The Siri for Maintenance program is aimed at enabling efficient querying of maintenance-related digital documentation such as maintenance work order records, failure modes and effects analysis, maintenance strategy and original equipment manufacturer’s, root cause analysis and other sources.
We are already making progress with this. In collaboration with partners in the USA and Europe we are working on 1) a reference ontology for maintenance and 2) a paper demonstrating how to use natural language processing (NLP) to estimate parameters for asset failure distributions and MTTF values from unstructured text in maintenance work order records.
We are active in the Industrial Ontology Foundry, an international group of ontologists aimed at developing a reference ontology for manufacturing, and working with Informational Modeling and Testing Group at NIST.
Prof. Melinda Hodkiewicz was awarded an Visiting Fellowship to the Alan Turing Institute (ATI) in London for June/July 2018 to collaborate with Professor Mark Girolami (Lloyds Register ATI Foundation Research Chair in Data-Centric Engineering) and Professor Jennifer Whyte (Laing O’Rouke/ Royal Academy of Engineering Professor of Systems Integration at Imperial College) to progress the Siri for Maintenance program with infrastructure owners in the UK.
The team here at University of Western Australia brings together expertise in maintenance (Prof. Melinda Hodkiewicz), modal logic (Dr. Tim French) and NLP (Dr. Wei Liu), with PhD student (Tom Smoker) and software engineer (Caitlin Woods).
One of our greatest assets is our close links to the maintenance and asset practitioners here in the resources and infrastructure community in Perth WA. Perth is a globally significant location for mining and oil and gas with BHP, Rio Tinto, Shell, Chevron and other global players having significant investments and staff located here.
In the last few years we have had a number of CEED masters projects with industry resulting in a good understanding of their needs in this area and a CRC Mining sponsored PhD project which developed a rule-based system to produce a reliability database for mobile mining assets.
We are keen to talk to prospective PhD students with an interest in applied ontology and natural language processing.
We also offer Honours and Masters of Professional Engineering projects for this project.