Direct multi-objective optimization of parametric geometrical models stored in PLM systems to improve functional product design

Abstract

-This paper presents a functional analysis and design method, including an optimization loop, which has been integrated into our self-developed, web-based Product Lifecycle Management (PLM) platform. Our design methodology, which includes advanced and parametric CAD modelling and direct multiobjective optimization is described here. Functional design and knowledge-based engineering features, such as functional parameters, expert rule definitions and design experience feedback are all developed in the product design process in order to reduce costs, lead time and also to improve product quality and value. To confirm our research hypotheses, an experimental case-study is chosen: the ground-link system of a racing car design and manufacturing project, including conceptual, embodiment, detailed design and manufacturing phases.

Application of data mining in multiobjective optimization problems

“…Figure 1 describes the common arrangement of meta-modeling tools in multiobjective optimization processes. Worth mentioning that the other well-known CAD-Optimization integrations for shape optimization, e.g., [16,18,19] also follow the described arrangements.…”

“…Although, as it is concluded in previous efforts [16,[18][19][20], in the future, scalability of methods in variable dimension and objective space dimension will become more important, as the methods need to be capable of dealing with higher computation cost, noise and uncertainties.…”

“…EMO-based techniques have application where mathematical-based methods have difficulties with. EMO are also helpful in knowledge discovery related tasks in particular for mining the data samples achieved from CAE and CAD systems [18,19]. Useful mined information from the obtained EMO trade-off solutions have been discovered in many real-life engineering design problems.…”

“…In the similar cases [12,16,18,20] in order to approach the optimal shape in an aerospace engineering optimization problem, the multiobjective optimization techniques are necessary to deal with all important objectives and variables efficiently. Here the optimization challenge is to identify as many optimal designs as possible to provide a choice of better decision.…”

“…Therefore the multiobjective optimization tasks become more difficult with the increasing number of variables [12,21]. Although the resent advances in parametric CAD/CAE integrations [16,18,19] have reduced the complexity of the approach to some levels.…”