Template-Type: ReDIF-Article 1.0
Author-Name: Long Nguyen-Tuan
Author-X-Name-First: Long
Author-X-Name-Last: Nguyen-Tuan
Author-Name: Carsten Koenke
Author-X-Name-First: Carsten
Author-X-Name-Last: Koenke
Author-Name: Volker Bettzieche
Author-X-Name-First: Volker
Author-X-Name-Last: Bettzieche
Author-Name: Tom Lahmer
Author-X-Name-First: Tom
Author-X-Name-Last: Lahmer
Title: Uncertainty assessment in the results of inverse problems: applied to damage detection in masonry dams
Abstract:
In this work, we study the uncertainties in the results of inverse problems. The inverse problems solve damage identification problems in multifield-multiphase problems for fluid-flow problems in deforming porous materials under non-isothermal boundary conditions. These analyses are important within the structural health monitoring of masonry dams. Results of the inverse problems show a scatter due to different sources of uncertainties in model parameters, measurement data, field of measurements, and in the solving algorithms of the inverse problem. In order to see and analyse the scatter, the inverse problem is solved repeatedly by a sampling process. The uncertainty in the inverse solutions can be quantified by their probability distributions according to the sampling results.
Journal: Int. J. of Reliability and Safety
Pages: 2-23
Issue: 1/2
Volume: 12
Year: 2018
Keywords: damage identification; masonry dams; optimisation; uncertainty quantification; random field.
File-URL: http://www.inderscience.com/link.php?id=92498
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:2-23
Template-Type: ReDIF-Article 1.0
Author-Name: Ferenc Leichsenring
Author-X-Name-First: Ferenc
Author-X-Name-Last: Leichsenring
Author-Name: Christian Jenkel
Author-X-Name-First: Christian
Author-X-Name-Last: Jenkel
Author-Name: Wolfgang Graf
Author-X-Name-First: Wolfgang
Author-X-Name-Last: Graf
Author-Name: Michael Kaliske
Author-X-Name-First: Michael
Author-X-Name-Last: Kaliske
Title: Numerical simulation of wooden structures with polymorphic uncertainty in material properties
Abstract:
Uncertainties are inherently present in structural parameters such as loadings, boundary conditions or resistance of structural materials. Especially material properties and parameters of wood are strongly varying in consequence of growth and environmental conditions. To include this variation in structural analysis, available data needs to be modelled appropriately, e.g. by means of probability and, furthermore, fuzzy probability based random variables or fuzzy sets. In order to comprehend uncertainties induced by estimating the distribution parameters, the stochastic approach has been extended by fuzzy distribution parameters to fuzzy probability based random variables according to studies by Möller et al. To cope with epistemic uncertainties for e.g. geometric parameters of knotholes, fuzzy sets are used. The consequence for wooden structures is determined by fuzzy stochastic analysis in combination with a Finite Element (FE) simulation using a model suitable for characteristics of a timber structure by Jenkel and Kaliske.
Journal: Int. J. of Reliability and Safety
Pages: 24-45
Issue: 1/2
Volume: 12
Year: 2018
Keywords: polymorphic uncertainty; fuzzy randomness; stochastic modelling; wood mechanics; structural analysis.
File-URL: http://www.inderscience.com/link.php?id=92499
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:24-45
Template-Type: ReDIF-Article 1.0
Author-Name: Árpád Rózsás
Author-X-Name-First: Árpád
Author-X-Name-Last: Rózsás
Author-Name: Miroslav Sýkora
Author-X-Name-First: Miroslav
Author-X-Name-Last: Sýkora
Title: Using statistical and interval-based approaches to propagate snow measurement uncertainty to structural reliability
Abstract:
Observations are inevitably contaminated with measurement uncertainty, which is a predominant source of uncertainty in some cases. In present practice probabilistic models are typically fitted to measurements without proper consideration of this uncertainty. Hence, this study explores the effect of this simplification on structural reliability and provides recommendations on its appropriate treatment. Statistical and interval-based approaches are used to quantify and propagate measurement uncertainty in probabilistic reliability analysis. The two approaches are critically compared by analysing ground snow measurements that are often affected by large measurement uncertainty. The results indicate that measurement uncertainty may lead to significant (order of magnitude) underestimation of failure probability and should be taken into account in reliability analysis. Ranges of the key parameters are identified where measurement uncertainty should be considered. For practical applications, the lower interval bound and predictive reliability index are recommended as point estimates using interval and statistical analysis, respectively. The point estimates should be accompanied by uncertainty intervals, which convey valuable information about the credibility of results.
