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The DSM algorithms are used for reordering the matrix elements subject to some criteria. Static DSMs are usually analyzed with [[Cluster analysis|clustering algorithms]] (i.e., reordering the matrix elements in order to group together related elements). Clustering results would typically show groups (clusters) of tightly related elements, and elements that are either not connected or are connected to many other elements and therefore are not part of a group.<ref name="complex"/>
Time-based DSMs are typically analyzed using partitioning, tearing and sequencing algorithms.<ref name="complex"/><ref>A. Karniel and Y. Reich, "Design process planning using DSM", Managing the Dynamics of New Product Development Processes: A New Product Lifecycle Management Paradigm, Springer, 2011 [http://link.springer.com/chapter/10.1007%2F978-0-85729-570-5_3]</ref
'''Partitioning''' methods try to order the matrix elements such that no feedback marks remain.<ref name="complex"/> In case of coupled activities (activities that have cyclic links, e.g., activity A is linked to B, which is linked to C, which is linked to A) the results is a block diagonal DSM (i.e., blocks or groups of coupled activities along the diagonal). Partitioning methods include: Path Searching; Reachability Matrix; Triangulation algorithm; and the powers of the Adjacency Matrix.
'''Tearing''' is the removal of feedback marks (in Binary DSM) or assignment of lower priority (numeric DSM). Tearing of a Component-based DSM may imply modularization (the component design is not influencing other components) or standardization (the component design is not influencing and not influenced by other components).<ref name="complex"/><ref>Sered Y, Reich Y (2006)," Standardization and modularization driven by minimizing overall process effort." Computer-Aided Design, 38(5):405-416</ref> After tearing a partitioning algorithm is (re)applied.
Minimizing feedback loops gets the best results for Binary DSM, but not always for Numeric DSM or Probability DSM. '''Sequencing''' algorithms (using optimization, genetic algorithms) are typically trying to minimize the number of feedback loops and also to reorder coupled activities (having cyclic loop) trying to have the feedback marks close to the diagonal. Yet, sometimes the algorithm just tries to minimize a criterion (where minimum iterations is not the optimal results).
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The use of DSM has been extended to visualize and optimize the otherwise invisible information flow and interactions associated with office work. This visualization via DSM allows the Lean Body of Knowledge to be applied to office and information intensive flows.<ref>{{cite book|title=Far From the Factory: Lean for the Information Age|year=2010|publisher=Productivity Press|___location=New York|isbn=1420094564|pages=159–180}}</ref>
The DSM method was applied as a framework for analyzing the propagation of rework in product development processes, and the related problem of convergence (or divergence) using the theory of linear dynamical systems.<ref name="complex"/><ref>Smith R, Eppinger S (1997) “Identifying controlling features of engineering design iteration.” Management Science 43(3):276–293. </ref><ref> Yassine A, Joglekar N, Braha D, Eppinger S, and Whitney D (2003),"Complex Concurrent Engineering and the Design Structure Matrix Approach." Research in Engineering Design, 14 (3): 131-144.</ref
==References==
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