Standing still is going backward, as they say. We at INOSIM believe that solid research is an important prerequisite for disruptive innovation that provides those key benefits to our customers that they don’t get anywhere else. Research has been part of the core identity of INOSIM for many years. As an innovative SME, we always have an eye on how we can get the most promising results transferred into industrial practice.
INOSIM is involved in collaborative research projects across a variety of technology areas where our simulation software can provide key benefits, ranging from optimal production scheduling and modular logistics over (early-stage) design of resource-efficient processes and bioprocess modeling to practical applications of artificial intelligence in the process industry. We are well-connected within the academic and industrial research and innovation landscape and are cooperating with leading academic institutions, innovative SMEs, and global industrial players, even if they sometimes lie a bit outside our typical comfort zone.
We are always interested in new opportunities to contribute our skills, software, and experience to promising research efforts. Our teams are eager to learn and expand their horizon from new research endeavors and interesting collaborators. If you are looking for an innovative SME as a partner for your research project, please contact us.
Within the KEEN innovation platform, we are building a decision support system that harnesses modern artificial intelligence methods and INOSIM digital twins to provide adaptive real-time predictions for complex batch plants.
In OptiProd.NRW, we are building the next generation of methods and software for the automatic generation of optimal production schedules, based on highly accurate digital twins by INOSIM.
In LEGOLAS, INOSIM and its partners have developed a simulation-driven planning assistance system that allows the user to quickly design modular production and logistics systems and to assess them quantitatively using INOSIM digital twins. The packaged-goods library for INOSIM that we have developed in LEGOLAS is now applied widely within other projects with logistical elements, as it enables seamless integration of production and logistics modules within a single simulation tool.
In the SkaMPi project, INOSIM and its partners have developed a new methodology that provides decision support to determine optimal modular unit operations and a maximally resource-efficient process layout for new products or new product portfolios already during the early design stages. INOSIM has developed a simulation-based tool that supports the systematic assessment and comparison of process alternatives using multi-criteria evaluation.
In EMKUS, we explored how process simulation with digital twins by INOSIM can support the steel and iron industries to provide predictive solutions for energy efficiency and demand-side management.
Within the European FP7 project TOP-REF, INOSIM and their partners from four European countries developed indicators, methodologies, and tools devoted to the improvement of resource efficiency in energy-intensive continuous industrial processes.
Within this research project, INOSIM and our partners have developed a new energy efficiency management system for processing systems that are based on proven software tools such as INOSIM simulation software and the STRUCTese tool by company Bayer.
The objective of the INOSIM Bio project was to develop a comprehensive model library and a mature simulation environment for bioprocess engineering that is based on the INOSIM simulation suite. The model library has become part of our software suites INOSIM Expert Edition and INOSIM Process Edition.
The objective of this project was to develop a new simulation environment for bioprocesses that is based on the INOSIM simulation suite.
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