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A review of asset management literature on multi-asset systems
This article gives an overview of the literature on asset management for multi-unit systems with an emphasis on two multi-asset categories: fleet (a system of homogeneous assets) and portfolio (a system of heterogeneous assets). As asset systems become more complicated, researchers have employed different terms to refer to their specific problems. With an
objective to facilitate readers in searching conducive studies to their interests, this paper establishes a novel classification scheme for multi-unit systems in accordance with essential features such as diversity of assets and intervention options. Moreover, discerning differences in characteristics between cross-component and cross-asset interactions, we select three types of potential multi-component dependencies (performance, stochastic, and resource) and extend their notions to be applicable to multi-asset systems. The investigation into these dependencies enables the identification of problems that could exist in real industrial settings
but are yet to be determined in academia. Ultimately, we delve into modelling approaches adopted by previous researchers. This comprehensive information allows us to offer the insights into the current trends in multi-asset maintenance. We expect that the output of this review paper will not only stress research gaps on multi-asset systems, but more importantly
help systematise future studies on this aspect
An overview of recent research results and future research avenues using simulation studies in project management
This paper gives an overview of three simulation studies in dynamic project scheduling integrating baseline scheduling with risk analysis and project control. This integration is known in the literature as dynamic scheduling. An integrated project control method is presented using a project control simulation approach that combines the three topics into a single decision support system. The method makes use of Monte Carlo simulations and connects schedule risk analysis (SRA) with earned value management (EVM). A corrective action mechanism is added to the simulation model to measure the efficiency of two alternative project control methods. At the end of the paper, a summary of recent and state-of-the-art results is given, and directions for future research based on a new research study are presented
Generic business process modelling framework for quantitative evaluation
PhD ThesisBusiness processes are the backbone of organisations used to automate
and increase the efficiency and effectiveness of their services and prod-
ucts. The rapid growth of the Internet and other Web based technologies
has sparked competition between organisations in attempting to provide
a faster, cheaper and smarter environment for customers. In response
to these requirements, organisations are examining how their business
processes may be evaluated so as to improve business performance.
This thesis proposes a generic framework to expand the applicability
of various quantitative evaluation to a large class of business processes.
The framework introduces a novel engineering methodology that defines
a modelling formalism to represent business processes that can be solved
for a set of performance and optimisation algorithms. The methodology
allows various types of algorithms used in model-based business pro-
cess improvement and optimisation to be plugged in a single modelling
formalism. As a part of the framework, a generic modelling formalism
(MWF-wR) is developed to represent business processes so as to allow
quantitative evaluation and to select the parameters for the associated
performance evaluation and optimisation.
The generic framework is designed and implemented by developing soft-
ware support tools using Java as object oriented programming language
combining three main modules: (i) a business process specification mod-
ule to define the components of the business process model, (ii) a stochas-
tic Petri net module to map the business process model to a stochastic
Petri net, and (iii) an algorithms module to solve the models for various
performance optimisation objectives. Furthermore, a literature survey
of different aspects of business processes including modelling and analy-
sis techniques provides an overview of the current state of research and
highlights gaps in business process modelling and performance analy-
sis. Finally, experiments are introduced to investigate the validity of the
presented approach
Risk-Based Optimal Scheduling for the Predictive Maintenance of Railway Infrastructure
In this thesis a risk-based decision support system to schedule the predictive maintenance activities, is proposed. The model deals with the maintenance planning of a railway infrastructure in which the due-dates are defined via failure risk analysis.The novelty of the approach consists of the risk concept introduction in railway maintenance scheduling, according to ISO 55000 guidelines, thus implying that the maintenance priorities are based on asset criticality, determined taking into account the relevant failure probability, related to asset degradation conditions, and the consequent damages
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
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