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1.
A model of surface roughness constitution in the metal cutting process applying tools with defined stereometry
Stanisĺaw Adamczak, Edward Miko, Franc Čuš, 2009, izvirni znanstveni članek

Opis: The process of surface roughness formation is complex and dependent on numerous factors. The analysis of the latest reports on the subject shows that mathematical relationships used for determining surface irregularities after turning and milling are not complete or accurate enough and, therefore, need to be corrected. A new generalized mathematical model of roughness formation was developed for surfaces shaped with round-nose tools. The model provides us with a quantitative analysis of the effects of the tool representation, undeformed chip thickness, tool vibrations in relation to the workpiece, tool runout (for multicutter tools) and, indirectly, also tool wear. This model can be used to prepare separate models for most of the typical machining operations. Surface roughness is represented here by two parameters Ra and Rt. Simulations carried out for this model helped to develop nomograms which can be used for predicting and controlling the roughness Ra of surfaces sculptured by face milling.
Ključne besede: metal cutting, surface roughness, finishing, face milling
Objavljeno: 31.05.2012; Ogledov: 1064; Prenosov: 9
URL Povezava na celotno besedilo

2.
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: 1026; Prenosov: 28
URL Povezava na celotno besedilo

3.
Approach to optimization of cutting conditions by using artificial neural networks
Franc Čuš, Uroš Župerl, 2006, izvirni znanstveni članek

Opis: Optimum selection of cutting conditions importantly contribute to the increase of productivity and the reduction of costs, therefore utmost attention is paid to this problem in this contribution. In this paper, a neural network-based approach to complex optimization of cutting parameters is proposed. It describes the multi-objective technique of optimization of cutting conditions by means of the neural networks taking into consideration the technological, economic and organizational limitations. To reach higher precision of the predicted results, a neural optimization algorithm is developed and presented to ensure simple, fast and efficient optimization of all important turning parameters. The approach is suitable for fast determination of optimum cutting parameters during machining, where there is not enough time for deep analysis. To demonstrate the procedure and performance of the neural network approach, an illustrative example is discussed in detail.
Ključne besede: optimization, cutting parameter optimization, genetic algorithm, cutting parameters, neural network algorithm, machining, metal cutting
Objavljeno: 30.05.2012; Ogledov: 1223; Prenosov: 38
URL Povezava na celotno besedilo

4.
Machining process optimization by colony based cooperative search technique
Uroš Župerl, Franc Čuš, 2008, izvirni znanstveni članek

Opis: Research of economics of multi-pass machining operations has significant practical importance. Non-traditional optimization techniques such genetic algorithms, neural networks and PSO optimization are increasingly used to solve optimization problems. This paper presents a new multi-objective optimization technique, based on ant colony optimization algorithm (ACO), to optimize the machining parameters in turning processes. Three conflicting objectives, production cost, operation time and cutting quality are simultaneously optimized. An objective function based on maximum profit in operation has been used. The proposed approach uses adaptive neuro-fuzzy inference system (ANFIS) system to represent the manufacturer objective function and an ant colony optimization algorithm (ACO) to obtain the optimal objective value. New evolutionary ACO is explained in detail. Also a comprehensive userfriendly software package has been developed to obtain the optimal cutting parameters using the proposed algorithm. An example has been presented to give a clear picture from the application of the system and its efficiency. The results are compared and analysed using methods of other researchers and handbook recommendations. The results indicate that the proposed ant colony paradigm is effective compared to other techniques carried out by other researchers.
Ključne besede: machining, turning, optimization, cutting parameters
Objavljeno: 31.05.2012; Ogledov: 959; Prenosov: 14
URL Povezava na celotno besedilo

5.
Turning of high quality aluminium alloys with minimum costs
Marko Reibenschuh, Franc Čuš, Uroš Župerl, 2011, izvirni znanstveni članek

Opis: Turning is one of the most common metal cutting procedures used. To optimize such a cutting process, some adaptations must be made. Implementing tool wear conditioning and the use of dry cutting can significantly lower the production cost. This research focuses on the cost effectiveness of using dry cutting in comparison with the use of cutting fluids and the use of different tool geometry. A series of tests was conducted and in the end the results are given.
Ključne besede: aluminium, cutting fluids, production costs, turning
Objavljeno: 01.06.2012; Ogledov: 718; Prenosov: 54
.pdf Celotno besedilo (315,97 KB)
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6.
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: 1042; Prenosov: 37
URL Povezava na celotno besedilo

7.
A generalized neural network model of ball-end milling force system
Uroš Župerl, Franc Čuš, Bogomir Muršec, Anton Ploj, 2005, izvirni znanstveni članek

Opis: The focus of this paper is to develop a reliable method to predict 3D cutting forces during ball-end milling process. This paper uses the artificial neural networks (ANNs) approach to evolve an generalized model for prediction of cutting forces, based on a set of input cutting conditions. A set of ten input milling parameters that have a major impact on the cutting forces was chosen to represent the machining conditions. The training of the networks is performed with experimental machining data. This approach greatly reduces the time-consuming mathematical work normally required for obtaining the cutting force expressions. The estimation performance of the network is evaluated through a detailed simulation study. The accuracy of an analytical model, which is a feasible alternative to the network, is compared to that of the network. With similar system parameter estimates for both methods, the network is found to be considerably more accurate than the analytical model. The results of model validation experiments on machining Ck45 are also reported. Experimental results demonstrate that this method can accurately estimate feed cutting force within an error of 4%. The results also indicate that when the combination of sigmoidal and gaussian transfer function were applied, the prediction accuracy of neural network is as high as 98%.
Ključne besede: end-milling, cutting forces, cutting parameters, generalized neural networks, modeling
Objavljeno: 01.06.2012; Ogledov: 1344; Prenosov: 21
URL Povezava na celotno besedilo

8.
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: 972; Prenosov: 33
URL Povezava na celotno besedilo

9.
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: 01.06.2012; Ogledov: 1251; Prenosov: 28
URL Povezava na celotno besedilo

10.
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: 1043; Prenosov: 26
URL Povezava na celotno besedilo

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