PHMAP23 Organised session Proposal form
Proposals are invited for organised sessions at PHM Asia-Pacific 2023. These sessions are anexcellent opportunity to present a group of similarly focused presentations on any relevant topic
that would be of interest to PHMAP23 participants.
 Organised sessions may take the form of a symposium, in which there is a set ofpresentations (4 presentations per block) centred on a specific topic.
 Each session will be scheduled for an 80-minute block or connected two or more blocks.

Submittal Instructions• Deadline for Special Session Proposal: 31st January 2023
o Please complete the information below on the session organiser, title, theme andobjective, and the list of presenters (4 presenters per block) is required for a proposal oforganised session.
o Submitted proposals are reviewed by the PHMAP23 technical program committee.
o Due to the limitation of the session block, please understand that not all proposals may
be accepted.
o For proposals of special sessions that are accepted, the organizers are responsible for themoderation of the session at PHMAP23.
o Procedure, regulations and important dates for extended abstracts and full papers are
the same as those of regular sessions.
o Please submit this form to the secretariat e-mail: secretariat@phmap.jp

Session organiser: Dr Samir KHAN and Professor Takehisa YAIRI
Session title: Advances in System Health Management Advances for Aerial Vehicles
Field: Aerospace Engineering

Theme and objective:
The advent of system health monitoring methods is realised to preserve system functionality
within harsh operational environments. For unmanned vehicles, achieving near-zero downtime
whilst integrating more sophisticated health management systems stretches these challenges
that affect the cost, design periods, availability of experts, etc. No matter how well amaintenance system is designed, there are always deficiencies due to decisions and trade-offs
which present an inherent weakness in systems which only become evident once it is inoperation.
These challenges extend the need for system-level health management to help coordinate safety
path planning and navigation, control and communication and maintenance schedulingstrategies. A real-time health management solution indicates a continuous stream of operational
and labelled data that must satisfy several resources and latency requirements. Traditional
solutions to the problem rely heavily on well-defined features and prior supervised knowledge,
whereas most techniques refer to hand-crafted rules derived from known conditions. While
successful in controlled situations, these rules assume that good data is available for them tomodel processes; indicating that these rules will fail to generalise beyond known scenarios.

To investigate these issues in the UAV domain, state-of-the-art methods need to address thechallenges:On the use of machine learning for health management
To detect unknown instances in a multivariate time series
On out-of-the-box approaches that do not require expert knowledge for configuration
To address dimensionality and correlation challenges found in most health management
systems.

Tentative list of presenters (4 presenters per block):-Professor Nadjim Horri-Professor Vaios Lappas-Dr Samir Khan
-Dr Liew ChunFui