Designing scalable product families by the radial basis function–high-dimensional model representation metamodelling technique

Abstract

Product family design is cost-efficient for achieving the best trade-off between commonalization and diversification. However, for computationally intensive design functions which are viewed as black boxes, the family design would be challenging. A two-stage platform configuration method with generalized commonality is proposed for a scale-based family with unknown platform configuration. Unconventional sensitivity analysis and information on variation in the individual variants’ optimal design are used for platform configuration design. Metamodelling is employed to provide the sensitivity and variable correlation information, leading to significant savings in function calls. A family of universal electric motors is designed for product performance and the efficiency of this method is studied. The impact of the employed parameters is also analysed. Then, the proposed method is modified for obtaining higher commonality. The proposed method is shown to yield design solutions with better objective function values, allowable performance loss and higher commonality than the previously developed methods in the literature.

Keywords:

• product family design optimization
• platform configuration
• sensitivity analysis
• scale-based family design
• black box

Acknowledgement

This work was supported by the Natural Science and Engineering Research Council (NSERC) of Canada. We would like to thank Dr Timothy W. Simpson for kindly sharing the codes for the Universal Electric Motors design problem.

Additional information

Funding

This work was supported by the Natural Science and Engineering Research Council (NSERC) of Canada.