INDUSTRIAL AI
PHM CHALLENGES (using Aviation as an example)

CHALLENGE AREAS

  • Effective utilization of design models for Digital Twins and PHM
  • Data availability (lagging utilization, limited segments of deployed fleets)

TECHNOLOGY CHALLENGES

  • Bootstrapping learning for early fleet experience
  • Learning from previous engine lines
  • Generalizing and modeling across varied global customer utilization/data

BUSINESS CHALLENGES

  • Spares management/risk of maintenance causing grounded aircraft
  • Data valuation for negotiation in contractual service agreements

SOLUTIONS ATTENDEES MIGHT WANT TO KNOW

  • Digital Maintenance, Repair and Operations (MRO) tools for proactive scheduled maintenance
  • Spares pool management tools
  • Health forecasting with mixed known and unknown failure modes

TAKE AWAY FROM THIS TOPIC

  • AI for Aviation should see some problems fall away with improved communication tech (5G+) to expedite and grow data availability… but other problems (particularly for early fleet experience) are still very much unsolved
  • Unlike other sectors, risk can be quantified very explicitly for the purposes of financial decision-making (for initial and growth investments)