Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm
MetadataShow full item record
This paper presents a new approach to the tolerance synthesis of the component parts of assemblies by simultaneously optimizing three manufacturing parameters: manufacturing cost, including tolerance cost and quality loss cost; machining time; and machine overhead/idle time cost. A methodology has been developed using the Genetic Algorithm (GA) technique to solve this multi-objective optimization problem. The effectiveness of the proposed methodology has been demonstrated by solving a wheel mounting assembly problem consisting of five components, two subassemblies, two critical dimensions, two functional tolerances, and eight operations. Significant cost saving can be achieved by employing this methodology.
The original publication is available at www.springerlink.com
NOTICE: This is the author’s version of a work in which changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication.
Showing items related by title, author, creator and subject.
Optimum tolerance synthesis of simple assemblies with nominal dimension selection using genetic algorithmKumar, D.; Ravindran, D.; Kumar, M.; Islam, Mohammad Nazrul (2015)Optimum tolerance allocation plays a vital role in minimization of the direct manufacturing cost, and it is sensitive to tolerances related to variations in manufacturing processes. However, optimal adjustment of both ...
Dong, Chensong; Zhang, C.; Liang, Z.; Wang, B. (2009)This paper presents a study on dimensional variations and tolerance analysis and synthesis for polymer matrix fiber-reinforced composite components and assemblies. A composite component dimensional variation model was ...
Li, Bin (2011)In this thesis, we consider several types of optimal control problems with constraints on the state and control variables. These problems have many engineering applications. Our aim is to develop efficient numerical methods ...