An Intelligent Methodology for Assembly Tools Selection and Assembly Sequence Optimisation

In the present paper, an intelligent methodology has been used for assembly tool/gripper selection and determination of the optimal assembly sequence. Since it is well known that assembly sequence planning (ASP) is an NP-hard combinatorial optimization problem, in particular, with increase in number of components in the assembly, the computational complexity involved in searching for the optimal assembly sequence in such a large solution space also increases. Furthermore, assembly process planning, tool/gripper selection is also an important decision making task and becomes tedious and time consuming for an assembly with large number of components. Keeping the above in mind, in the present work, a knowledge based system has been developed for selection of assembly tools and grippers for performing the assembly, while a Genetic Algorithm (GA) based approach has been used to determine the feasible and optimal assembly sequences considering minimum number of tool changes and assembly direction changes.