Towards selective laser sintering of objects with customized mechanical properties based on ANFIS predictions

被引：0
作者：
Saleh A. Aldahash
Shaaban A. Salman
Abdelrasoul M. Gadelmoula
机构：
[1] Majmaah University,Department of Mechanical and Industrial Engineering, College of Engineering
[2] Abu Dhabi Polytechnic,Department of Electromechanical Engineering
[3] Assiut University,Department of Mechanical Engineering, Faculty of Engineering
来源：
Journal of Mechanical Science and Technology | 2020年 / 34卷
关键词：
Adaptive network-based fuzzy inference system (ANFIS); Cement-filled PA12; Mechanical properties; Selective laser sintering (SLS);
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Recently, the adaptive network-based fuzzy inference system (ANFIS) has been used extensively in modeling of manufacturing processes to save both optimization time and manufacturing costs. ANFIS is a powerful iterative tool for optimizing non-linear and multivariable manufacturing operations. In the present study, ANFIS is used to predict the optimum manufacturing parameters in selective laser sintering (SLS) of cement-filled polyamide 12 (PA12) composite. For this purpose, a set of cement-filled PA12 test specimens is manufactured by SLS technique with 8 different values of laser power (4.5–8 Watt) and 8 different weight fractions of white cement (5 %–40 %). Mechanical characterization of cement-filled PA12 is carried out to evaluate the ultimate tensile strength (UTS), compressive strength, and flexural properties. The experimental data are then divided into two groups; one group for training the ANFIS model and the other group for checking the validity of the identified model. The built ANFIS model was validated experimentally and comparison with experimental results revealed mean relative errors of 2.92 %, 3.84 %, 4.75 %, and 3.31 % in the predictions of UTS, compressive strength, flexural modulus, and flexural yield strength, respectively.
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页码：5075 / 5084
页数：9
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