Towards Automated Welding in Big Shipbuilding Assisted by Programed Robotic Arm Using a Measuring Arm
This paper presents an automated robotic welding system adapted for shipbuilding in large shipyards. This solution has been devised in the shipyard of Navantia located in the south of Spain, in the context of ROBOT FASE II R&D project. It also presents the human teams that have developed this welding system. The article explains the 3 parts that make up the welding system. The location of the robotic welding arm of the Fanuc brand is detailed in the first part. In addition, the gantry and spatial coordinate axes are described and indicated where the robotic arm is housed. The second part contains the system capture of the coordinates in the space for the reading of the singular points to be soldered. These points are measured by a portable measuring arm. The last part is composed of the system of communication between the different parts throughout the computer. The computer is responsible for synchronizing the measuring arm and the robotic welding arm by translating the points to be soldered.
Development of multi welding robot system for sub assembly in shipbuilding
Abstract In an effort to increase a productivity of welding process and to reduce the impact to workers from industrial disaster, the research in the field of welding automation is sharply increasing in shipbuilding industry. DSME had developed and successfully applied a welding robot system for grand assembly line in OKPO shipyard in 1997 and has recently developed multi welding robot system for the sub assembly line. This study describes the essential parts of welding automation for the sub assembly process of a hull when using industrial robots. Study includes description of auto detection process of work-pieces, off line program (OLP), host control program and high speed welding method.
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.