The development of products with a modular structure, where the constituent modules could be derived from a set of common platforms to suit different market niches, provides unique engineering and economic advantages. However, the quantitative design of such modular product platforms could become significantly challenging for complex products. The Comprehensive Product Platform Planning (CP3) method facilitates effective design of such product platforms. The original CP3 method is however typically suitable for scale-based product family design. In this paper, we perform important modifications to the commonality matrix and the commonality constraint formulation in CP3 to advance its applicability to modular product family design. A commonality index (CI), defined in terms of the number of unique modules in a family, is used to quantify the commonality objective. The new CP3 method is applied to design a family of reconfigurable Unmanned Aerial Vehicles (UAVs) for civilian applications. CP3 enables the design of an optimum set of distinct modules, different groups of which could be assembled to configure twin-boom UAVs that provide three different combinations of payload capacity and endurance. The six key modules that participate in the platform planning are: (i) the fuselage/pod, (ii) the wing, (iii) the booms, (iv) the vertical tails, (v) the horizontal tail, and (vi) the fuel tank. The performance of each UAV is defined in terms of its range per unit fuel consumption. Among the best tradeoff UAV families obtained by mixed-discrete Particle Swarm Optimization, the family with the maximum commonality (CI = 0.5) required a 66% compromise of the UAVs’ range/fuel-consumption performance. The platform configuration corresponding to the maximum-commonality UAV family involved sharing of the horizontal tail and fuel tank among all three UAVs and sharing of the fuselage and booms among two UAVs.
An Investigation of the Impact of Assembly Sequencing on the Product Family Design Outcomes
