Concurrent optimization of manufacturing cycle cost by genetic algorithms

A systematic multi-phase procedure is developed concurrently to optimize the design and manufacturing parameters using the genetic algorithm (GA) method. The simultaneous consideration of both design and manufacturing decision variables overcomes the conflicting relationship between these variables and ensures global optimal design solution. A multi-variable optimization problem for the optimum design of a robot arm is formulated and solved using the GA method to demonstrate the proposed procedure. The objective is to optimize (minimize) the total manufacturing cost under dimensional, weight, and machine power constraints using GA. Finite element analysis was adopted for the structural part of the analysis.