Michal Piasecki’s recent design – Weaving Bowl – was selected for the final of Young Design 2010 competition organized by Warsaw’s Institute of Industrial Design (IWP). During the project presentation at IWP, taking place on June 2nd this year, Michal emphasized how mass customization paradigm shifts designers and users roles. Designers’ focus moves away from a single solution towards a spectrum of possible forms, while the “users”, “customers”, “prosumers” or “co-designers” choose a single option from this spectrum.

Michal later moved on to describe the spectrum of Weaving Bowl’s forms, also often called the solution space. The product is controlled by three attributes: height, porosity and type of material. The size of the object is 20 by 20 by 4-16 cm and it is a 3d printed piece. It is designed to be manufactured using stereolithography, fused deposition modeling or selective laser sintering.

Parameter 1: height.

Parameter 2: porosity.

Parameter 3: type of material.

Different algorithms for browsing through a solution space of such product where also discussed. This part of the presentation was directly related to Michal’s PhD research, where he is looking at two distinctive approaches to the design of configurators:

- An elective approach where users define levels of each of the product attributes explicitly.

- An instructive approach – an implementation of genetic algorithms which enables users to manually select parents of next generations without a need to understand how many parameters control the product and what each of them is responsible for exactly.

These two approaches were compared in the Breeding Objects Experiment 1.

“A Redefinition of the Paradox of Choice”, a paper co-authored by Michal Piasecki and Sean Hanna, was accepted for the Design Computing Cognition conference 2010 (DCC’10).

In the paper builds upon Barry Schwart’z definition of the paradox of choice. The abstract outlines our proposition of reconsideration of the paradox and positions the Breeding Objects Experiment 1 in this context:

Abstract: Barry Schwartz defined the paradox of choice as the fact that in western developed societies a large amount of choice is commonly associated with welfare and freedom but too much choice causes the feeling of less happiness, less satisfaction and can even lead to paralysis. The paradox of choice has been recognized as one of the major sources of mass confusion in context of the B2C online mass customization. We propose to redefine the paradox of choice with an emphasis on the meaning of choice in conjunction with the amount of available options, rather than just the quantity of choice. We propose that it is the lack of meaningful choice, rather than an overwhelming amount of choice, that can cause customers’ feelings of decreased happiness, decreased satisfaction and paralysis. We further propose that since users themselves are often not able to explicitly define what constitutes a meaningful choice, the task they face belongs to the category of ill-defined problems. The challenge for mass customization practitioners is thus not to limit the scope of choice, as has been suggested in previous literature, but to provide users with choice that is relevant to them.

We further discuss two computational approaches to solving problems related to the redefined paradox of choice in the context of the B2C mass customization. The first is based on recommender systems and the second is an implementation of artificial selection in genetic algorithms. We present findings of an empirical comparison of genetic algorithm and parametric product configurators. We find that the genetic algorithm tools, which allow users to move through a solution space by recognition of meaningful options rather than their definition, appear to be more popular among the users when it comes to browsing through solution spaces with larger number of dimensions.

Breeding Objects Experiment 01 is my first experiment with configurators for mass customization of products over the Internet, conducted as part of PhD research at the Bartlett School of Graduate Studies. The experiment is a comparison of two types of configurators: “parametric” configurators and genetic algorithms configurators. In parametric configurators users have to specify the values of each of the parameters explicitly, while in genetic algorithms configurators they are not required to do so. Thanks to artificial selection, they can instead navigate through solution space by breeding objects, that is manually selecting parents of next generations.

The experiment is only about the patterns of interaction with the tools available, so you will not be asked to fill in any questionnaires. Once you start interaction with the tools, you will be able to navigate between them using links on top of each page.