Abstract
The energy efficiency of manufacturing systems represents a topic of huge interest for the management of innovative production plants. In this paper, a production cell based on three operating machines has been taken into account. In particular, each machine has an independent lubrication system whose lubricant is cooled by a centralized cooling system, while the lubrication fluid temperatures must be maintained inside known upper and lower bounds, and the controller of the centralized cooling system has to minimize the cooling power. In order to control the lubrication and cooling processes, a Model Predictive Controller (MPC) has been designed, synthetized, implemented and simulated.
The main advantage of the proposed algorithm consists in the possibility to directly consider the temperature limits together with the maximum bound of the cooling power directly into the optimization problem. This means that the control action is computed using the a-priori knowledge of these bounds, resulting in better temperature profiles then those obtained with standard controllers, e.g. with saturated Proportional, Integral, Derivative (PID) ones.
Chapter PDF
Similar content being viewed by others
Keywords
References
European Commission: ICT and energy efficiency - the case for manufacturing, Recommendations of the Consultation Group, European Commission (February 2009) ISBN: 978-92-79-11306-2
Organization for Economic Cooperation and Development (OECED),OECD Key Environmental Indicators (2004), www.oecd.org/dataoecd/32/20/31558547.pdf
Fysikopoulos, A., Pastras, G., Alexopoulos, T., Chryssolouris, G.: On a generalized approach to manufacturing energy efficiency. The International Journal of Advanced Manufacturing Technology (May 2014)
Eberspächer, P., Verla, A.: Realizing energy reduction of machine tools through a control integrated consumption graph-based optimization method. In: 46th CIRP Conference on Manufacturing Systems. Procedia CIRP, vol. 7, pp. 640–645 (2013)
Calvanese, M.L., Albertelli, P., Matta, A., Taisch, M.: Analysis of energy consumption in CNC machining centers and determination of optimal cutting conditions. In: Proceedings of the 20th CIRP LCE (2013)
Frigerio, N., Matta, A.: Machine Control Policies for Energy Saving in Manufacturing. In: 2013 IEEE International Conference on Automation Science and Engineering (CASE), Madison, WI, August 17-20, pp. 651–656 (2013)
Cataldo, A., Taisch, M., Stahl, B.: Modeling, simulation and evaluation of Energy consumption for a manufacturing production line. In: 39th Annual Conference of IEEE on Industrial Electronics Society, IECON 2013, Vienna, Austria, November 10-13 (2013)
Camacho, E., Bordons, C.: Model Predictive Control. Springer (2007)
Bauer, M., Craig, I.K.: Economic assessment of advanced process control – a survey and framework. J. of Process Control 18, 2–18 (2008)
Bendtsen, J., Trangbaek, K., Stoustrup, J.: Hierarchical Model Predictive Control for Resource Distribution. In: 49th IEEE Conf. on Decision and Control, Hilton Atlanta Hotel, Atlanta, GA, USA (2010)
Negenborn, R.R., Beccuti, A.G., Demiray, T., Leirens, S., Damm, G., De Schutter, B., Morari, M.: Supervisory hybrid model predictive control for voltage stability of power networks. In: American Control Conference, ACC 2007, New York City, USA, July 9-13, pp. 5444–5449 (2007)
Torrisi, F.D., Bemporad, A.: HYSDEL—A Tool for Generating Computational Hybrid Models for Analysis and Synthesis Problems. IEEE Transactions on Control Systems Technology 12(2) (March 2004)
Bemporad, A., Morari, M.: Control of systems integrating logic, dynamics, and constraints. Automatica 35, 407–427 (1999)
MATLAB, MathWorks, http://www.mathworks.com
Bemporad, A., Borrelli, F., Morari, M.: Piecewise linear optimal controllers for hybrid systems. In: Proc. American Control Conference, pp. 1190–1194 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 IFIP International Federation for Information Processing
About this paper
Cite this paper
Cataldo, A., Perizzato, A., Scattolini, R. (2014). Management of a Production Cell Lubrication System with Model Predictive Control. In: Grabot, B., Vallespir, B., Gomes, S., Bouras, A., Kiritsis, D. (eds) Advances in Production Management Systems. Innovative and Knowledge-Based Production Management in a Global-Local World. APMS 2014. IFIP Advances in Information and Communication Technology, vol 440. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44733-8_17
Download citation
DOI: https://doi.org/10.1007/978-3-662-44733-8_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-44732-1
Online ISBN: 978-3-662-44733-8
eBook Packages: Computer ScienceComputer Science (R0)