An evaluation method for the layout of industrial digital twin monitoring interfaces based on entropy weight-TOPSIS

This paper proposes a multi-criteria decision-making evaluation model that integrates the entropy weight method with the TOPSIS approach to systematically assess and optimize the interface layout of industrial digital twin monitoring systems. By constructing a structured evaluation index system, collecting expert rating data, and applying entropy weight calculation and TOPSIS ranking, the model objectively determines the optimal layout scheme. A case study involving six alternative interface layouts of an industrial smart manufacturing platform demonstrates the effectiveness of the proposed method, identifying Scheme A as the best-performing design. To validate the model's reliability, a supplementary user-based evaluation using a Likert-scale questionnaire was conducted, and the results showed high consistency with the entropy-TOPSIS outcomes. The study highlights the model’s scientific rigor, objectivity, and practical applicability for interface optimization in digital twin systems. While the current evaluation relies on subjective scoring, future research will explore the incorporation of behavioral data, such as eye-tracking, for a more comprehensive and data-driven evaluation framework.