چکیده مقاله
Tolerance design is one of the prominent tools to achieve the optimal performance of an assembly Different factors like thermal deformations would make the initially assigned tolerances ineffective Therefore, it is essential to consider the temperature variations during the tolerance design procedure This study presented an intelligent tolerance design framework using machine learning ML models First, the geometrical and dimensional tolerances influencing the performance of the assembly are identified Next, tolerance design goals and the working temperature conditions are determined In the third step, finite element modeling FEM is carried out to collect the required dataset Then, supervised ML models predicted the assembly equation In the following step, multi objective optimization is performed to explore the optimal tolerances Finally, unsupervised ML algorithms are employed to cluster the obtained optimized answers, and the classification model classifies the clustered dataset to provide various groups of tolerances according to the manufacturing costs and tolerance values, which helps to assign the optimal set of tolerances using an ML based intelligent approach A turbocharger assembly was investigated as a case study to evaluate the efficiency of the proposed approach The random forest RF algorithm estimated the assembly equation with an 80% coefficient of determination Next, the NSGA II algorithm was applied to find the optimal tolerances Subsequently, the K Means model clustered the optimal answers into five groups according to their similarity Finally, the RF algorithm was utilized to predict the class of the optimal solutions The results indicated an accuracy of 92 31% for optimal answer classification
کلیدواژهها
نویسندگان
Hossein Soroush
MSc Student, Mechanical Engineering Department, Sharif University of Technology
Saeed Khodaygan
Faculty of Mechanical Engineering Department, Sharif University of Technology
Javad HematiNik
MSc Student, Mechanical Engineering Department, Sharif University of Technology
شیوه ارجاع
Soroush, Hossein and Khodaygan, Saeed and HematiNik, Javad,1403,Intelligent tolerance design for mechanical assemblies considering thermal gradients using supervised and unsupervised machine learning,The10th International and 21th National Conference on Manufacturing Engineering,Tehran
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