Toward an XR-Based Scalable Modular Design Framework for Smart Electric Commercial Vehicle Customization

Traditional manufacturing is shifting toward smart Product-Service Systems (SPSS), with smart electric commercial vehicle (SECV) customization emerging as a representative challenge. Traditional design methods often suffer from high prototyping costs and limited user engagement. To address these gaps, this study develops an XR-based scalable modular framework that integrates Digital Twins (DT) and modularity principles to enable dynamic product-service configuration. Unlike conventional approaches, the proposed framework employs a "Scenario-Product-Space" adaptive logic to facilitate intuitive evaluation of interior layouts. A key refinement in this version is the integration of embodied virtual humans, which allows for the simulation of complex service workflows and human-vehicle interactions. Experimental results demonstrate that the framework significantly enhances design efficiency and decision-making transparency compared to fixed-configuration methods. The study validates the framework’s scalability across diverse service scenarios and provides a methodological foundation for user-centered SPSS customization.