Content area
ABSTRACT
The value of a product relies greatly on the significance of the innovations when a product is designed and manufactured. Whereas numerous computer aided design (CAD) tools, such as computer aided engineering (CAE) and artificial intelligence (AI) tools, are widely used to create and accelerate the innovations in engineering design, commercially available AI tools sacrifice the efficiency for generality in virtual design. Because the behaviours of a physical model must be interpreted as governing mathematical models, this may ignore key analytical correspondence of inputs and outputs in the physical model. Design optimisation is simulation based with a limited exploration of a design space. We argue that for innovations such as routine designs or parametric designs that are rooted in knowledge‐based engineering (KBE), a sophisticated tool, rather than a general‐purpose CAE tool, should be developed to optimise a design solution analytically. To illustrate the feasibility and effectiveness of the proposed idea, a parametric FEA model was developed for a client company in construction. The model is programed and implemented, its conciseness, efficiency and accuracy was proven by comparative studies with SolidWorks simulation. It was recommended and used by the client company for practical use.
Details
Aircraft;
Comparative studies;
Simulation;
Design engineering;
Digital twins;
Computer aided design--CAD;
Productivity;
Artificial intelligence;
Customization;
Design optimization;
Structural members;
Computer aided engineering--CAE;
Innovations;
Product development;
Efficiency;
Composite materials;
Case studies
1 School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China
2 Department of Civil and Mechanical Engineering, Purdue University Fort Wayne, Fort Wayne, Indiana, USA