COMPOSITIONAL MODELLING OF FLUID POWER SYSTEMS USING PREDICTIVE TRADEOFF MODELS

Authors

  • Richard J. Malak Jr. Systems Realization Laboratory, G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332
  • Lina Tucker Systems Realization Laboratory, G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332
  • Christiaan J.J. Paredis Systems Realization Laboratory, G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332

Keywords:

systems design, tradeoff modelling, parameterized Pareto frontiers

Abstract

System-level decisions can have a large impact on the success of any design project, including those in the fluid power domain. Regardless of efforts by designers to optimize individual fluid power components, poor decisions at the systems level can lead to poor system performance and unsatisfied design requirements. In this paper, the principles of system-level decision making are applied to the design of fluid power systems. Describe a methodology for modelling fluid power component technology using predictive modelling and data mining techniques in a way that facilitates system- level modelling and decision making is described. This approach is demonstrated on the design of a hydraulic log splitter.

Downloads

Download data is not yet available.

Author Biographies

Richard J. Malak Jr., Systems Realization Laboratory, G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332

Richard J. Malak Jr. Rich is an instructor at the Georgia Institute of Technology, serving at their European Campus in Metz, France. He received his Ph.D. in Mechanical Engineering at Georgia Tech. He also holds M.S. degrees in mechanical engineering from Georgia Tech and electrical and computer engineering from Carnegie Mellon University.

Lina Tucker, Systems Realization Laboratory, G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332

Lina Tucker Lina an undergraduate research assistant in the G.W. Woodruff School of Mechanical Engineering at Georgia Tech.

Christiaan J.J. Paredis, Systems Realization Laboratory, G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332

Christiaan J.J. Paredis Chris is an associate professor in the G.W. Woodruff School of Mechanical Engineering at Georgia Tech. He also is director of the Systems Realization Laboratory and associate director of the Product & Systems Lifecycle (PSLM) Center.

References

Barber, C. B., Dobkin, D. P. and Huhdanpaa, H. T.

The Quickhull Algorithm for Convex Hulls.

ACM Transactions on Mathematical Software. Vol.

, pp. 469-483.

Boehm, B. W. 1988. A Spiral Model of Software Development

and Enhancement. IEEE Computer. Vol.

, pp. 61-72.

Buede, D. M. 2000. The Engineering Design of Systems.

New York, John Wiley & Sons.

Clemen, R. T. 1996. Making Hard Decisions: An Introduction

to Decision Analysis. Pacific Grove, CA,

Duxbury Press.

Daschbach, J. M. and Apgar, H. 1988. Design Analysis

through Techniques of Parametric Cost Estimation.

Engineering Costs and Production Economics.

Vol. 14, pp. 87-93.

Dean, J. 1976. Statistical Cost Estimation. Bloomington,

IN, Indiana University Press.

Dewulf, W. 2003. A Pro-Active Approach to

Ecodesign: Framework and Tools. Ph.D. Thesis,

Katholieke Universiteit Leuven.

Eaton Corp. 1998. Pump and Motor Sizing Guide.

Eaton Heavy Duty Hydrostatic Transmissions. Eden

Prarie, MN, Eaton Corporation Hydraulics Division,

pp. 72.

Farineau, T., Rabenasolo, B., Castelain, J. M.,

Meyer, Y. and Duverlie, P. 2001. Use of Parametric

Models in an Economic Evaluation Step During

the Design Phase. International Journal of Advanced

Manufacturing Technology. Vol. 17, pp. 79-

Fishburn, P. C. 1965. Decision and Value Theory.

New York, Wiley.

Forsberg, K. and Mooz, H. 1992. The Relationship of

Systems Engineering to the Project Cycle. Engineering

Management Journal. Vol. 4, pp. 36-43.

Hand, D. J., Mannila, H. and Smyth, P. 2001. Principles

of Data Mining. Cambridge, MA, MIT Press.

Hansen, M. R., Andersen, T. O., Hansen, J. M. and

Mouritsen, O. Ø. 2005. Two-Stage Design Optimization

of Servo Driven Manipulator. 6th World

Congress of Structural and Multidisciplinary Optimization,

Rio de Janeiro.

Keeney, R. L. and Raiffa, H. 1993. Decisions with

Multiple Objectives. Cambridge, UK, Cambridge

University Press.

Kutner, M. H., Nachtsheim, C. J., Neter, J. and Li,

W. 2005. Applied Linear Statistical Models. New

York, McGraw-Hill/Irwin.

Lophaven, S. N., Nielsen, H. B. and Sondergaard, J.

DACE: A Matlab Kriging Toolbox, Technical

University of Denmark.

Malak, R. J. 2008. Using Parameterized Efficient Sets

to Model Alternatives for Systems Design Decisions.

Ph.D. Thesis, Georgia Institute of Technology.

Malak, R. J. and Paredis, C. J. J. 2007. Using Parameterized

Pareto Sets to Model Design Concepts.

ASME International Mechanical Engineering Congress

and Exposition (IMECE2007), Seattle, WA,

USA.

Malak, R. J. and Paredis, C. J. J. 2008. Modeling

Design Concepts under Risk and Uncertainty using

Parameterized Efficient Sets. SAE World Congress,

Detroit, MI.

Malak, R. J. and Paredis, C. J. J. 2009. Using Support

Vector Machines to Formalize the Valid Input

Domain of Models in Data-Driven Predictive Modeling

for Systems Design. ASME 2009 International

Design Engineering Technical Conferences and

Computers and Information in Engineering Conference

(IDETC/CIE 2009), San Diego, CA.Malak, R. J., Tucker, L. and Paredis, C. J. J. 2008.

Composing Tradeoff Models for Multi-Attribute

System-Level Decision Making. ASME 2008 International

Design Engineering Technical Conferences

and Computers and Information in Engineering

Conference (IDETC/CIE 2008), New York, NY.

Papadopoulos, E. and Davliakos, I. 2004. A Systematic

Methodology for Optimal Component Selection

of Electrohydraulic Servosystems. International

Journal of Fluid Power. Vol. 5.

Royce, W. W. 1970. Managing the Development of

Large Systems: Concepts and Techniques. 9th International

Conference on Software Engineering,

ACM.

Sage, A. P. and Armstrong Jr., J. E. 2000. Introduction

to Systems Engineering, Wiley and Sons.

Sauer-Sundstrand Co. 1997. Selection of Driveline

Components. Sauer Danfoss Applications Manual.

Ames, IA, Sauer-Sundstrand Company, pp. 32.

Witten, I. H. and Frank, E. 2005. Data Mining: Practical

Machine Learning Tools and Techniques,

Academic Press.

Downloads

Published

2009-08-01

How to Cite

Malak Jr., R. J., Tucker, L., & Paredis, C. J. (2009). COMPOSITIONAL MODELLING OF FLUID POWER SYSTEMS USING PREDICTIVE TRADEOFF MODELS. International Journal of Fluid Power, 10(2), 45–55. Retrieved from https://journals.riverpublishers.com/index.php/IJFP/article/view/499

Issue

2009: Vol 10 Iss 2

Section

Original Article