotation_subject Control (management) 0211 other engineering and technologies Energy Engineering and Power Technology Inference 02 engineering and technology Industrial and Manufacturing Engineering Management of Technology and Innovation 021105 building & construction 0202 electrical engineering electronic engineering information engineering T1-995 Industry Quality (business) Electrical and Electronic Engineering Technology (General) media_common solar energy complexes business.industry Applied Mathematics Mechanical Engineering HD2321-4730.9 ontological approach Computer Science Applications Quality management system Control and Systems Engineering Software deployment Software engineering business quality management |
| Zdroj: | Eastern-European Journal of Enterprise Technologies, Vol 6, Iss 3 (108), Pp 60-69 (2020) |
| Popis: | 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 |
| Databáze: | OpenAIRE |
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