Customization design method for complex product systems based on a meta-model

TLDR

The method aims to synthesize common and adaptive customer demands and product features of a product‑pedigree of complex product systems, enabling rapid, holistic individual product design by reusing design knowledge across the product family life cycle. It achieves this by constructing a four‑layered, product‑pedigree‑oriented meta‑model that abstracts product elements and by developing a specialized configuration technique for the meta‑model of complex product systems. The approach was validated by rapidly designing the product‑pedigree of a high‑speed train’s bogie, demonstrating a prototype system that constructs the meta‑model, configures it across layers, and generates variant designs for new products.

Abstract

In order to effectively reuse the design knowledge of product family life cycle development and support holistic and rapid individual product design, this article presents a new meta-model-based systemic customization design method for complex product systems within a product-pedigree. The proposed method aims to synthetically analyze the common and adaptive customer demands and product features of a product-pedigree of complex product systems and to quickly respond to the changing demands based on knowledge accumulation in the field of customization design. The key to implement such a method is (1) to construct a product-pedigree-oriented product meta-model with a four-layered architecture where it is possible to achieve a high degree of abstraction of product and (2) to develop a special technique for configuring the meta-model of the complex product systems. We have tested the proposed method with the rapid design of product-pedigree of a high-speed train’s bogies as an illustrative example. In this work, a rapid customization design prototype system has been developed and applied to the design of a high-speed train’s bogie to illustrate how to construct a product meta-model and how to conduct configuration design on different layers and variant design for generating new products.