Wyniki wyszukiwania - BazTech

1

Development process and manufactu-ring of modern medical implants with LENS technology

Balazic M., Recek D., Kramar D., Milfelner M., Kopac J.

Journal of Achievements in Materials and Manufacturing Engineering

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2009

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Vol. 32, nr 1

46-52

EN

Purpose: Research and development of modern medical implants is complex and demanding process focused on fulfilling requirements regarding materials, machining technologies and functionality. Typical example of modern medical implant is elbow nail for fixation of Caput radii fractures. It could be manufactured with classical machining technologies and with advanced Rapid Prototyping technologies such as highly targeted metal deposition technology LENS (Laser Engineered Net Shaping). Design/methodology/approach: Development of modern medical implants is a multi-stage design and manufacturing process primarily based on computer aided design (CAD), computer simulations, machinability of certificated biomaterials, in-vitro biofunctionality and in-vivo tests. Findings: LENS technology enables rapid and agile manufacturing, improved design flexibility, repair and re-manufacture. Material built with LENS technology has equal or even better mechanical and material properties. In medical application LENS technology enables development and rapid prototyping of special surgical instruments, trauma and orthopaedic high-performance implants which are hollow and thin walled. Research limitations/implications: To confirm assumption regarding better material and mechanical properties of products made with LENS technology additional static, dynamic (the High-Cycle-Fatigue test) and material (porosity and microstructure) tests will be carried out in the near future. Practical implications: Three different designs of bone fixation nail prototype made of titanium alloy had been manufactured with conventional machining techniques where some disadvantages due to the technology had been identified. To solve those problems LENS technology had been applied. As fourth design hollow thin walled fixation bone nail prototype made of titanium alloy powder (grain size 45 micrometers) had been manufactured and tested. Originality/value: Paper presents case study where LENS technology is being applied to manufacture modern medical implants. Particular focus of the paper is on material quality and quality benefits obtained in current and future medical application.

2

Adaptive self-learning controller design for feedrate maximisation of machining process

Cus F., Zuperl U., Kiker E., Milfelner M.

Journal of Achievements in Materials and Manufacturing Engineering

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2008

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Vol. 31, nr 2

469-476

EN

Purpose: Of this paper: The purpose of this paper is to built an adaptive control system which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters. Design/methodology/approach: The paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization) in modeling and adaptively controlling the process of end milling. An overall approach of hybrid modeling of cutting process (ANfis-system), used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS) consisting of two neural identificators of the process dynamics and primary regulator. Findings: The research has shown that neural control scheme has significant advantages over conventional controllers. The experimental results show that not only does the milling system with the design controller have high robustness, and global stability but also the machining efficiency of the milling system with the adaptive controller is much higher than for traditional CNC milling system. Experiments have confirmed efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear. Research limitations/implications: 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. In this way the system compensates all disturbances during the cutting process: tool wear, non-homogeneity of the workpiece material, vibrations, chatter etc. Practical implications: The results of experiments demonstrate the ability of the proposed system to effectively regulate peak cutting forces for cutting conditions commonly encountered in end milling operations. Applicability of methodology of adaptive adjustment of cutting parameters is experimentally demonstrated and tested on a 4-axis CNC milling machine Heller. The high accuracy of results within a wide range of machining parameters indicates that the system can be practically applied in industry. Originality/value: By the hybrid process modeling and feed-forward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of cutting parameters is built.

3

Intelligent system for machining and optimization of 3D sculptured surfaces with ball-end milling

Milfelner M., Kopac J., Cus F., Zuperl U.

Journal of Achievements in Materials and Manufacturing Engineering

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2006

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Vol. 14, nr 1-2

171--177

EN

Purpose: This paper describes about intelligent machining system which is applied in a high speed machining robot with on-line monitoring and optimization for ball-end milling process. Design/methodology/approach: Manufacturing of 3D sculptured surfaces on high speed machining robot involves a number of machining parameters and tool geometries. The system collects machining data and cutting parameters which are necessary for genetic algorithm optimization. Findings: An intelligent machining system is developed for the simulation and testing on the PC machine. It is based on a main PC computer, which is connected to the high speed machining robot main processor so that control and communication can be realized. The system collects the variables of the cutting process by means of sensors which are optimized with the genetic algorithms. Research limitations/implications: 3D sculptured milling covers a wide range of operations. In 3D metal cutting processes, cutting conditions have an influence on reducing the production cost and time and deciding the quality of a final product. Practical implications: Simulated results show that the proposed intelligent machining system is effective and efficient, and can be integrated into a real-time intelligent manufacturing system for solving complex machining optimization problems. Originality/value: The paper describes about intelligent machining system which can applied in intelligent manufacturing process.

4

Adaptive controller design for feedrate maximization of machining process

Cus F., Zuperl U., Kiker E., Milfelner M.

Journal of Achievements in Materials and Manufacturing Engineering

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2006

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Vol. 17, nr 1-2

237--240

EN

Purpose: An adaptive control system is built which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters. Design/methodology/approach: The paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization) in modeling and adaptively controlling the process of end milling. An overall approach of hybrid modeling of cutting process (ANfis-system), used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS) consisting of two neural identificators of the process dynamics and primary regulator. Findings: The experimental results show that not only does the milling system with the design controller have high robustness, and global stability but also the machining efficiency of the milling system with the adaptive controller is much higher than for traditional CNC milling system. Experiments have confirmed efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear. Research limitations/implications: 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. Practical implications: The results of experiments demonstrate the ability of the proposed system to effectively regulate peak cutting forces for cutting conditions commonly encountered in end milling operations. The high accuracy of results within a wide range of machining parameters indicates that the system can be practically applied in industry. Originality/value: By the hybrid process modeling and feed-forward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of cutting parameters is built.

5

Tool wear prediction in machinning by using the adaptive neuro-fuzzy system

Zuperl U., Milfelner M., Cus F.

International Journal of Applied Mechanics and Engineering

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2004

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Vol. 9, no spec.

73-78

EN

The focus of this paper is to develop a reliable method to predict flank wear during end milling process. A neural-fuzzy scheme is applied to perform the prediction of flank wear from cutting force signals. In this contribution we also discussed the construction of a ANFIS system that seeks to provide a linguistic model for the estimation of tool wear from the knowledge embedded in the neural network. Machining experiments conducted using the proposed method indicate that using an appropriate force signals, the flank wear can be predicted within 4% of the actual wear for various end-milling conditions.