Digital Twin-Driven Analysis of Design Constraints

Abstract

Design constraints play a critical role in product development. Management of constraints significantly affect achievements of functions. Conventionally, constraints analysis is driven by designers’ knowledge, cognition and experience. Besides, constraints analysis is an iterative work with high cost, time and efforts. As an emerging technology, digital twin enhances the information processing with its synchronization, high-quality model and real-time data exchange. Therefore, digital twin is expected to enhance the conventional constraints analysis. This report is written to envision the digital-twin driven analysis of design constraints. The envision will focus on constraints identification, boundaries detection and importance analytics. A case study of robot vacuum cleaner is used as an illustrative example. It is concluded that DT improves the overall reliability of constraints analysis while reducing human efforts into iterative work.