Om tjänsten
Data-Driven Criticality Analysis for PM2 Background and purpose Criticality analyses of industrial equipment are often based on
manual expert assessments. At the same time, large amounts of historical maintenance and operational data are available and could
potentially be used to make the assessment more objective and efficient. The purpose of this thesis is to investigate how existing
maintenance and operational data can be used to assess equipment criticality of maintainable asset level in a more automated and
data-driven way. Method The work will include identifying relevant data sources and developing a model based on, for example: -
Failure history and downtime (MTBF/MTTR) - Maintenance cost and labour hours - Spare part availability and lead time - Production
impact and redundancy The model will be tested in a selected area (Returfiber and Lut) and benchmarked against the existing
manually performed criticality analyses for the same equipment. Expected outcome A proposed model for data-driven criticality
analysis of maintainable items in PM2, designed to be scalable to other assets and areas at the mill, validated in a pilot area
(Returfiber and Lut), together with an assessment of how well it can replace or complement manual criticality assessment. If you
have any questions, please contact Weronica Lundberg, Head of Department – Technology Division Smurfit Westrock Piteå AB