Samoylova Elena Mikhaylovna, Candidate of engineering sciences, associate professor, sub-department of automation, control, mechatronics, Yuri Gagarin State Technical University of Saratov (77 Politekhnicheskaya street, Saratov, Russia), email@example.com
Ignat'ev Aleksandr Anatol'evich, Doctor of engineering sciences, professor, sub-department of automation, control, mechatronics, Yuri Gagarin State Technical University of Saratov (77 Politekhnicheskaya street, Saratov, Russia), firstname.lastname@example.org
Background. The use of the expert decision support system (ESPPR) in real time improves the quality of decision-making, increases efficiency, specialists’ qualification, allows to analyze the quality of the process and the quality of manufactured products. The problem of development and usage of ESPPR in real time is a topical one in modern production and aims at reduction of the probability of making wrong decisions, and improvement of the quality of technological equipment.
Materials and methods. Of great scientific and practical interest is development and application of expert real-time systems to improve the efficiency of the grinding machining on CNC machines Weiss WKG-05 for various combinations of workpieces and abrasive tools.
Results. The work displays the results of practical studies of grinding of 85 workpieces in the production environment of CNC Weiss WKG-05, which served as the basis for determining the frequency of dressing of abrasive wheels and stablishing of the expert decision support system (EDSS). The authors developed the structure and the expert decision support system (ESPPR) in real time while controlling the efficiency of the grinding process for various combinations of workpieces and abrasive tools.
Conclusions. The use of ES allows to analyze the quality of the technological process, to increase the frequency abrasive tool dressing more than 2 times while maintaining the quality of details’ surface that enhances the effectiveness of treatment.
expert system, automated machine module, knowledge base, database, grinding model
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