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Intelligent adaptive cutting force control in end-milling
Uroš Župerl, Franc Čuš, Edvard Kiker, 2006, izvirni znanstveni članek

Opis: In this article, an adaptive neural controller for the ball end-milling process is described. Architecture with two different kinds of neural networks is proposed, and is used for the on-line optimal control of the milling process. A BP neural network is used to identify the milling state and to determin the optimal cutting inputs. The feedrate is selected as the optimised variable, and the milling state is estimated by the measured cutting force. The adaptive controller is operated by a PC and the adjusted feedrates are sent to the CNC. The purpose of this article is to present a reliable, robust neural controller aimed at adaptively adjusting feed-rate to prevent excessive tool wear, tool breakage and maintain a high chip removal rate. The goal is also to obtain an improvement of the milling process productivity by the use of an automatic regulation of the cutting force. Numerous simulations are conducted to confirm the efficiency of this architecture. The proposed architecture for on-line determining of optimal cutting conditions is applied to ball end-milling in this paper, but it is obvious that the system can be extended to other machines to improve cutting efficiency.
Ključne besede: end milling, adaptive force control, neuron controller, cutting conditions, adaptive control systems
Objavljeno v DKUM: 12.07.2017; Ogledov: 1116; Prenosov: 126
.pdf Celotno besedilo (3,43 MB)
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Databases for technological information systems
Franc Čuš, Bogomir Muršec, 2004, izvirni znanstveni članek

Opis: Organization of tool management for mixed production includes today, in particular, the computer-supported management and organization of the flow of tools and data on them. The system supports the entire flow of tools in a production process including the tool store management, commissioning, mounting, dismantling and pre-setting of tools. The system contains the management of the tool database with all vital data on tools and ensures adaption of production requirements for meeting the needs for tools. The integral model for the selection of optimal cutting conditions in the computer aided tool management system (TOMS) is proposed. The integration of technological databases and tool management systems is urgently necessary. The target function for the OPTIS programme, worked out by the programme package Microsoft Visual Basic, is selection of optimal cutting conditions from commercial databases with respect to the lowest costs of machining by taking into account the technological limitations of the metal removal process. The newly developed OPTIS programme selects optimal cutting conditions with respect to the tool maker, workpiece material, type of machining, cutting machine, smallest and greatest cutting conditions, tool, data on series, type of clamping and workpiece geometry.
Ključne besede: machining processes, tool system, manufacturing systems, technological information systems, databases, tool management, machining systems, cutting conditions
Objavljeno v DKUM: 01.06.2012; Ogledov: 3871; Prenosov: 95
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A Hybrid analytical-neural network approach to the determination of optimal cutting conditions
Uroš Župerl, Franc Čuš, Bogomir Muršec, Anton Ploj, 2004, izvirni znanstveni članek

Opis: In the contribution, a new hybrid optimization technique for complex optimization of cutting parameters is proposed. The developed approach is based on the maximum production rate criterion and incorporates 10 technological constrains. It describes the multi-objective techniqueof optimization of cutting conditions by means of the artificial neural network (ANN) and OPTIS routine by taking into consideration the technological, economic and organization limitations. The analytical module OPTIS selects theoptimum cutting conditions from commercial databases with respect to minimum machining costs. By selection of optimum cutting conditions, it is possible to reach a favourable ratio between the low machining costs and high productivity taking into account the given limitation of the cutting process. To reach higher precision of the predicet results, a hybrid optimization algorithm is developed and presented to ensure sample, fast and efficient optimization of all important turning parameters. _
Ključne besede: optimization, cutting conditions, turning, analytical-neural routine, database
Objavljeno v DKUM: 01.06.2012; Ogledov: 2296; Prenosov: 89
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