Journal: Int. J. of Reliability and Safety
Pages: 46-68
Issue: 1/2
Volume: 12
Year: 2018
Keywords: measurement uncertainty; snow; structural reliability; interval arithmetic; maximum likelihood; deconvolution.
File-URL: http://www.inderscience.com/link.php?id=92503
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:46-68
Template-Type: ReDIF-Article 1.0
Author-Name: Naiwei Lu
Author-X-Name-First: Naiwei
Author-X-Name-Last: Lu
Author-Name: Yang Liu
Author-X-Name-First: Yang
Author-X-Name-Last: Liu
Author-Name: Michael Beer
Author-X-Name-First: Michael
Author-X-Name-Last: Beer
Title: Extrapolation of extreme traffic load effects on a cable-stayed bridge based on weigh-in-motion measurements
Abstract:
The steadily growing traffic loading may become a hazard for the bridge safety. Compared to short and medium span bridges, long-span bridges suffer from simultaneous presence of multiple vehicle loads. This study presents an approach for extrapolating probabilistic extreme effects on long-span bridges based on weigh-in-motion (WIM) measurements. Three types of stochastic traffic load models are simulated based on the WIM measurements of a highway in China. The level-crossing rate of each stochastic traffic load is evaluated and integrated for extrapolating extreme traffic load effects. The probability of exceedance of a cable-stayed bridge is evaluated considering a linear traffic growth model. The numerical results show that the superposition of crossing rates is effective and feasible to model the probabilistic extreme effects of long-span bridges under the actual traffic loads. The increase of dense traffic flows is sensitive to the maximum load effect extrapolation. The dense traffic flow governs the limit state of traffic load on long-span bridges.
Journal: Int. J. of Reliability and Safety
Pages: 69-85
Issue: 1/2
Volume: 12
Year: 2018
Keywords: bridge; traffic load; extreme value; level-crossing theory; weigh-in-motion; probability of exceedance.
File-URL: http://www.inderscience.com/link.php?id=92504
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:69-85
Template-Type: ReDIF-Article 1.0
Author-Name: Ekaterina Auer
Author-X-Name-First: Ekaterina
Author-X-Name-Last: Auer
Author-Name: César Benavente-Peces
Author-X-Name-First: César
Author-X-Name-Last: Benavente-Peces
Author-Name: Andreas Ahrens
Author-X-Name-First: Andreas
Author-X-Name-Last: Ahrens
Title: Solving the power allocation problem using methods with result verification
Abstract:
Characterising how different types of uncertainty in the multiple-input multiple-output (MIMO) systems influence their performance is an important research topic. In this paper, we focus on the task of power allocation in fixed rate MIMO systems with singular value decomposition based channel separation. The interval analysis is used to develop a verified solution to the problem taking bounded uncertainty in parameters and rounding errors into account. We demonstrate that power allocation improves the bit error rate (BER) using an exemplary 4 × 4 MIMO channel for two distinct choices of the channel matrix and compute an upper bound on the BER under realistic uncertainty conditions. Besides, we show that a combined analytical/numerical procedure produces better results than the purely numerical one and identify parameters the mathematical model is most sensitive to.
Journal: Int. J. of Reliability and Safety
Pages: 86-102
Issue: 1/2
Volume: 12
Year: 2018
Keywords: interval analysis; result verification; MIMO systems; power allocation.
