Mathematical Methods in Reliability
CONDITION MONITORING
THINKlab, Maxwell Building, University of Salford
Tuesday 16th June 2015
ABSTRACTS
Mr Roy Assaf (University of Salford)
Autonomous systems for maintenance planning
This talk contains details of my research project on autonomous systems for maintenance
planning in collaboration with Marel, which supplies integrated systems and standardised
individual machines for the meat, fish and poultry industries.
Professors Jian-Bo Yang1, Dong-Ling Xu1 & Xiaobin Xu1,2
(1University of Manchester & 2Hangzhou Dianzi University)
Evidential reasoning for fault diagnosis of railway systems
In this presentation, we introduce the evidential reasoning rule for conjunctive
combination of independent evidence and its relationship with Bayes’ rule in statistical
inference by examining a real life case study on fault diagnosis in rail track maintenance.
In this case study, data is gathered from an operational railway system. This case study is
intended to show the whole process of evidential reasoning in real life, from sample data
collection and evidence acquisition to the estimation of evidence reliability and weight and
the combination of evidence for fault diagnosis.
Dr Sabine von Hünerbein (University of Salford)
Wind turbine condition monitoring
With a growing amount of wind energy being produced from off-shore plants, remote
monitoring of wind turbine operation becomes crucial for financial viability. One method of
condition monitoring of wind turbine blades is using acoustical beam forming to identify
and localise faults such as delamination, residual debris or ice build-up. The talk will
report preliminary laboratory results and talk about possible strategies for the acoustics
monitoring of wind turbines.
Dr Van Phuc Do (Université de Lorraine)
Wear rate-state interaction for condition based maintenance
This presentation will begin with rate-state wear interactions for multi-component
systems. The deterioration speed of a component depends not only on its own state
(deterioration level) but also on the state of other ones. Then we will consider
maintenance policy models for a two-component system with wear interactions. To select
a component/group of components to be preventively maintained, adaptive preventive
maintenance and opportunistic maintenance rules are proposed. A cost model is
developed to find the optimal value of decision parameters.
Professor Frank Coolen (Durham University)
On the structure function in system reliability
In system reliability, the structure function models the functioning of a system for given
states of its components. As such, it is typically a straightforward binary function which
plays an essential role in reliability assessment, yet it has received remarkably little
attention in its own right. We explore the structure function in more depth, considering in
particular whether its generalization can provide useful further tools for reliability
assessment in case of uncertainty.
The recently introduced concept of survival signature provides a useful summary of the
structure function to simplify reliability assessment for systems with many components of
multiple types. We also consider how a generalized version of the structure function can
be linked to the survival signature. We illustrate the research with several examples
involving small systems, and we outline research topics towards implementation to large
practical systems and networks and their maintenance.
Dr Andrew Brint (University of Sheffield) & Ibrahim Al-Ghraify (Costain)
Whole life condition databases for managing utility assets
The UK is set to invest £375bn in infrastructure over the next 10 years, and this figure is
expected to be maintained or grow over the following 20 years. However, deciding when
a group of assets has reached the stage where they need to be refurbished or replaced is
often difficult as a detailed life history of the items has not been kept. Therefore
databases that have been developed for other purposes are pressed into service.
For example, the National Fault and Interruption Reporting System (NAFIRS) is used for
electricity distribution systems, while in the USA there is the National Bridge Inventory
(NBI) database. Additionally, different types of asset are frequently covered by very
different databases. Furthermore, each company records different information and has
different definitions of condition, and so it is difficult to decide on national policies and
standards.
The large sums set to be invested in infrastructure provide both a motivation and an
opportunity to specify practical whole life asset databases that will enable sound condition
based decisions to be made on refurbishment strategies in the future. Therefore this talk
will review the condition and failure information that is available in existing distribution
asset management databases, before discussing work on a new comprehensive whole
life database for highways.
Mr Francisco Arteche (Brunel University)
Correlation of pipeline corrosion and coating condition with ECDA survey results
This study looks at the key factors affecting external corrosion in underground pipelines.
Regression models have been performed in order to understand the underlying factors. It
has been found that the corrosion depth is not directly proportional to the coating defect
size, and therefore, small indications detected during pipeline survey should not be
omitted. Suggestions for improving the analysis of pipeline survey data are discussed and
an alternative framework is presented.
Dr Mimi Zhang (University of Strathclyde)
Maintenance modelling
Maintenance can be classified, according to efficiency, into three categories: perfect
maintenance, imperfect maintenance and minimal maintenance. To date, the literature on
imperfect maintenance is voluminous, and a myriad of models have been developed to
treat imperfect maintenance. The all-important problems in imperfect maintenance that
still remain widely open are (1) how to give practical grounds for an imperfectmaintenance model, (2) how to evaluate the involved unknown parameters efficiently, and
(3) how to test the fit of a real data set to an imperfect-maintenance model.
With the foregoing problems as motivation, this work develops an imperfect-maintenance
model by taking a physically meaningful approach. For the practical implementation of the
imperfect-maintenance model, we advance two methods, called the QMI method and the
spacing-likelihood algorithm, to estimate the unknown parameters. The two methods
complement each other and are widely applicable. To offer a practical guide for testing fit
to the imperfect-maintenance model, this work promotes a bootstrapping approach to
approximating the distribution of a test statistic. The attractions and dilemmas of the QMI
method and spacing-likelihood algorithm are revealed via a simulated data, and the utility
of the imperfect-maintenance model is evidenced via a real data set.
Mr Safar Alghamdi (University of Salford)
Reliability equivalence using generalized distributions and survival signature
We consider improving system reliability (a) a reduction method and (b) three duplication
methods: (i) hot duplication; (ii) cold duplication with perfect switching; (iii) cold duplication
with imperfect switching. Two measures for comparing system improvements are
considered, survival and mean reliability equivalence factors. We apply flexible lifetime
distributions to study: (1) simple parallel-series and series-parallel systems; (2) networks
and complex systems with multiple types of components.
We then derive reliability equivalence factors for any coherent system, with any structure
and lifetime distributions, using survival signature and the ReliabilityTheory R package.
Numerical examples for simple and complex systems are presented, to illustrate the
application of theoretical results and demonstrate the relative benefits of various
improvements. We conclude that considerable advances in reliability equivalence testing
are made possible by specifying and analysing the survival signature, especially for
modelling networks and complex systems.