Dynamic multi-objective optimisation for machining gradient materials

Roy, R.^{1, a}; Mehnen, J.^{1, b}

1)

Decision Engineering Centre, University Cranfield, Cranfield, United Kingdom

a) r.roy@cranfield.ac.uk; b) j.mehnen@cranfield.ac.uk

Kurzfassung

Efficient machining of material with continuously varying properties, so called gradient material, needs advanced planning of cutting parameters; this is a dynamic optimisation problem. Additionally the manufacturing has to satisfy several constraints in parallel. The parameters are optimised using a new predictive multi-objective optimisation approach based on Genetic Algorithms. The algorithm adapts online to the dynamically varying hardness properties of the material. A model based detailed case study is presented where the optimisation identifies good parameter sets for the machining. The solutions are finally selected based on a desirability function (DF) and heuristics.

Schlüsselwörter

Optimisation, Genetic, Computer aided manufacturing (CAM)

Veröffentlichung

CIRP Annals – Manufacturing Technology, 57 (2008) 1, S. 429-432, doi: 10.1016/j.cirp.2008.03.020