Module identification plays an important role in modular design and mass customization. In order to further extend the quantitative methodology for product modularization, an approach to product granulation based on the theory of fuzzy quotient space was proposed. The traditional product modularization based on the relativity analysis was translated into the product granulation by introducing the granular computing method, and the product granulation was analyzed by the theory of fuzzy quotient space. The product granular space was established based on the normalized distance and the integrated fuzzy similarity relation, and the optimal granular layer was obtained using a two-stage optimization algorithm. Then the optimal modularization scheme was achieved. A case of the telescopic shuttle mechanism of automatic storage/retrieval machine was studied to illustrate the validity of the proposed method. This approach offers a new way of numerical analysis and evaluation for module identifying and optimizing, and the application result shows that the proposed method is feasible and rational, which can guide the product modularization process effectively.