Cyber-Physical Systems (CPS) simulation provides a unified paradigm for equipment verification. While Modelica excels in multi-physics modeling (e.g., mechanical, electrical, and thermal systems), it lacks native support for signals, communications, control, imaging, data processing, and AI.
To overcome these limitations, MWORKS delivers:
Enhanced Modelica Support – After a decade of R&D and five years of refactoring, MWORKS offers improved Modelica compilation and solver capabilities.
Extended Block-Diagram Modeling – Building on Modelica’s unified framework, MWORKS enables embedded code generation and bidirectional model-code traceability.
Seamless Scientific Computing Integration – By leveraging Julia, MWORKS incorporates toolboxes for signals, control, imaging, data, and AI, achieving tight integration between system modeling and scientific computing for full-spectrum CPS simulation.
MWORKS has been successfully deployed in aerospace, aviation, nuclear, shipbuilding, and automotive industries.

Modelica models exhibit excellent cross-platform compatibility (they can be compiled and simulated on any platform supporting Modelica). However, experiments have revealed that simulation results of the same Modelica model may vary across different platforms (under identical simulation algorithm configurations). The root cause of such discrepancies lies in modeling uncertainties introduced by improper modeling practices, such as insufficient initial constraints or ambiguous state variables selection. Different Modelica platforms employ unique translation strategies when handling model uncertainties. Therefore, consistent model translation must be ensured to achieve aligned simulation results. Model Disambiguation can be done in two ways: by improvements in language, such as propose relevant annotations; by improvements in vendor tools. This paper presents a model disambiguation technology in MWORKS.Sysplorer that enables modelers to automatically correct model text based on translation information, eliminating uncertainties and ensuring model portability across Modelica platforms.