File-URL: http://www.inderscience.com/link.php?id=92506
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:86-102
Template-Type: ReDIF-Article 1.0
Author-Name: Yuan Luo
Author-X-Name-First: Yuan
Author-X-Name-Last: Luo
Author-Name: Donghaung Yan
Author-X-Name-First: Donghaung
Author-X-Name-Last: Yan
Author-Name: Ming Yuan
Author-X-Name-First: Ming
Author-X-Name-Last: Yuan
Title: Fatigue reliability evaluation of short-span concrete bridges under dynamic impacts of stochastic truck loading
Abstract:
This study presents an approach for the fatigue stress spectrum simulation of short-span bridges under the dynamic impacts of stochastic traffic loading. This approach is utilised to evaluate the fatigue reliability of existing bridges. Response functions defined by intervals are used to approximate the equivalent fatigue stress range of the bridge. Probability models of the fatigue stress ranges are evaluated with Gaussian mixture models. The effectiveness of the proposed method is validated via a case study of a simply supported bridge. The numerical results indicate that the impact effect of vehicle loads on short-span bridge leads to an obvious increase in both the stress range and the number of stress cycles. Both the degradation of the road surface roughness condition and the traffic growth lead to a significant decrease in the fatigue reliability.
Journal: Int. J. of Reliability and Safety
Pages: 103-121
Issue: 1/2
Volume: 12
Year: 2018
Keywords: fatigue reliability; vehicle-bridge coupled vibration; response surface method; stochastic traffic flow; road surface roughness; traffic volume.
File-URL: http://www.inderscience.com/link.php?id=92514
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:103-121
Template-Type: ReDIF-Article 1.0
Author-Name: Naijia Xiao
Author-X-Name-First: Naijia
Author-X-Name-Last: Xiao
Author-Name: Robert L. Mullen
Author-X-Name-First: Robert L.
Author-X-Name-Last: Mullen
Author-Name: Rafi L. Muhanna
Author-X-Name-First: Rafi L.
Author-X-Name-Last: Muhanna
Title: Solution of uncertain linear systems of equations with probability-box parameters
Abstract:
The solution of linear systems of equations is often a component of engineering simulation and modelling. Often, the system parameters are uncertain. One representation of this uncertainty is the use of probability-boxes (or p-boxes), which do not require complete information about the probability distribution underlying the random variables. P-boxes are the bounds on allowable continuous distribution function for the random variables. Arithmetic operations on p-boxes yield guaranteed bounds on the probability distribution of the solution, regardless the nature of dependency. The solutions of p-box linear systems of equations are presented in the context of FEA of structural systems. Loading and material uncertainties are described by p-boxes. Earlier Monte-Carlo p-box approach was limited to independent uncertainties. The governing p-box linear equations are solved by an iterative approach using a fixed-point formulation. The resulting formulation gives guaranteed bounds of the probability distribution of the structural responses, at a high computational efficiency and a low overestimation level.
Journal: Int. J. of Reliability and Safety
Pages: 147-165
Issue: 1/2
Volume: 12
Year: 2018
Keywords: uncertainty; probability-box; matrix decomposition; iterative enclosure method.
File-URL: http://www.inderscience.com/link.php?id=92515
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:147-165
Template-Type: ReDIF-Article 1.0
Author-Name: Naijia Xiao
Author-X-Name-First: Naijia
Author-X-Name-Last: Xiao
Author-Name: Francesco Fedele
Author-X-Name-First: Francesco
Author-X-Name-Last: Fedele
Author-Name: Rafi L. Muhanna
Author-X-Name-First: Rafi L.
Author-X-Name-Last: Muhanna
Title: Structural dynamic problems in time domain under uncertainty: an interval finite element approach
Abstract:
An analysis of the structural dynamic response under uncertainty is presented. Uncertainties in load and material are modelled as intervals exploiting the interval finite element method (IFEM). To reduce overestimation and increase the computational efficiency of the solution, we do not solve the dynamic problem by an explicit step-by-step time integration scheme. Instead, our approach solves for the structural variables in the whole time domain simultaneously by an implicit scheme using discrete Fourier transform and its inverse (DFT and IDFT). Non-trivial initial conditions are handled by modifying the right-hand side of the governing equation. To further reduce overestimation, a new decomposition strategy is applied to the IFEM matrices, and both primary and derived quantities are solved simultaneously. The final solution is obtained using an iterative enclosure method, and in our numerical examples the exact solution is enclosed at minimal computational cost.
