Abstract
This chapter describes the basic concepts involved in advanced CNC systems for new machining processes. It begins with a description of some of the classic ideas about numerical control. Particular attention is paid to problems in state-of-the-art numerical control at the machine level, such as trajectory generation and servo control systems. There is a description of new concepts in advanced CNC systems involving multi-level hierarchical control architectures, which include not only the machine level, but also include a process level and a supervisory level. This is followed by a description of the sensory system for machining processes, which is essential for implementing the concept of the “ideal machining unit”. The chapter then goes on to offer an introduction to openarchitecture CNC systems. It describes communications in industrial environments and an architecture for networked control and supervision via the Internet. Finally, there is a brief summary of the systems available to assist in programming and the architectures of current CNC systems. There is also a description of the most recent developments in manual programming for current CNC systems and possible architectures for these systems, with the different uses of PCs and their various operating systems.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Al-Habaibeh A, Gindy N (2000) A new approach for systematic design of condition monitor ing systems for milling processes. J of Mater Process Technol, 107:243–251
Azpeitia JL et al. (2006) Desarrollo de nuevas estrategias de control basadas en observadores de estado para la mejora de la precisión y la dinámica en MH (in Spanish, New control strategies bases on state-observers for improving precision and machine dynamics). XIV Congreso de Máquinas Herramienta y Tecnologías de Fabricación: 457–476
Boissier R et al. (2001) Enhancing numerical controllers using MMS concepts and a CORBA-based software bus. Int J Comput Integr Manuf, 14(6):560–569
Fagor Automation Scoop (2007) CNC 8070 Programming Manual. Fagor
Deleure C, Lannoo M (2004) Nanostructures. Theory and Modeling. NanoScience and Technology series. Springer Verlag
Felser M (2005) Real-time ethernet – Industry prospective. Proceedings of the IEEE, 93:1118–1129
Feng CX, Wang XF (2003) Surface roughness predictive modeling:neural networks versus regression. IIE Transactions, 35:11–27
Goser K et al. (2004) Nanoelectronics and Nanosystems. Springer Verlag
Haber R, Alique A (2003) Intelligent process supervision for predicting tool wear in machining processes. Journal of Mechatronics, Special Issue on Computational Intelligence in Mechatronics Systems, 13(8–9):825–849
Haber R, Alique JR (2007) Fuzzy logic-based torque control system for milling process optimization. IEEE Trans on Systems, Man and Cybernetics, 37 (5):941–950
Haber R et al. (1998) Toward intelligent machining: hierarchical fuzzy control for the end milling process. IEEE Trans Contr Sys Technol, 6 (2):188–199
Haber R et al. (2007) A classic solution for the control of a high-performance drilling process. Intern J of Mach Tool Manufact, 47:2290–2297
HEIDENHAIN (2007) Uniformly Digital. Technical Information. 6+10 Edition. Klartext.
Ji K, Kim WJ (2005) Real-Time Control of Networked Control Systems via Ethernet. Int J Contr, Automat Syst, 3 (4):591–600
Koren Y (1980) Cross coupled biaxial computer control for manufacturing systems. J of Dynam Syst Measure Contr, Trans of the ASME 102:265–272
Koren Y, Bollinger JG (1978) Design parameters for sampled data drives for CNC machine tools. IEEE Trans on Ind Applications IA, 14(3):380–390
Landers RG et al. (2004) A comparison of model-based machining force control approaches. Intern J of Mach Tool Manufact, 44:733–748
Lee KC, Lee S (2002). Performance evaluation of switched Ethernet for real-time industrial communications. Computer Standards & Interfaces, 24:411–423
Lian FL et al. (2001) Performance Evaluation of Control Networks: Ethernet, ControleNet, and DeviceNet. IEEE Control Systems Magazine, 21(1):66–83
Liang SY et al. (2004) Machining process monitoring and control: The state of the art. J of Manufact Sci Engineer, Trans of the ASME, 126:297–310
Martin D et al. (2008) Design and implementation of a networked monitoring platform based on CORBA middleware for industrial processes. Future Generation Computer Systems, in review
Moreno A et al. (2006) SIMUMEK: Un sistema de simulación grafica 3D para operaciones de mecanizado CNC (in Spanish, System for the graphic simulation of 3D machining operations). XIV Congreso de Máquinas Herramienta y Tecnologías de Fabricación, 391–403
Neumann P (2004) Communication in Industrial Automation – What Is Going On? Proceedings of INCOM’04 Salvador Brazil: 1332–1347
Norman et al. (2006) A sophisticated platform for characterization, monitoring and control of machining. Meas Sci Technol, 17:847–854
Park J et al. (1995) An open architecture real time controller for machining processes. Proc CRIP, May
Poo AN, Bollinger JG (1974) Digital analog servosystem design for CNC. IEEE Ind Appli Society, 9th Annual Meeting
Poo AN et al. (1972) Dynamic errors in type 1 contouring systems. IEEE Trans on Ind Applications IA-8(4):477–484
Pristschow G et al. (2001) Open controller architecture – Past, present and future. Annals of CIRP, 50(2):463–470
Renton D, Elbestawi MA (2000) High speed servo control of multi-axis machine tools. Inter J of Mach Tool Manufact, 40:539:559
Sanz R (2003) A CORBA-based architecture for strategic process control. Annual Reviews in Control 27:15–22
SERCOS Interface Controller (2000) Reference Manual 10/2000
Solis E et al. (2004) A new analytical–experimental method for the identification of stability lobes in high speed milling. Inter J of Mach Tool Manufact, 44:1591–1597
Song Q, Kasabov N (2006) TWNFI – a transductive neuro-fuzzy inference system with weighted data normalization for personalized modelling. Neur Netw, 19:1591–1596
Tanenbaum AS (2001) Computer Networks. 3rd ed. Prentice Hall, Upple Saddle River NJ
Tikhon M et al. (2004) NURBS interpolator for constant material removal rate in open NC machine tools. Inter J of Mach Tool Manufact, 44:237–241
Tomizuka M (1987) Zero phase error tracking algorithm for digital control. J of Dynamic Systems, Measurement and Control, Trans of the ASME, 109:65–68
Torfs D et al. (1992) Extended bandwidth zero phase error tracking control of nonminimal phase systems. J of Dynamic Systems, Measurement and Control, Trans of the ASME, 114:347–351
Tsai YH et al. (1999) An in process surface recognition system based on neural networks in end milling cutting operations. Inter J of Mach Tool Manufact, 39: 583–605
Waser R (2003) Nanoelectronics and Information Technology. Ed. Wiley-VCH
Wecks M, Ye G (1990) Sharp corner tracking using the IKF control strategy. Annals of the CIRP, 39(1):437–441
Yang TC (2006) Networked Control System: A Brief Survey, Control Theory and Applications. IEE Proceedings, 153(4):403–412
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer London
About this chapter
Cite this chapter
Alique, J., Haber, R. (2009). Advanced Controls for New Machining Processes. In: López de Lacalle, L., Lamikiz, A. (eds) Machine Tools for High Performance Machining. Springer, London. https://doi.org/10.1007/978-1-84800-380-4_5
Download citation
DOI: https://doi.org/10.1007/978-1-84800-380-4_5
Publisher Name: Springer, London
Print ISBN: 978-1-84800-379-8
Online ISBN: 978-1-84800-380-4
eBook Packages: EngineeringEngineering (R0)