Solving the assembly configuration problem for modular products using an immune algorithm approach

Designing for modularity enhances the agility of a manufacturing system. It allows manufacturing systems to be built under high product customization requirements and at the same time keeping product development time low. Modular products imply in themselves a complex multiproduct assembly line design challenge. The design of such assembly systems comprises some of the most challenging computations in engineering and mathematics. More often than not, the optimal solution to the problem could not be found. This paper describes an approach based on the principles of natural immune systems for solving the design of assembly system for modular products. This approach, which was based on immune algorithm, was illustrated using an assembly combinatorial problem and the results obtained were compared with those derived by an established heuristic algorithm, the genetic algorithm. The results show that the immune algorithm outperforms the genetic algorithm in terms of convergence trends, distribution of near-optimal solutions and quality of solutions.