Journal: Int. J. of Reliability and Safety
Pages: 122-146
Issue: 1/2
Volume: 12
Year: 2018
Keywords: interval finite element method; dynamic response; discrete Fourier transform; matrix decomposition; iterative enclosure method.
File-URL: http://www.inderscience.com/link.php?id=92516
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:122-146
Template-Type: ReDIF-Article 1.0
Author-Name: Shashwati Ray
Author-X-Name-First: Shashwati
Author-X-Name-Last: Ray
Author-Name: Shimpy Ralhan
Author-X-Name-First: Shimpy
Author-X-Name-Last: Ralhan
Title: Reliable power flow and short circuit analysis of systems with uncertain data
Abstract:
This paper addresses the problem of uncertainties in the input parameters by specifying them as compact intervals, taking into consideration the errors in modelling and measurement of transmission line parameters and also the continuous influence of load measurement errors and fluctuations in the load demand. The power flow equations are modelled as a set of nonlinear algebraic equations which are first linearised using Taylor series expansion and the solution is obtained by the Krawczyk's method of interval arithmetic. For the short circuit analysis the prefault conditions are obtained from power flow analysis and the faulty network is then solved using Thevenin's equivalent network as seen from the fault point. The proposed method is applied to 3 bus, 14 bus and 30 bus IEEE test systems where load currents and fault currents for each relay are obtained in bounded form and thus well-defined relay coordination pairs are available.
Journal: Int. J. of Reliability and Safety
Pages: 166-186
Issue: 1/2
Volume: 12
Year: 2018
Keywords: interval mathematics; load flow analysis; uncertain data; Newton Raphson method; Intlab toolbox; Krawczyk's method; short circuit studies.
File-URL: http://www.inderscience.com/link.php?id=92519
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:166-186
Template-Type: ReDIF-Article 1.0
Author-Name: Ba Trung Cao
Author-X-Name-First: Ba Trung
Author-X-Name-Last: Cao
Author-Name: Steffen Freitag
Author-X-Name-First: Steffen
Author-X-Name-Last: Freitag
Author-Name: Günther Meschke
Author-X-Name-First: Günther
Author-X-Name-Last: Meschke
Title: A fuzzy surrogate modelling approach for real-time predictions in mechanised tunnelling
Abstract:
In mechanised tunnelling, it is important to perform reliability analyses with respect to the tunnel face collapse and the damage risks of the tunnel lining and existing structures on the ground surface due to the tunnelling induced settlements. The reliability assessment requires to deal with limited information describing the local geology and the soil parameters due to the availability of only a small number of borehole data. In this paper, it is focused on real-time reliability analyses in mechanised tunnelling considering different types of uncertain data, i.e. combining epistemic and aleatoric sources of uncertainty within polymorphic uncertainty models. The system output of interest in these analyses is time variant tunnelling induced surface settlement fields, which are computed by a finite element simulation model. However, for real-time predictions with uncertain data, efficient and reliable surrogate models are required. A new surrogate modelling strategy is developed to predict time variant high dimensional fuzzy settlement fields in real-time. The predicted results of the new surrogate model show similar accuracy compared to the results obtained by optimisation based fuzzy analyses. Meanwhile, the computation time is significantly reduced especially in case of high dimensional outputs and in combination with the p-box approach in the case of polymorphic uncertain data.
Journal: Int. J. of Reliability and Safety
Pages: 187-217
Issue: 1/2
Volume: 12
Year: 2018
Keywords: surrogate models; proper orthogonal decomposition; artificial neural networks; uncertainty; reliability analysis; mechanised tunnelling; real-time predictions; fuzzy data.
