F. Cus

Optimization of cutting process by GA approach

Abstract The paper proposes a new optimization technique based on genetic algorithms (GA) for the determination of the cutting parameters 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. This paper presents a new methodology for continual improvement of cutting conditions with GA. It performs the following: the modification of recommended cutting conditions obtained from a machining data, learning of obtained cutting conditions using neural networks and the substitution of better cutting conditions for those learned previously by a proposed GA. Experimental results show that the proposed genetic algorithm-based procedure for solving the optimization problem is both effective and efficient, and can be integrated into an intelligent manufacturing system for solving complex machining optimization problems.

Optimization of cutting conditions during cutting by using neural networks

Abstract 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.

Integral model of selection of optimal cutting conditions from different databases of tool makers

Abstract The contribution suggests some possibilities of the determination of cutting conditions for the cutting process. Flexibility and intelligence are indispensable factors in automation and manufacturing. For such demands, intelligent information systems are required, especially considering the technological date type. The process setting parameters have to be determined in the best suitable way. A central point of technological data are the cutting values feed and speed, especially because of their influence on cost, time, quality and security of the manufacturing process. The rapid development of new advanced materials, tools etc. cause the lack of qualified, actual machining values. The integral model represents integration of individual databases in the tool management system. The integral model of selection of optimal cutting conditions presented in the paper was developed from different databases taking into account the limitations of the cutting process. The optimization depends on the data on the workpiece (e.g. dimensions or the required grade of surface roughness), and also the data on the tool and the machine tool.

Simulation of cutting forces in ball-end milling

Abstract The paper presents a simulation system (SCP) that determines the cutting forces in the ball-end milling process. The system is based on numerical methods, computer programme, theoretical knowledge of technological processes, machining and tests performed. The system for simulation of the cutting process combines the technological data base, the analytical and experimental model and the data base SCP. The experimental model contains a collection of variables of the cutting process by means of sensors and transformation of those data into numerical values, which are a starting point for data calculation of characteristic coefficients of materials. The analytical model is used to estimate the tangential, radial and axial cutting forces, along with a material data base obtained from cutting experiments. Ball-end milling test has been conducted to verify simulation results. The simulation results, are the basis for the development of the tool-designing model and for the model of optimization of the machining process cutting parameters.

SELECTION OF CUTTING CONDITIONS AND TOOL FLOW IN FLEXIBLE MANUFACTURING SYSTEM

Abstract Modern production requires minimum costs and maximum productivity of cutting processes. By using the simultaneous engineering, it is possible to include the processes of optimization of cutting conditions and tool flow already in the integrated preparation of the product and processes and in the parallel program of all activities. This paper presents the experience gained in concrete researches in industry.

Organization of tool supply and determination of cutting conditions

Abstract The tool supply system is intended to feed the tools to metal-working machines taking into account the time, quantity, position and target and also the tool removal. As a matter of fact, it represents a subsystem of the superior tool system. For a trouble-free flow the following functions are needed: purchase, arrangement, readiness, pre-setting and maintenance. In this paper, a model is proposed for selection of optimal cutting conditions obtained from different data bases by taking into account the limitations of the cutting process. The developed model selects optimal cutting conditions with respect to the data on the workpiece, such as dimensions and required degree of surface roughness, the data on tool and the data on the machine tool.

Model of complex optimization of cutting conditions

Modern flexible production with its JUST-IN-TIME philosophy requires efficient organization, high quality tools, selected machining materials with defined mechanical and technological properties and continual determination and optimization of cutting conditions. Therefore, for successful production it is necessary to carry out a number of studies with the purpose to optimize the cutting conditions which should include understanding of tribological problems, the cutting material properties, cooling agent and its application. The rationality and economy of manufacturing which are a result of material and energy saving and shorter machining times, depend to a large extent on the right choice of selected cutting conditions and required product quality. This paper deals with the development of a model for complex optimization of cutting conditions showing that the right way from optimal cutting conditions to product quality is via process quality.

Model of a universal manufacturing interface in CIM for small- and medium-sized companies

Abstract This paper deals with the development of a universal manufacturing interface which enables data exchange between several sub-systems that are included in a production system. The interface has been created especially for small- and medium-sized companies and is a very important part of flexible manufacturing systems. The basic concept of a production system integration is defined. The production system is treated as a computer-aided process information system. The solution discussed is a contribution to the integration of production processes, the system being adaptable to existing real-production processes with the lowest possible expense and with minimum changes in the company employee structure. With this condition the usage of open-system architecture is not possible, so that the problem must be solved with existing sub-systems in the production process, which are generally closed and incompatible with other sub-systems.

Optimization in ball-end milling by using adaptive neural controller

In this paper, a neural controller with optimisation for the ball end milling process is described. An 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 learn the appropriate mappings between the input and output variables of the machining process. The feedrate is selected as the optimised variable, and the milling state is estimated by the measured cutting forces. 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.

Planning of tool supply to a group of machines

Abstract Flexibility is defined as the ability to respond effectively to changing circumstances. A need for wider product scopes and the trend towards shorter product life cycles are some factors that make flexibility a top priority issue in manufacturing strategy. The requested tools delivery flexibility will imply a faster production response. Planning of tool supply to a group of machines is simplified by the use of computerized monitoring [QM and cost optimization in machining of Al-alloys, Proceedings of the Sixth World Congress on Total Quality, Institute of Directory, New Delhi, 1996; Einsatz der Computersimulation fur die Auslegung und Steuerung von FFS, Proceedings of the DAAAM Symposium, Vienna, Austria, October 1996, pp. 203–204. ISBN 3-901509-02-X]. In this paper, the authors propose a new ordering model for the tools transportation problem based on the depot system. Order scales are used as decision parameters for planing tools consumption. The model has been tested with an example and computational results that verify the effectiveness of the model are shown with the help of the EXCEL program.