The UWA NLP-TLP group has had over $1.8M of funding since 2018 to develop tools and processes to “Transform Maintenance through Data Science”. By collaborating with over 20 national and international organisations we have developed and released 11 open-source language processing software and web tools and the largest maintenance dataset for fine-tuning AI models.

This talk describes these tools, what value they add for reliability engineers and planners, and how organisations are using them.

These tools establish a basis to enable processing and exchange of maintenance data within and between organisations. Continuing to process maintenance texts and procedures manually is no longer acceptable from productivity or quality control perspectives now we have viable and open AI-enabled alternatives.

There is no doubt that the future is here with us and applications like ChatGPT are just a tip of the iceberg. Will we still need Maintenance SMEs or Advisors to tell us how to troubleshoot or direct us on possible causes and resolution? Or will the machines take over and do it better than us?