Trends like electrification, digitalization and the Internet of Things force companies to rethink their products and expand their resources to new technological areas. However, focus and deep expertise are required to create reliable, safe and durable products out of complex technologies like lithium-ion batteries. In 2016, during our PhD Theses at the Technical University of Munich, we have realized that companies take enormous risks in accepting the high uncertainties of new technological aspects such as, for example, battery lifetime. Our research points out that model-based digital twins within a centralized platform provide manufacturers with valuable technological knowledge and analytical skills in order to keep up with the described trends. There is no such company in the market until now. We have also seen the need for a different kind of company, which merges conventional physical-world engineering with information technology, data science and machine learning. That is why we have started the project CIPLAB.


CIPLAB brings the concept of digital twins from asset maintenance to model-based digital twins of products and their sub-systems by starting from the niche application of batteries. By aggregating already existing sensor data in the field to form digital product twins and data-driven models, we not only close the loop between product development and feedback from product usage but also enable new market opportunities like predictive maintenance and product reuse.

With digital battery twins, CIPLAB enables system analytics, aging prediction and longer lifetime with one click.


We see the service created for manufacturers by digital product twins as one of the most valuable applications within vast mega trends like digitalization and the Internet of Things. Our vision is to use the capabilities of digitalization and IoT to provide services based on deep domain-specific expert knowledge with one click. We therefore imagine digital twins to be the next disruptive technology for physical products.