Adding Value to Your IoT Data
But a pragmatic approach can change this. By integrating off-the-shelf solutions and building upon proven technologies, even companies with limited resources can harness the power of AI and Digital Twins. The use of high-fidelity models and simplified engineering calculations can embed engineering insights into digital twins, providing a valuable resource for decision-making.
One common mistake that companies make is creating digital twin projects that are too complex too soon. Instead, a “start small and scale fast” approach can help companies embrace Digital Twin technology incrementally. Gradually expanding its applications and benefits throughout the development, production, operation, and maintenance.
In addition to practical benefits, it’s essential to remember that AI and Digital Twins can contribute to a more sustainable future. By improving resource efficiency, reducing waste, optimizing energy consumption, and enhancing predictive maintenance, companies can fulfill their social responsibility goals while achieving economic success.
As technology continues to evolve, companies that adopt a pragmatic approach to Digital Twin implementation will have a competitive edge. By starting small and scaling fast, they can achieve operational excellence, meet ESG targets, and create a sustainable future.