Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/10941
Title: DEVELOPING EXPERT SYSTEM FOR LASER BEAM WELDING OF DISSIMILAR METAL COMBINATION
Authors: Chakravorty, Pradyumn
Keywords: MECHANICAL INDUSTRIAL ENGINEERING;DEVELOPING EXPERT SYSTEM;LASER BEAM WELDING;DISSIMILAR METAL COMBINATION
Issue Date: 2002
Abstract: Laser Beam Welding (LBW) is a proven technique of welding of difficult to weld material combinations, due to unique advantages like well define focal spot, high power density and insensitivity to magnetic material. A large number of experiments are to be conducted for optimizing laser welding parameters for a given combination of material. The data concerning weld properties and welding parameters being voluminous, makes manual search of applicable welding parameters for a desired weld cumbersome. Hence, to facilitate quick and efficient retrieval of pertinent welding parameters for a particular desired weld even by a semiskilled shop floor assistant, necessitates development of an expert system. Here an attempt has been made to design an expert system for laser welding of dissimilar materials. The incorporated welding properties data have been based on the 'simulated bead-on-plate welds (about 230) created at different welding parameters on three materials, namely, Stainless Steel 304, Permendur 49 and Kovar. The expert system takes into account the material type, thickness of both the ;sheets and method of preparation of edges (to be butted during welding). Presently the expert system is effective for thin (<2.0 mm) to thick sheets. It predicts LBW parameters of the combinations of Stainless Steel 304, Permendur 49, and Kovar. The system is expandable, for other materials also. It has been validated by creating welds using the predicted welding parameters. The mechanical properties of welds have been found satisfactory. Present work has details of the expert system and metallurgical characterization of the• welds created between above stated materials combinations at the predicted welding
URI: http://hdl.handle.net/123456789/10941
Other Identifiers: M.Tech
Research Supervisor/ Guide: Arora, Navneet
Bharti, Arvind
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (MIED)

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