An assembly sequence generation of a product family for robot programming

Abstract

In this paper, we present an efficient assembly sequence generation method for robot programming, which can reduce the complexity of assembly sequence generation for products within a product family. Today, principle markets for robot assembly automation (e.g., automobile and consumer electronics) have a relatively short product run rate, ranging from six to twelve months. To accommodate this rapidly changing production demand, in most cases, manufacturers design a series of new products within a product family (i.e., a group of products derived from a common product platform) so that they have similar assembly sequences. Seemingly robot programming for a new product within a product family does not require extensive programming adjustments, but it is still complex and manufacturers spend large amount time and money in programming robots for each new product. To solve this problem, we present a new assembly sequence generation method. With a case-based planner, we generate feasible and similar-to-real assembly sequence candidates for a new product from assembly sequences of old products within a product family. Then, we use geometric information extracted from its CAD model to evaluate those candidate sequences. Unlike those used by previous studies, our method can generate an assembly sequence that is more suitable for the concept of a reconfigurable assembly system for general-purpose robots (assembly sequence generation for robot programming); more similar to assembly sequences used in real assembly systems (case-based planning); and more properly evaluated for robot assembly (a CAD model). We apply the proposed method to a toy airplane assembly scenario and demonstrate its feasibility.