A product family optimization approach using multidimensional data visualization

Product families have become an effective way for companies to provide the variety of products that customers desire while keeping manufacturing costs relatively low. One of the most difficult tasks in designing a product family is the decision of which components to make common and which to make variant or unique. There have been several approaches to this problem, ranging from the use of expert knowledge to the use of optimization algorithms as the basis for commonality decision-making. This paper introduces an approach utilizing multidimensional data visualization in conjunction with optimization to create a new hybrid approach for making commonality decisions. The proposed approach involves five steps: (1) problem formulation, (2) optimization of all common and all unique solutions, (3) visualization of unique optimization designs with parallel coordinates, (4) optimization based on data visualization results, and (5) plotting of design envelope to visualize final results. Multidimensional data visualization is used with "on-the-fly" visual design steering to enable designers to see and interact directly with the product family optimization process. The approach also allows designers to identify subsets of commonality through the use of parallel coordinates, rather than limit decisions to make design variables either common across all products or unique to each. The final step in the approach provides designers with a plot of several platform options where trade-offs between commonality and performance can be easily visualized. A family of three General Aviation Aircraft (GAA) is used to demonstrate this approach. Although the family is limited to three products, the approach should scale to larger product families given the multidimensional data visualization tools employed.