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An intelligent system for monitoring and optimization of ball-end milling process
Franc Čuš, Matjaž Milfelner, Jože Balič, 2006, izvirni znanstveni članek

Opis: The paper presents an intelligent system for on-line monitoring and optimization of the cutting process on the model of the ball-end milling. An intelligent system for monitoring and optimization in ball-end milling is developed both in hardware and software. It is based on a PC, which is connected to the CNC main processor module through a serial-port so that control and communication can be realised. The monitoring system is based on LabVIEW software, the data acquisition system and the measuring devices (sensors) for the cutting force measuring. The system collects the variables of the cutting process by means of sensors. The measured values are delivered to the computer program through the data acquisition system for data processing and analysis. The optimization technique is based on genetic algorithms for the determination of the cutting conditions in machining operations. In metal cutting processes, cutting conditions have an influence on reducing the production cost and time and deciding the quality of a final product. Experimental results show that the proposed genetic algorithm-based procedure for solving the optimization problem is effective and efficient, and can be integrated into a real-time intelligent manufacturing system for solving complex machining optimization problems.
Ključne besede: ball-end milling, cutting forces, monitoring, optimization
Objavljeno: 30.05.2012; Ogledov: 1127; Prenosov: 54
URL Povezava na celotno besedilo

Genetic equation for the cutting force in ball-end milling
Matjaž Milfelner, Janez Kopač, Franc Čuš, Uroš Župerl, 2005, izvirni znanstveni članek

Opis: The paper presents the development of the genetic equation for the cutting force for ball-end milling process. The development of the equation combines different methods and technologies like evolutionary methods, manufacturing technology, measuring and control technology and intelligent process technology with the adequate hardware and software support. Ball-end milling is a very common machining process in modern manufacturing processes. The cutting forces play the important role for the selection of the optimal cutting parameters in ball-end milling. In many cases the cutting forces in ball-end milling are calculated by equation from the analytical cutting force model. In the paper the genetic equation for the cutting forces in ball-end milling is developed with the use of the measured cutting forces and genetic programming. The experiments were made with the system for the cutting force monitoring in ball-end milling process. The obtained results show that the developed genetic equation fits very well with the experimental data. The developed genetic equation can be used for the cutting force estimation and optimization of cutting parameters. The integration of the proposed method will lead to the reduction in production costs and production time, flexibility in machining parameter selection, and improvement of product quality.
Ključne besede: milling, ball-end mill, optimization, cutting forces, cutting parameters, genetic algorithms
Objavljeno: 01.06.2012; Ogledov: 1186; Prenosov: 68
URL Povezava na celotno besedilo

An overview of data acquisition system for cutting force measuring and optimization in milling
Matjaž Milfelner, Franc Čuš, Jože Balič, 2005, izvirni znanstveni članek

Opis: This paper presents an approach, for the systematic design of condition monitoring system for machine tool and machining operations. The research is based on utilising the genetic optimization method for the on-line optimization of the cutting parameters and to design a program for the signal processing and for the detection of fault conditions for milling processes. Cutting parameters and the measured cutting forces are selected in this work as an application of the proposed approach.
Ključne besede: ball-end milling, cutting process, data acqusition, simulation, cutting forces
Objavljeno: 01.06.2012; Ogledov: 1073; Prenosov: 59
URL Povezava na celotno besedilo

Tool cutting force modeling in ball-end milling using multilevel perceptron
Uroš Župerl, Franc Čuš, 2004, izvirni znanstveni članek

Opis: This paper uses the artificial neural networks (ANNs) approach to evolve an efficient model for estimation of cutting forces, based on a set of input cutting conditions. A neural network algorithms are developed for use as a direct modeling method, to predict forces for ball-end milling operation. Supervised neural networks are used to successfully estimate the cutting forces developed during end milling process. The training of the networks is preformed with experimental machining data. The predictive capability of using analytical and neural network approaches are compared using statistics, which showed that neural network predictions for three cutting force components were for 4% closer to the experimental measurements, compared to 11% using analytical method. Exhaustive experimentation is conduced to develop the model and to validate it. The milling experiments prove that this model can predict accurately the cutting forces in three Cartesian directions.The force model can be used for simulation purposes and for defining threshold values in cutting tool condition monitoring system.
Ključne besede: ball end milling, cutting forces, modelling, artificial intelligence, neural networks
Objavljeno: 01.06.2012; Ogledov: 1217; Prenosov: 54
URL Povezava na celotno besedilo

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