156,941 research outputs found
Uncertainty-aware dynamic reliability analysis framework for complex systems
YesCritical technological systems exhibit complex dynamic characteristics such as time-dependent
behavior, functional dependencies among events, sequencing and priority of causes that may alter the effects
of failure. Dynamic fault trees (DFTs) have been used in the past to model the failure logic of such systems,
but the quantitative analysis of DFTs has assumed the existence of precise failure data and statistical
independence among events, which are unrealistic assumptions. In this paper, we propose an improved
approach to reliability analysis of dynamic systems, allowing for uncertain failure data and statistical and
stochastic dependencies among events. In the proposed framework, DFTs are used for dynamic failure
modeling. Quantitative evaluation of DFTs is performed by converting them into generalized stochastic Petri
nets. When failure data are unavailable, expert judgment and fuzzy set theory are used to obtain reasonable
estimates. The approach is demonstrated on a simplified model of a cardiac assist system.DEIS H2020 Project under Grant 732242
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After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study
After-sales maintenance services can be a very profitable source of incomes for original equipment manufacturers (OEM) due to the increasing interest of assetsâ users on performance-based contracts. However, when it concerns the product value-adding process, OEM have traditionally been more focused on improving their production processes, rather than on complementing their products by offering after-sales services; consequently leading to difficulties in offering them efficiently. Furthermore, both due to the high uncertainty of the assetsâ behaviour and the inherent challenges of managing the maintenance process (e.g. maintenance strategy to be followed or resources to be deployed), it is complex to make business out of the provision of after-sales services. With the aim of helping the business and maintenance decision makers at this point, this paper proposes a framework for optimising the incomes of after-sales maintenance services through: 1) implementing advanced multi-objective opportunistic maintenance strategies that sistematically consider the assetsâ operational context in order to perform preventive maintenance during most favourable conditions, 2) considering the specific OEMsâ and usersâ needs, and 3) assessing both internal and external uncertainties that might condition the after-sales servicesâ success. The developed case study for the wind energy sector demonstrates the suitability of the presented framework for optimising the after-sales services.EU Framework Programme Horizon 2020, MSCA-RISE-2014: Marie SkĆodowska-Curie Research and Innovation Staff Exchange (RISE) (grant agreement number 645733- Sustain-Owner-H2020-MSCA-RISE-2014) and the EmaitekPlus 2016-2017 Program of the Basque Government
Reliability-based economic model predictive control for generalized flow-based networks including actuators' health-aware capabilities
This paper proposes a reliability-based economic model predictive control (MPC) strategy for the management of generalized flow-based networks, integrating some ideas on network service reliability, dynamic safety stock planning, and degradation of equipment health. The proposed strategy is based on a single-layer economic optimisation problem with dynamic constraints, which includes two enhancements with respect to existing approaches. The first enhancement considers chance-constraint programming to compute an optimal inventory replenishment policy based on a desired risk acceptability level, leading to dynamically allocate safety stocks in flow-based networks to satisfy non-stationary flow demands. The second enhancement computes a smart distribution of the control effort and maximises actuatorsâ availability by estimating their degradation and reliability. The proposed approach is illustrated with an application of water transport networks using the Barcelona network as the considered case study.Peer ReviewedPostprint (author's final draft
Risk Management in the Arctic Offshore: Wicked Problems Require New Paradigms
Recent project-management literature and high-profile disastersâthe financial crisis, the BP
Deepwater Horizon oil spill, and the Fukushima nuclear accidentâillustrate the flaws of
traditional risk models for complex projects. This research examines how various groups with
interests in the Arctic offshore define risks. The findings link the wicked problem framework and
the emerging paradigm of Project Management of the Second Order (PM-2). Wicked problems
are problems that are unstructured, complex, irregular, interactive, adaptive, and novel. The
authors synthesize literature on the topic to offer strategies for navigating wicked problems,
provide new variables to deconstruct traditional risk models, and integrate objective and
subjective schools of risk analysis
Quality of Information in Mobile Crowdsensing: Survey and Research Challenges
Smartphones have become the most pervasive devices in people's lives, and are
clearly transforming the way we live and perceive technology. Today's
smartphones benefit from almost ubiquitous Internet connectivity and come
equipped with a plethora of inexpensive yet powerful embedded sensors, such as
accelerometer, gyroscope, microphone, and camera. This unique combination has
enabled revolutionary applications based on the mobile crowdsensing paradigm,
such as real-time road traffic monitoring, air and noise pollution, crime
control, and wildlife monitoring, just to name a few. Differently from prior
sensing paradigms, humans are now the primary actors of the sensing process,
since they become fundamental in retrieving reliable and up-to-date information
about the event being monitored. As humans may behave unreliably or
maliciously, assessing and guaranteeing Quality of Information (QoI) becomes
more important than ever. In this paper, we provide a new framework for
defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the
current state-of-the-art on the topic. We also outline novel research
challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN
Safety management theory and the military expeditionary organization: A critical theoretical reflection
Management of safety within organizations has become a key topic within safety science. Theorizing on this subject covers a diverse pallet of concepts such as âresilienceâ and âsafety management systemsâ. Recent studies indicate that safety management theory has deficiencies. Our interpretation of these deficiencies is that much confusion originates from the issue that crucial meta-theoretical assumptions are mostly implicit or applied inconsistently. In particular, we argue that these meta-theoretical assumptions are of a systems theoretical nature. Therefore, we provide a framework that will be able to explicate and reflect on systems theoretical assumptions. With this framework, we analyze the ability of two frequently used safety management theories to tackle the problem of managing safety of Dutch military expeditionary organizations. This paper will show that inconsistent and implicit application of systems theoretical assumptions in these safety management theories results in problems to tackle such a practical problem adequately. We conclude with a reflection on the pros and cons of our framework. Also, we suggest particular meta-theoretical aspects that seem to be essential for applying safety management theory to organizations
Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World
This report documents the program and the outcomes of GI-Dagstuhl Seminar
16394 "Software Performance Engineering in the DevOps World".
The seminar addressed the problem of performance-aware DevOps. Both, DevOps
and performance engineering have been growing trends over the past one to two
years, in no small part due to the rise in importance of identifying
performance anomalies in the operations (Ops) of cloud and big data systems and
feeding these back to the development (Dev). However, so far, the research
community has treated software engineering, performance engineering, and cloud
computing mostly as individual research areas. We aimed to identify
cross-community collaboration, and to set the path for long-lasting
collaborations towards performance-aware DevOps.
The main goal of the seminar was to bring together young researchers (PhD
students in a later stage of their PhD, as well as PostDocs or Junior
Professors) in the areas of (i) software engineering, (ii) performance
engineering, and (iii) cloud computing and big data to present their current
research projects, to exchange experience and expertise, to discuss research
challenges, and to develop ideas for future collaborations
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