MODELING AND OPTIMIZATION OF DRILLING PROCESS

In this paper, the use of an abductive network for modeling drilling p rocesses is first described. The abductive network is composed of a nu mber of functional nodes, these nodes being self-organized to form an optimal network architecture by using a predicted squared error (PSE) criterion. Once the process parameters (drill diameter, cutting speed and feedrate) are given, the drilling performance (tool life, metal re moval rate, thrust force and torque) can be predicted by this develope d network. A simulated annealing optimization algorithm with a perform ance index is then applied to the developed network when searching for the optimal process parameters. Experimental results are provided to confirm the effectiveness of this approach. (C) 1998 Elsevier Science S.A.