Aspen software selected for Borealis polyethylene site

The selection of this software was based on its successful performance in a competitive predictive maintenance ‘proof of concept’ project for a business-critical compressor on site. Predictive maintenance is a key initiative for Borealis, and this initial project effectively demonstrated the tangible benefit of automating such data analysis and knowledge work. The decision to move forward with Aspen Mtell was further supported by the demonstrated rapid speed of deployment, accurate early detection of asset degradation and ability to scale the solution system-wide.

Aspen Mtell is part of the aspenONE^® Asset Performance Management (APM) software suite, combining big data, machine learning and process knowledge expertise to maximise performance across the design, operations and maintenance asset lifecycle. The software mines historical and real time operational and maintenance data to discover the precise failure signatures that precede asset degradation and breakdowns, predict future failures and prescribe detailed actions to mitigate or solve problems.

Through asset performance management – enabled by a blend of historical and real time process, asset and enterprise data – organisations can transform asset maintenance into optimum reliability, extending the life of assets and maximising the return on capital employed.

Read the article online at: https://www.hydrocarbonengineering.com/petrochemicals/26042018/aspen-software-selected-for-borealis-polyethylene-site/