File-URL: http://www.inderscience.com/link.php?id=92521
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:187-217
Template-Type: ReDIF-Article 1.0
Author-Name: Evgenija D. Popova
Author-X-Name-First: Evgenija D.
Author-X-Name-Last: Popova
Title: Equilibrium equations in interval models of structures
Abstract:
A new interval model of linear equilibrium equations in mechanics is based on the algebraic completion of classical interval arithmetic and provides more realistic and accurate models involving interval uncertainties. It replaces straightforwardly a linear deterministic model by an interval model in terms of proper and improper intervals, fully conforms to the equilibrium principle, and provides sharper enclosure of a resultant force than the methods based on classical interval arithmetic. The present paper presents the interval algebraic approach to linear equilibrium equations and discusses its applications to some interval models of structures.
Journal: Int. J. of Reliability and Safety
Pages: 218-235
Issue: 1/2
Volume: 12
Year: 2018
Keywords: static equilibrium; structures; interval arithmetic; proper and improper intervals; overestimation.
File-URL: http://www.inderscience.com/link.php?id=92525
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:1/2:p:218-235
Template-Type: ReDIF-Article 1.0
Author-Name: Amal Hentati
Author-X-Name-First: Amal
Author-X-Name-Last: Hentati
Author-Name: Mbarka Selmi
Author-X-Name-First: Mbarka
Author-X-Name-Last: Selmi
Author-Name: Tarek Kormi
Author-X-Name-First: Tarek
Author-X-Name-Last: Kormi
Author-Name: Nizar Bel Hadj Ali
Author-X-Name-First: Nizar Bel Hadj
Author-X-Name-Last: Ali
Title: Random finite element method for bearing capacity assessment of a shallow foundation under varied uniaxial loadings
Abstract:
This paper focuses on the application of the random finite element method (RFEM) for the assessment of the uniaxial bearing capacities of a shallow foundation subjected to centred vertical, horizontal and rotational loadings. The analysis combines finite element modelling, spatial variability analysis and Monte Carlo simulation. For this, the soil undrained shear strength is assumed to be variable in both horizontal and vertical directions with spatial dependency expressed via a Markovian autocorrelation function. The application of the proposed methodology to a shallow foundation permitted to highlight the insufficiency of the deterministic approach to predict the uniaxial foundation bearing capacities and led to different failure mechanisms.
Journal: Int. J. of Reliability and Safety
Pages: 237-260
Issue: 3
Volume: 12
Year: 2018
Keywords: random finite element method; random fields; spatial variability; shallow foundation reliability.
File-URL: http://www.inderscience.com/link.php?id=94939
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:3:p:237-260
Template-Type: ReDIF-Article 1.0
Author-Name: Walid Mechri
Author-X-Name-First: Walid
Author-X-Name-Last: Mechri
Author-Name: Wassim Snene
Author-X-Name-First: Wassim
Author-X-Name-Last: Snene
Author-Name: Kamel Ben Othman
Author-X-Name-First: Kamel Ben
Author-X-Name-Last: Othman
Title: Bayesian networks and probability boxes to model uncertainty in unavailability assessment
Abstract:
In this paper the problem of uncertainty in assessing unavailability of Safety Instrumented Systems (SIS) is treated. The characteristic parameters of the SIS including Common Cause Failure (CCF) factors are replaced by probability densities families (p-boxes) allowing reliability experts to express their uncertainty on the statement of values probabilities. We show how the imprecision is modelled and propagated in a Bayesian networks which induces uncertainty about the failure probability on demand of the SIS and its Safety Integrity Level (SIL). We will demonstrate how the uncertainty in the values of some characteristic parameters causes significant variations in the level risk.
Journal: Int. J. of Reliability and Safety
Pages: 261-278
Issue: 3
Volume: 12
Year: 2018
Keywords: safety systems; probability of failure on demand; uncertainty; Bayesian networks; common cause failure; p-boxes.
