Research Tools

Antares DSM

Developed as part of a university thesis by Antonio Neto, Antares DSM is a software tool to manipulate all types of DSMs. In Antares DSM is possible create, see, and execute functions to optimize the DSM projects. Documentation is only available in Portugese, unfortunately. A short version in English is available here. Antares DSM is freeware, but its development is discontinued. If you are interested to continue the work and improve the tool, it is available at Sourceforge.

Cambridge Advanced Modeller by the Engineering Design Center, University of Cambridge

Cambridge Advanced Modeller (previously known as P3) is a software tool for building and analysing models of complex systems. Its strength lies in customisability, allowing users to address specific modelling needs.
Toolboxes provide functionality to develop and analyse models using a range of standard methods. Meta-modelling and a modular architecture allow customisation.


Developed by the NASA Langley Research Center, DeMAID is a knowledge-based software tool for ordering the sequence of design processes and identifying a possible multilevel structure for a design cycle. DeMAID uses and displays the processes in a Design Structure Matrix notation.


Excel Macros for Partitioning and Simulation

A DSM Excel macro that performs partitioning, tearing, banding, and simulation. Both the original and an updated version are available including comprehensive documentation.


MATLAB Macro for Clustering DSMsby Ronnie Thebeau
This short algorithm lets you use MatLab to cluster DSMs. You do need a valid installation of MatLab to run the macro. Unformtunately, no further documentation is available.

PSM 32 by Problematics

The PSM32 program is used to implement the Dependency Structure Method (DSM). It allows for inputing and editing DSMS, displaying and manipulating DSMs, and the computational partitioning and tearing of DSMs.


Triangularization Algorithm by Andrew Kusiak et al.

Online implementation of a triangularization algorithm to obtain an optimum sequence of a DSM, which is based on the results published in A. Kusiak , N. Larson, and J. Wang, Reengineering of Design and Manufacturing Processes, Computers and Industrial Engineering, Vol. 26, No. 3, 1994, pp. 521-536.