Synergistic and intelligent process optimization




  • Aalto University, School of Chemical Engineering (Prof. Iiro Harjunkoski)
  • Aalto University, School of Science (Prof. Keijo Heljanko)
  • Selected companies (use cases)



Begin: 2018-01-01

End: 2019-12-31



SINGPRO will merge Big Data platforms, machine learning and data analytics methods with process planning and scheduling optimization. The goal is to create online, reactive and anticipative tools for more sustainable and efficient operation leading to an agile, self-aware and flexible decision-making loop. SINGPRO will enable the tracking of abnormal situations (anomaly detection), identifying process equipment performance degradations (predictive maintenance), anticipate process timing deviations (prediction of process behavior) and scenario simulation (AI planning). This helps to select the best production strategies in order to maintain production and energy efficiency as well as sustainability targets in rapidly changing market situations through data-driven self-adaptive scheduling models. Industrial Internet of Things (IIoT) provides the needed seamless connectivity, cloud computing infrastructure and service-based business models to realize this vision.

PostDoc N.N.1

PostDoc N.N.2

PostDoc School of Science




             This info last modified 2018-03-19 by Jukka Kortela