Material selection using knowledge-based expert system for racing bicycle forks

被引:3
|
作者
Ahmed, Syed Naseer [1 ]
Bhargava, M. [1 ]
Srinadh, K. V. Sai [1 ]
机构
[1] Natl Inst Technol, Dept Mech Engn, Warangal, India
来源
关键词
Material selection; Knowledge-based expert system; Artificial intelligence; Mass; Material index; Shape factor; Design requirements; DESIGN;
D O I
10.1016/j.iswa.2023.200257
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Materials today provide enormous prospects for innovation. However, progress is only possible if a mechanism for making a sensible choice from the materials exists. When choosing a material for a component, one should start with the full menu of materials as an option. When selecting a material for an engineering component, there is usually more than one option. However, the final choice will be a balance between the materials based on the benefits and drawbacks they provide. This paper focuses on material selection for racing bicycle forks utilizing knowledge-based expert systems based on design requirements. Knowledge-based expert systems are computer methods replicating human problem-solving through artificial intelligence to arrive at the best decisive action. A database of 67 materials with its own set of attributes was created. The material index and shape factor were evaluated for all the materials in the database based on the critical selection factors of mass and section shape. Material selection is determined by considering the material index, shape factor, and coupling various design requirements by framing simple IF-THEN rules using the python interface and Jupyter Notebook. According to this method, the final suitable materials for selecting racing bicycle forks are Aluminium alloys and Carbon Fiber Reinforced Plastics (CFRP). As the application demands lower weight by compromising on the cost, Carbon Fiber Reinforced Plastic (CFRP) is the most preferred choice for material selection of racing bicycle forks.
引用
收藏
页数:8
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