Using a Large Language Model to generate a Design Structure Matrix

Koh, Edwin C. Y.

arXiv.org Artificial Intelligence 

DSM is known for its simplicity and conciseness in representation and exists in the form of a square matrix that maps the relationships between the set of system elements [Yassine and Braha 2003; Browning 2015]. An example DSM (= 4) is shown in Figure 1. Based on the DSM convention described by Browning [2001], Element 1 depends on Element 2 as indicated by a red cell entry in row 2 column 1 of the DSM. Likewise, Element 4 depends on Element 3 as indicated in row 3 column 4. The diagonal of the DSM maps each element to itself and is indicated as black cells in Figure 1. The diagonal is usually left empty but is sometimes used as a space to store element-specific data, such as the likelihood of changing the given element based on market projection [Koh et al. 2013]. The DSM in Figure 1 is not symmetrical across the diagonal, indicating asymmetrical dependencies between the system elements. For example, Element 1 depends on Element 2 but Element 2 does not depend on Element 1. In contrast, the example DSM shows that Element 2 and Element 4 have a symmetrical interdependency. It is important to note that a transposed version of the DSM convention is also widely adopted by many (e.g.