Browse Publications Technical Papers 2011-01-1254
2011-04-12

Innovative Robust Solutions for Lean Manufacturing in Automotive Assembly Processes 2011-01-1254

The article presents an innovative approach to the implementation of a robust design optimization solution in an automobiles assembly process. The approach of the entire project is specific to the 6 Sigma optimization process, by applying the DMAIC cycle integrated in a robust engineering approach for rendering lean the final product assembly process. According to the improvement cycle, the aspects specific for such a process are presented sequentially starting with the “Define” phase for presenting the encountered problem and continuing with the presentation of the scope of the project and its objectives. The “Improvement” cycle phase is applied by the analysis of the monitored 6 Sigma metrics (defined during the previous “Measure” phase and the cause and effect analysis, done during a brainstorming meeting developed during the “Analyze” phase). There follows a proposal for the innovative robust solution by which the assembly process is optimized. Therefore, we propose the final assembly of already painted doors on the already assembled cars with a special work-holding which is easy to handle by the human operator. The automation of designed and implemented solutions provides features of error proofing for the assembly process in the case in which the doors are not located accordingly on the work-holding locating elements, which may lead to various inconveniences during the assembly on the vehicle and/or some faults of the door quality, such as scratches or deformations because of the impacts. The initially presented process indices, for the not yet optimized process are finally evaluated after the implementation of the innovative solution for a comparative study of the initial monitoring results and after the implementation of the proposed corrective solution. This underlines the critical conclusions that are induced during the “Control” phase. The final conclusions point to the corrective / preventive actions for a sustainable and reliable optimization, which give the maximal process its overall efficiency.

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