File-URL: http://www.inderscience.com/link.php?id=94940
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:3:p:261-278
Template-Type: ReDIF-Article 1.0
Author-Name: Maram Salem
Author-X-Name-First: Maram
Author-X-Name-Last: Salem
Author-Name: Zeinab Amin
Author-X-Name-First: Zeinab
Author-X-Name-Last: Amin
Author-Name: Moshira Ismail
Author-X-Name-First: Moshira
Author-X-Name-Last: Ismail
Title: A prediction interval approach to developing life test acceptance criteria for progressively censored data
Abstract:
In this paper we use the prediction-interval approach to construct acceptance criteria to determine whether or not certain batches of products are acceptable. The procedure is intended to protect both producers and consumers against highly defective lots and demonstrate that a required quality level is met with certain probability. The prediction interval approach is particularly useful to employ when the lifetime of the product represents the quality characteristic of interest. On the basis of a progressively censored sample from the Weibull lifetime distribution, the problem of constructing acceptance criteria by predicting a future lifetime based on an independent past sample of lifetimes from the same distribution is addressed in a Bayesian setting with a dependent bivariate prior. The Metropolis-within-Gibbs Sampler algorithm is used to obtain a sequence of draws from the posterior predictive distribution of future observations. This sequence is used to derive the prediction intervals based on which the lot acceptance criteria are determined. An example using real data is illustrated.
Journal: Int. J. of Reliability and Safety
Pages: 279-291
Issue: 3
Volume: 12
Year: 2018
Keywords: acceptance criteria; Metropolis-within-Gibbs sampler algorithm; prediction interval; progressively censored sample; Weibull lifetime model.
File-URL: http://www.inderscience.com/link.php?id=94941
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:3:p:279-291
Template-Type: ReDIF-Article 1.0
Author-Name: K. Meenakshi
Author-X-Name-First: K.
Author-X-Name-Last: Meenakshi
Author-Name: S.B. Singh
Author-X-Name-First: S.B.
Author-X-Name-Last: Singh
Title: Reliability analysis of ((e, f), k, lc)/(m, n):F system under multiple failure using universal generating function
Abstract:
In this paper ((e, f), k, l<SUB align="right"><SMALL>c</SMALL></SUB>)/(m, n):F system is taken for study under multiple failures. The target system has m and n rows and columns respectively. System fails if any (e, f) sub-matrices fail or any k components fail or consecutive l<SUB align="right"><SMALL>2</SMALL></SUB> components within any m rows or n columns fail out of (m, n) matrix. A Markov stochastic process has been applied to obtain probability of components of the systems. Reliability indices such as reliability, mean time to failure and sensitivity analysis of the considered system have been evaluated with the help of universal generating function. Finally, a numerical example is taken to demonstrate the model.
Journal: Int. J. of Reliability and Safety
Pages: 292-305
Issue: 3
Volume: 12
Year: 2018
Keywords: ((e,f),k,lc)/(m,n):F system; reliability; mean time to failure; sensitivity analysis; universal generating function.
File-URL: http://www.inderscience.com/link.php?id=94942
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:3:p:292-305
Template-Type: ReDIF-Article 1.0
Author-Name: Mario Fargnoli
Author-X-Name-First: Mario
Author-X-Name-Last: Fargnoli
Author-Name: Mara Lombardi
Author-X-Name-First: Mara
Author-X-Name-Last: Lombardi
Author-Name: Nicolas Haber
Author-X-Name-First: Nicolas
Author-X-Name-Last: Haber
Title: A fuzzy-QFD approach for the enhancement of work equipment safety: a case study in the agriculture sector
Abstract:
The paper proposes a design for safety methodology based on the use of the Quality Function Deployment (QFD) method, focusing on the need to identify and analyse risks related to a working task in an effective manner, i.e. considering the specific work activities related to such a task. To reduce the drawbacks of subjectivity while augmenting the consistency of judgements, the QFD was augmented by both the Delphi method and the fuzzy logic approach. To verify such an approach, it was implemented through a case study in the agricultural sector. While the proposed approach needs to be validated through further studies in different contexts, its positive results in performing hazard analysis and risk assessment in a comprehensive and thorough manner can contribute practically to the scientific knowledge on the application of QFD in design for safety activities.
