Product family commonality selection through interactive visualization

High dimensionality and computational complexity are curses typically associated with many product family design problems. In this paper, we investigate interactive methods that combine two traditional technologies - optimization and visualization - to create new and powerful strategies to expedite high dimensional design space exploration and product family commonality selection. In particular, three different methods are compared and contrasted: (1) exhaustive search with visualization, (2) individual product optimization with visualization, and (3) product family optimization with visualization. Among these three, the individual product optimization with visualization methods appears to be the most suitable one for engineer designers, who do not have strong optimization background. This method allows designers to "shop" for the best designs iteratively, while gaining key insight into the tradeoff between commonality and individual performance. The study is conducted in the context of designing a UTC product using an in-house, system-level simulation tool. The challenges associated with (1) design space exploration involving mixed-type design variables and infeasibility, and those associated with (2) visualizing product family design spaces during commonality selection are addressed. Our findings indicate a positive impact on the company's current approach to product family design and commonality selection.