Axel Nordin

Complex product form generation in industrial design: A bookshelf based on Voronoi diagrams

Complex product form generation methods have rarely been used within the field of industrial design. The difficulty in their use is mainly linked to constraints – such as functionality, production and cost – that apply to most products. By coupling a mathematically described morphology to an optimisation system, it may be possible to generate a complex product form, compliant with engineering and production constraints. In this paper we apply this general approach to the designing of a bookshelf whose structure is based on Voronoi diagrams. The algorithm behind the developed application used here is based on a prior work submitted elsewhere [1], adapted to the bookshelf problem. This second example of product form generation, which includes specific constraints, confirms the relevance of the general approach.

An Approach to Constraint-Based and Mass-Customizable Product Design

In traditional product development, several iterations are usually necessary to obtain a successful compromise between constraints emanating from engineering, manufacturing, and aesthetics. Moreover, this approach to product development is not well suited for true mass-customization, as the manufacturing company remains in control of all aspects of the shape of the product-to-be. In this article, we propose an alternative approach that would (1) allow for an improved integration of industrial design into the product development process and (2) enhance the creative repertoire of industrial designers, which (3) would result in significantly improved prospects for mass-customization. The industrial design process may benefit from using advanced and aesthetically interesting morphologies emanating from the areas of mathematics and nature. Such complex morphologies can only be manipulated (analyzed and represented) by means of specific algorithms. On one hand, this requires a shift from established industrial design practice, where the industrial designer is in total control of the product form; on the other hand, it makes it fully possible to compute form so that it complies with engineering and manufacturing constraints. In this setup, the industrial designer still has control of the final result, in that she or he can choose from a set of valid forms. This approach would greatly reduce the number of iterations in the product development process between industrial design, engineering, and production. Naturally, such an approach also allows for advanced masscustomization by allowing consumers to use these tools. Within this approach, a table generation system has been developed: A system that generates tables whose support structure is based on a Voronoi diagram that fulfills structural and manufacturing constraints while being aesthetically appealing.

Study of the sequential constraint-handling technique for evolutionary optimization with application to structural problems

Engineering design problems are most frequently charac-terized by constraints that make them hard to solve and time-consuming. When evolutionary algorithms are used to solve these problems, constraints are often handled with the generic weighted sum method or with techniques specific to the prob-lem at hand. Most commonly, all constraints are evaluated at each generation, and it is also necessary to fine-tune different parameters in order to receive good results, which requires in-depth knowledge of the algorithm. The sequential constraint-handling techniques seem to be a promising alternative, be-cause they do not require all constraints to be evaluated at each iteration and they are easy to implement. They neverthe-less require the user to determine the ordering in which those constraints shall be evaluated. Therefore two heuristics that allow finding a satisfying constraint sequence have been developed. Two sequential constraint-handling techniques using the heuristics have been tested against the weighted sum technique with the ten-bar structure benchmark. They both performed better than the weighted sum technique and can therefore be easy to implement, and powerful alternatives for solving engineering design problems.

Constraint-handling techniques for generative product design systems in the mass customization context

Abstract Generative product design systems used in the context of mass customization are required to generate diverse solutions quickly and reliably without necessitating modification or tuning during use. When such systems are employed to allow for the mass customization of product form, they must be able to handle mass production and engineering constraints that can be time-consuming to evaluate and difficult to fulfill. These issues are related to how the constraints are handled in the generative design system. This article evaluates two promising sequential constraint-handling techniques and the often used weighted sum technique with regard to convergence time, convergence rate, and diversity of the design solutions. The application used for this purpose was a design system aimed at generating a table with an advanced form: a Voronoi diagram based structure. The design problem was constrained in terms of production as well as stability, requiring a time-consuming finite element evaluation. Regarding convergence time and rate, one of the sequential constraint-handling techniques performed significantly better than the weighted sum technique. Nevertheless, the weighted sum technique presented respectable results and therefore remains a relevant technique. Regarding diversity, none of the techniques could generate diverse solutions in a single search run. In contrast, the solutions from different searches were always diverse. Solution diversity is thus gained at the cost of more runs, but no evaluation of the diversity of the solutions is needed. This result is important, because a diversity evaluation function would otherwise have to be developed for every new type of design. Efficient handling of complex constraints is an important step toward mass customization of nontrivial product forms.

Teaching Design for Additive Manufacturing Through Problem-Based Learning

Additive Manufacturing (AM) is a technology that, while removing many of the constraints of traditional manufacturing, imposes some new constraints of its own. Because of this, engineers and designers need to be taught a new set of skills in design for additive manufacturing (DfAM) in order to become competent in designing parts that maximize the benefits offered by AM. Around the world, universities and organizations are beginning to offer courses in DfAM to improve the skills of modern engineers and designers. Staff at Lund University, in Sweden, have begun to offer such DfAM courses to industry that use problem-based learning (PBL) as the pedagogical approach to teaching DfAM in a more effective way. This chapter describes how these courses have been implemented, and how they have benefitted from the PBL teaching approach.

Challenges in the industrial implementation of generative design systems : An exploratory study

Abstract The aim of this paper is to investigate the challenges associated with the industrial implementation of generative design systems. Though many studies have been aimed at validating either the technical feasibility or the usefulness of generative design systems, there is, however, a lack of research on the practical implementation and adaptation in industry. To that end, this paper presents two case studies conducted while developing design systems for industrial uses. The first case study focuses on an engineering design application and the other on an industrial design application. In both cases, the focus is on detail-oriented performance-driven generative design systems based on currently available computer-assisted design tools. The development time and communications with the companies were analyzed to identify challenges in the two projects. Overall, the results show that the challenges are not related to whether the design tools are intended for artistic or technical problems, but rather in how to make the design process systematic. The challenges include aspects such as how to fully utilize the potential of generative design tools in a traditional product development process, how to enable designers not familiar with programming to provide design generation logic, and what should be automated and what is better left as a manual task. The paper suggests several strategies for dealing with the identified challenges.

Restart Strategies for Constraint-Handling in Generative Design Systems

Product alternatives suggested by a generative design system often need to be evaluated on qualitative criteria. This evaluation necessitates that several feasible solutions which fulfill all technical constraints can be proposed to the user of the system. Also, as concept development is an iterative process, it is important that these solutions are generated quickly; i.e., the system must have a low convergence time. A problem, however, is that stochastic constraint-handling techniques can have highly unpredictable convergence times, spanning several orders of magnitude, and might sometimes not converge at all. A possible solution to avoid the lengthy runs is to restart the search after a certain time, with the hope that a new starting point will lead to a lower overall convergence time, but selecting an optimal restart-time is not trivial. In this paper, two strategies are investigated for such selection, and their performance is evaluated on two constraint-handling techniques for a product design problem. The results show that both restart strategies can greatly reduce the overall convergence time. Moreover, it is shown that one of the restart strategies can be applied to a wide range of constraint-handling techniques and problems, without requiring any fine-tuning of problem-specific parameters.