Journal: Int. J. of Reliability and Safety
Pages: 306-326
Issue: 3
Volume: 12
Year: 2018
Keywords: design for safety; risk assessment; hazard analysis; quality function deployment; fuzzy logic; agricultural machinery.
File-URL: http://www.inderscience.com/link.php?id=94943
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:3:p:306-326
Template-Type: ReDIF-Article 1.0
Author-Name: Ajay Kumar
Author-X-Name-First: Ajay
Author-X-Name-Last: Kumar
Title: Availability optimisation of pre-heat exchanger system with random repair and failure rates using PSO
Abstract:
The main objective of this study is to carry out performance analysis and availability maximisation with randomly selected failure and repair rates (FRR) of a Pre-Heat Exchanger (PHE) system of a brewery plant using the particle swarm algorithm. The behavioural analysis of each system is carried out by Markovian method and the schematic diagram of the PHE system represents various components and their connectivity (series/parallel/hybrid) whereas the transition diagram explores various possibilities and combinations of working states of the components i.e. full capacity working (FCW), reduced capacity working (RCW) and failed state (FS). The mathematical equations are formulated using the transition diagrams in order to carry out steady state availability (SSA) and transient state availability (TSA) analysis. The prediction of failure and repair rate to attain maximum availability of a system is done by using Particle Swarm Optimisation (PSO) technique. These results are beneficial for plant personnel by steering of failure and repair rates to achieve maximum availability.
Journal: Int. J. of Reliability and Safety
Pages: 327-347
Issue: 4
Volume: 12
Year: 2018
Keywords: performance modelling; repair rates; availability optimisation; brewery plant; failure rate.
File-URL: http://www.inderscience.com/link.php?id=96058
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:4:p:327-347
Template-Type: ReDIF-Article 1.0
Author-Name: Monika Gahlot
Author-X-Name-First: Monika
Author-X-Name-Last: Gahlot
Author-Name: V.V. Singh
Author-X-Name-First: V.V.
Author-X-Name-Last: Singh
Author-Name: Hamisu Ismial Ayagi
Author-X-Name-First: Hamisu Ismial
Author-X-Name-Last: Ayagi
Author-Name: C.K. Goel
Author-X-Name-First: C.K.
Author-X-Name-Last: Goel
Title: Performance assessment of repairable system in series configuration under different types of failure and repair policies using copula linguistics
Abstract:
This paper deals with the study of reliability measures of a complex system consisting two subsystems, subsystem-1 and subsystem-2 in a series configuration. The subsystem-1 has three units that are working under the policy 2-out-of-3: F; policy, and the subsystem-2 has two units that are working under 1-out-of-2: G; policy. Failure rates of units of subsystems are constant and assumed to follow an exponential distribution, but their repair supports two types of distribution, general distribution, and Gumbel-Hougaard family copula distribution. Two types of repair (general repair and copula repair) have been employed for partially failed and completely failed states. The system is analysed using the supplementary variable technique. Some important measures of reliability such as availability of system, reliability of the system, MTTF and profit analysis have been discussed. Computations have taken a particular case by evaluating availability, reliability, MTTF and profit of operation of the system.
Journal: Int. J. of Reliability and Safety
Pages: 348-363
Issue: 4
Volume: 12
Year: 2018
Keywords: k-out-of-n:F system; k-out-of-n:G system; availability; MTTF; cost analysis; Gumbel-Hougaard family copula distribution.
