Adjusting input processing parameters of the FDM to maximize the tensile strengthof ۳D printed parts using the combination of the Taguchi method and TeachingLearning-Based Optimization (TLBO) algorithm

سال انتشار: 1401
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 206

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ICIORS15_005

تاریخ نمایه سازی: 23 بهمن 1401

چکیده مقاله:

The popularity of FDM ۳D printing has made many effortsto optimize the properties of the manufactured parts. One ofthe most important features is tensile strength.In this research, the experiments were designed for ۸ inputparameters, with ۳ levels for each, using Taguchi L۲۷. ۲series of samples are made from PLA, according to thesuggested settings. Signal-to-noise ratio is calculated andfull quadratic regression model is built. The use of TLBO,which is a population-based metaheuristic optimizationmethod, overcomes the main weakness of the mostmetaheuristic algorithms, which is a high dependency onthe initial settings. Also, the creative use of the Roundfunction provides the possibility of simultaneous use ofcontinuous and discrete variables in the input. The outputof the optimization process shows a good agreement withthe signal-to-noise ratio diagram. Also, the average tensilestrength of the verification samples has less than ۲%relative error in comparison with the prediction of theoptimization process, which confirms the effectiveness ofthe proposed algorithm.

نویسندگان

Hamid Haghshenas Gorgani

Engineering Skills Education Center, Sharif University of technology, Tehran, Iran

Mohammad Ali Zonoobi

Tehran International Campus, Sharif University of technology, Tehran, Iran

Dorin Javaherneshan

Aalto University, Espoo, Finland