Towards automated conceptual design space exploration
Licentiate thesis, 2018
This research has been undertaken in four different research projects, addressing the challenges of the aerospace industry.
The process of exploring the design space, the set of all possible designs, can be divided into three phases: to define the design space boundaries, to populate this design space with concepts, and lastly, to analyse the different concepts to find the one which provides the highest value. A deficiency in the description of functions and constraints which constitute the design space dimensions and boundaries, rooted in the lack of methods, has been identified to reduce the available search space already in the beginning. To populate this search space, developers need to generate representations of their new designs. These representations, commonly 3D geometries in the form of CAD models, are too rigid in the form they are used today. Therefore, it is expensive to create many variants, which differ in solutions and shape. This reduces the design space population to only a few concepts, derived from the legacy design. The analysis of alternative concepts is challenged through different maturities and variety of concepts.
The coverage of multiple hierarchical search spaces, from geometry over solutions to value, has been identified as a driver for wider DSE. Furthermore, the need for a product development approach that is capable to bridge the levels of modelling abstraction. Enhanced Function-Means (EF-M) modelling, a function model applied in all studies referenced in this thesis, bridges the abstraction from a verbal description to a teleological graph, while enabling a more systematic capture of the design space boundaries. However, a subsequent gap towards geometry models could be observed in all studies. This hindered a faster design space exploration, since extensive manual labour is required to bridge these abstraction levels.
For further work, the closing of the abstraction gap in the product modelling methods is seen as the primary goal for further work, either by extending the already applied function- and geometry modelling methods, or by including other frameworks.
Knowledge Based Engineering
Model Based Design
Design Space Exploration
Chalmers, Industrial and Materials Science, Product Development
Virtual Contextual Validation of technologies and methods for Product Development
14th International Design Conference, DESIGN 2016, Cavtat, Dubrovnik, Croatia, 16-19 May 2016,; Vol. DS 84(2016)p. 669-678
Paper in proceeding
Lifecycle design and management of additive manufacturing technologies
Procedia Manufacturing,; Vol. 19(2018)p. 135-142
Function modelling and constraints replacement for additive manufacturing in satellite component design
Proceedings of NordDesign: Design in the Era of Digitalization, NordDesign 2018,; (2018)
Paper in proceeding
Müller, J. R., Isaksson, O., Landahl, J., Raja, V., Panarotto, M., Levandowski, C. E. and Raudberget, D. (2018). Enhanced function-means modelling supporting design space exploration, submitted to Artificial Intelligence for Engineering Design and Manufacturing
VITUM - Virtual Turbine Module Demonstrator
VINNOVA (2014-00911), 2014-11-03 -- 2017-06-30.
Digital experiments -methods to evaluate alternative technolgies in early phases
VINNOVA (2017-04858), 2017-11-10 -- 2020-12-31.
Digitalisering av komplett produktionsflöde - en förutsättning för additiv tillverkning (DINA)
VINNOVA (2016-01968), 2016-04-01 -- 2017-03-31.
Areas of Advance
Innovation and entrepreneurship
Thesis for the degree of licentiate of engineering / Department of Product and Production Development, Chalmers University of Technology
Virtuella utvecklingslaboratoriet (VDL), Chalmers Tvärgata 4C, M-huset
Opponent: Dr Timoleon Kipouros, University of Cambridge, England