A machining partition method for local features with dimensional correlations of large cabin

Abstract

AbstractIntegrated in-situ partition manufacturing mode of large cabins based on the mobile serial robots is adopted for machining tasks of outboard local features currently. However, the existing partition criteria of large-scale components only consider the geometric features and structure, ignoring the dimensional correlations of local features and the effective workspace of serial robots. This tends to cause that features with the same dimensional correlation are divided into different sub-regions, resulting in extra machining adjustment which reduces the machining efficiency. Aiming at the machining partition problem for local features of the large cabin, a machining partition method is proposed for local features with dimensional correlations of the large cabin based on clustering. Considering positions and dimensional correlations of local features, a multi-objective optimization model of partition based on clustering validity indexes is established to pre-solve partition schemes. To solve the reachable region of the large cabin, the effective workspace of serial robots is taken into account. With the reachable region as the constraint and the machining efficiency as the decision basis, the optimal partition scheme for local features of the large cabin is determined. The contrast validation is conducted on a reference cabin. The results indicate that the proposed method both satisfies the dimensional correlations of local features and the effective workspace of serial robots, which improves the machining efficiency. This research provides significant machining partition bases for robot machining in the integrated in-situ partition manufacturing mode of large cabins.