Applying Theory of Constraints (TOC) to digital twins: simulation and managerial outputs

Digital twins act as a digital counterpart to physical processes, enabling real-time data analysis and feedback cycles to improve system performance. As with every technological tool, there is a need for theory to serve as a base for modelling. In the case of this paper, the manufacturing process of a metal mechanic company was modelled based on the Theory of Constraints (TOC) to identify managerial actions based on objective data. In this study, TOC principles were applied within a digital twin environment, developed in AnyLogic, to model and simulate the production flow. Using real production data over a one-year timeframe, scenarios were generated and evaluated to assess productivity outcomes and bottleneck shifts. The simulations exposed the main bottleneck as well as the next possible bottlenecks (once the main one is eliminated). The findings support decision-making at multiple organizational levels, offering concrete insights into strategic investments, layout optimization, and outsourcing potential.