Assembly path planning (APP) is a critical step in verifying the assembly feasibility of precision products. However, due to the loss of upstream knowledge, parts in mainstream APP technologies lack the cognitive ability of proactively playing as the agents of designers in computer-aided design (CAD) systems, thus leading to the heavy cognitive burdens of designers in APP and the great gap between APP and its upstream activities. A cognitive behavior based autonomous and integrated APP method for precision products is proposed in this paper, aiming at endowing parts with cognitive capabilities and integrating APP with its upstream stage of assembly modeling. In the method, the previously developed concept of interaction feature pair is extended as a comprehensive carrier to describe and capture upstream knowledge into parts, and to model cognitive behaviors of parts, thus enabling these parts to autonomously perceive APP environment, deform according to tolerances, plan collision-free paths, and establish assembly constraints that are traditionally processed at assembly modeling stage. On this basis, key implementation algorithms for the cognitive behavior models are developed. Case studies on a simplified smartphone and a jet engine validate the feasibility of the autonomous and integrated CAD APP approach. Results indicate that, the time and manual operations used for the two cases are reduced by at least 24% and 93%, respectively; and the effects of tolerance on precision assembly can be intuitively and quantitatively evaluated. The study may potentially provide reference to more intelligent APP technologies for precision products in the future.
Jiang et al. (Fri,) studied this question.