Tradespace exploration: making well-founded decisions
The term Tradespace Exploration (TSE) originates from the defense sector. TSE provides decision makers with an understanding of capabilities, gaps and potential trade-offs in order to find a good compromise for the competing objectives.
Tradespace exploration is also an interesting approach for systems engineering in order to be able to make well-founded decisions regarding solution approach, architecture and design.
Finding compromises
Different, often conflicting interests come together in (almost) every product development. A classic example is under the name Magic triangle This is familiar from project management, but also applies to product development:
Good, cheap, fast - choose two!
Unfortunately, it is rarely that simple in practice. The increasing Product complexity also makes it increasingly difficult to understand the impact of decisions.
Concept selection analysis according to Pugh
Widely used is the Concept selection analysis according to Pugh. This tabular approach is also suitable for many everyday decisions. Evaluation criteria are collected and weighted in a table. For each relevant concept, all criteria are evaluated and entered into the table. The result is a numerical value that expresses the suitability of the concept.
This approach has its limits as complexity increases.
Tradespace Exploration
Tradespace exploration is another approach to decision-making. The approach differs from traditional approaches in three aspects in particular: Firstly, the selection of criteria has a systematic focus on benefits. Secondly, there are special tools for evaluating the results, which simplifies the handling of a large number of criteria in particular. Thirdly, this also enables the evaluation of significantly more alternatives. It is also possible to generate the alternatives automatically.
A graphical representation of the results of a tradespace exploration makes them more tangible. Akle et.al. compare in their paper Information visualization for selection in Design by Shopping different representations:
An example: Distributed Satellite Missions (NASA)
Many Space missions require the interaction of several satellites. NASA has been optimizing such systems for a long time with Tradespace Exploration. The evaluation criteria are cost and performance, which is relatively straightforward. However, there is an extremely high number of constellations. This is because an important aspect of the system is the orbit of the satellites.
NASA describes this problem vividly in this presentation. On a side note: although the topic of the presentation is the use of machine learning in the context of tradespace exploration, this does not make it any less informative.
Conclusion
As with any tool, the approach must be applied correctly. In particular, changes to the system or the requirements can render an analysis that has been carried out obsolete. It is also easy to get bogged down.
Nevertheless, Tradespace Exploration is another useful tool in the systems engineer's toolbox. From a certain level of complexity and structure of the system, it might be worth taking it out of the toolbox.
Image source: Pixabay
