The present work is shown to bring two different domains which are manufacturing and design into picture and to make them co-exist with one another. The increase in customer diversity and variety in demand has led to the proliferation of product variety to the point of mass customization and personalization which also changed the product design constantly. These rapid changes are handled with the help of matrices Design Structure Matrix (DSM) and Incidence Matrix (IM) which help to understand how the machines and parts and components of parts interact with each other. The DSM shows how the component of parts and arranged in a module and the IM shows how the parts and machines interact with each other in a cell. The modules and cells help to make the overall process easier by giving a clear representation of their positions and activities. These two modules and cells, when combined makes for a much more efficient understanding of the overall entire process that goes into making a final product. In literature, there are ways and methods on how the DSM and IM can be clustered to get the best arrangement of the parts and their corresponding machines as well as the components of the parts. However, the current paper aims to combine the two domains together. This is done with the help of Genetic Algorithm (GA). Genetic Algorithm makes use of natural selection to get the best output which helps to bring the two matrices together so that both of them are clustered at the same time to get the final result. The objective is to develop a new model which can cluster both IM and DSM at the same time. A product module can be manufactured and assembled in a single machine cell. This will make it easier to change, upgrade and manufacture a product, by only modifying specific modules and their corresponding machine cells, without disturbing either the whole product design or the whole manufacturing system.