الفهرس | Only 14 pages are availabe for public view |
Abstract br> Metal deposition is one of the promising fields. Until now metal deposition is used for shape modelling. Materials and sizes are so limited. To get rid of these limitations welding robots were used instead of laser 3D printers, and instead of metal powders MIG welding was used. But to make this process a full production and prototyping one optimizing mechanical properties of products was required. To enhance accuracy of products width of deposited lines needed to be minimal. Also key to make mechanical properties acceptable hardness required to be close as possible to base metal one. So these were optimization targets. As MIG is one of the highly nonlinear processes NN were used to model it. 3 optimization techniques were used before developing 4th new one by optimizing ACO initial parameters values which is one of the main problems facing ACO optimization. First stage was to develop models for the MIG process. Current, voltage and travel speed are inputs and deposited line shape (width, penetration and height) and hardness of 3 levels on each line are outputs. Values of inputs were gotten from wires catalogues and suppliers applications as ranges. Second stage was optimizing the process to get optimal parameters that satisfies optimization targets. Using the experience from optimization by HS and ACO the fourth one was made and applied on the process. Results from the 4 optimization practically tested. The newly developed one showed performance very close to the HS which was the best one among the previous 3. Also ACO, HS and modified ACO testing results were close to those got from computer in contrast of those for genetic algorithm. |