ISSN 2079-3537      

 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                                                                                             





Scientific Visualization, 2018, volume 10, number 3, pages 108 - 120, DOI: 10.26583/sv.10.3.08

Using visualization tools for operational control of composite construction materials production

Authors: V.A. Kharitonov1, V.A. Golubev2, S.V. Leontev3, V.A. Shamanov4, A.D. Kurzanov5

Perm National Research Polytechnic University, Russia

1 ORCID: 0000-0002-9098-8627, cems@cems.pstu.ru

2 ORCID: 0000-0003-4930-7356

3 ORCID: 0000-0002-0659-3324

4 ORCID: 0000-0003-1938-0333

5 ORCID: 0000-0003-0550-012X

 

Abstract

The results of the software complex "Dekon-SM» development and application are presented in this article. The use of "Dekon-SM" data visualization tools allows the technologist to control the composite building materials production process. This helps to reduce defects and improve the products quality. The algorithm of intellectual decision support at management of composite building materials production technological process for the program full adaptation to real production conditions is offered. The algorithm implementation combined with the visualization tools using allow to graphically interpret and choose a limited number of compositions variants from a control alternatives set that provide the best values of building material quality indicators. The capabilities of the software complex "Dekon-SM" and its data visualization tools are revealed by the example of decision-making problem in the management of the aerated concrete components dosing process.

 

Keywords: program for PC, aerated concrete, visualization, regression dependencies, complex quality criterion, composite material, decision support.