<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/EB4C56B8-D475-430C-A82D-91E1FA32BECB" ns1:id="EB4C56B8-D475-430C-A82D-91E1FA32BECB"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/9936D852-6308-4978-AF32-A0B0EBBBFDE9" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/34F13D2D-7FD2-4106-BAB0-2A0315BF849E" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/77E7EAAB-05F4-4130-8566-59AF7E8E67FD" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/34F13D2D-7FD2-4106-BAB0-2A0315BF849E" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/6F3F01BE-B645-424E-8C31-DD3505296170" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/3AF98652-621F-420B-A0FE-094777D22202" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2019-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/3947E9EF-5029-4C7C-92D0-960BC3893E46" ns1:rel="FUND" ns1:start="2016-08-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">102435</ns2:identifier></ns2:identifiers><ns2:title>Integrated Ship Energy &amp;amp; Maintenance Management System (ISEMMS)</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The ISEMMS project aims at the development of an integrated energy and maintenance management system

to optimise the energy efficiency and minimise the maintenance cost of ship machinery systems by monitoring

of the performance, emissions and plant condition parameters, culminating in proposing the most effective

energy and maintenance scheduling. A number of advanced technologies including model based power

management and fault diagnosis, condition/performance/emissions parameters monitoring, machinery

vibration monitoring, infrared radiation and fluid analysis, multi-criteria optimisation techniques and machinery

risk analysis will be combinatory used. Data acquisition will be integrated with the ship control systems and the

acquired 'big' data will be analysed using statistical and artificial intelligence algorithms and transferred ashore

using satellite communications providing decision support and advise for optimal operation/adjustment of the

system parameters and the most effective maintenance scheduling. The ISEMMS system development will lead

to a significant improvement in the vessels energy efficient operation and the reduction of the operational cost.</ns2:abstractText></ns2:project>