Borealis selected Aspen Mtell for predictive service

Aspen Technology, the software developer for optimization of production assets, in May, 2018 announced that Borealis company, the supplier of the innovative solutions in the field of polyolefins, basic chemicals and fertilizers, selected the software of Aspen Mtell, performing the first deployment of software for production of polyethylene at the plant in Stenunsunda in Sweden.

Software of Aspen Mtell is a part of the software package aspenONE Asset Performance Management (APM) combining knowledge of production processes with the solutions Big Data and machine learning for increase in efficiency in the field of engineering design, operation and service of industrial assets for all their lifecycle. Aspen Mtell collects data as on the history of production operations and maintenance, and on transactions and maintenance in process in real time precisely to detect signs of failures which precede possible breakdowns and degradation of industrial assets and also to predict future failures and to order detailed recommendations to actions for mitigation or the solution of these problems.

The choice of this software was based on its work within the forecast of service for the principle of "justification of the concept" for the crucial compressor. Predictive service is a key initiative for "Borealis", and this original project effectively showed notable benefit from automation of such data analysis and work with information. The decision on promotion forward with "Aspen Mtell" was supported also because of the shown fast speed of deployment, exact early identification of degradation of assets and a scaling option of the solution on all system.

Thanks to management of industrial assets and also collection of data on the history of production operations and on transactions in real time along with the checked advanced technologies - the organizations can transform process of maintenance of assets, providing optimal reliability, prolonging service life of assets and increasing profitability of the enterprises.