A well-designed layout is essential for efficient production, which significantly contributes to a manufacturing company's economic success. In the era of mass customization, production planners must adapt resources in the layout to accommodate various product variants. However, they face constraints in time and resources, limiting their ability to explore the complete solution space for an optimal configuration. Meta-heuristics like genetic algorithms and simulated annealing frequently produce suboptimal solutions and are susceptible to parameter tuning. This paper presents a novel layout optimization approach that converts the layout problem into a mass-spring-damper system, where the equilibrium state represents the ideal layout for resource arrangement. It applies this approach to a brownfield layout problem involving 20 resources, utilizing robots as the handling mechanism. It analyzes the results, assesses the performance of the method, and discusses its limitations. Finally, it outlines potential avenues for future research to address these limitations.