File-URL: http://www.inderscience.com/link.php?id=96059
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:4:p:348-363
Template-Type: ReDIF-Article 1.0
Author-Name: Shuang Liu
Author-X-Name-First: Shuang
Author-X-Name-Last: Liu
Author-Name: Yu-Feng Shi
Author-X-Name-First: Yu-Feng
Author-X-Name-Last: Shi
Author-Name: Ming-Y Huang
Author-X-Name-First: Ming-Y
Author-X-Name-Last: Huang
Title: Model checking software product line based on multi-valued logic
Abstract:
Software product line (SPL) maximises commonality between software products to reduce cost and improve productivity. SPL has been widely applied in critical systems, and ensuring correctness of the system is thus of great importance. In this paper, we consider the incomplete designs in the early stage of software development. This enables detecting design errors earlier, reducing the cost of later development of final products. We first propose bilattice-based feature transitions systems (BFTSs), which support description of uncertainty. We then express system behavioural properties using ACTL formulas and define its semantics over BFTSs. On the one hand, we provide the procedures that translate BFTSs to multi-valued Kripke structure and develop a software model checker assistant BPMCA. On the other hand, we decompose the multi-valued BFTS to lower the complexity of model checking. Finally, we implement our approach and illustrate its effectiveness on a benchmark from the literature.
Journal: Int. J. of Reliability and Safety
Pages: 364-393
Issue: 4
Volume: 12
Year: 2018
Keywords: model checking; software product line; multi-valued.
File-URL: http://www.inderscience.com/link.php?id=96060
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:4:p:364-393
Template-Type: ReDIF-Article 1.0
Author-Name: Swapnil D. Khorate
Author-X-Name-First: Swapnil D.
Author-X-Name-Last: Khorate
Author-Name: Digambar T. Shirke
Author-X-Name-First: Digambar T.
Author-X-Name-Last: Shirke
Title: Bayesian sample size determination for product retesting after design change in Poisson distributed data
Abstract:
Many times, a design is changed after product validation testing in the real world. It occurs more frequently in the engineering field, which will create a problem of retesting the product with the original product specification without consideration of the degree and significance of the design change. As far as cost and resources are concerned, we have to find the minimum sample size for retesting the product. In this paper, we present a Bayesian method for determining sample size for retesting the redesigned product in Poisson distributed data via success-based testing prior. Numerical results of sample size for retesting the redesigned product are given. An example of paper pulp is provided.
Journal: Int. J. of Reliability and Safety
Pages: 394-405
Issue: 4
Volume: 12
Year: 2018
Keywords: Bayesian analysis; retesting; gamma priors; redesign; Poisson distribution; sample size reduction.
File-URL: http://www.inderscience.com/link.php?id=96070
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:4:p:394-405
Template-Type: ReDIF-Article 1.0
Author-Name: Weichao Dang
Author-X-Name-First: Weichao
Author-X-Name-Last: Dang
Author-Name: Jianchao Zeng
Author-X-Name-First: Jianchao
Author-X-Name-Last: Zeng
Title: State-control-limit-based rejuvenation modelling and optimisation of the virtualised cloud server
Abstract:
Software rejuvenation modelling and optimisation of the virtualised cloud server has been studied. A software rejuvenation policy on the virtual machines and the virtual machine monitor has been proposed in order to ensure high availability of the virtualised cloud server. The multi-component system, composed of the virtual machines and the virtual machine monitor, which are structurally dependent, has been reduced to the multiple two-component systems. The state-control-limit-based rejuvenation policy has been proposed and the joint probability density of the degraded state of the two-component VM-VMM has been derived. Furthermore, the solution to the joint probability density has been proposed. Finally, the stationary unavailability of the virtualised cloud server has been modelled. Numerical experiments have verified the correctness of the probability density function and the feasibility of the rejuvenation policy. The state-control-limit-based rejuvenation policy leads to lower unavailability of the virtualised cloud server in comparison with the lifetime-based rejuvenation policy.
Journal: Int. J. of Reliability and Safety
Pages: 406-428
Issue: 4
Volume: 12
Year: 2018
Keywords: software rejuvenation; state-control-limit; virtualised cloud server; availability.
File-URL: http://www.inderscience.com/link.php?id=96071
File-Format: text/html
File-Restriction: Access to full text is restricted to subscribers.
Handle: RePEc:ids:ijrsaf:v:12:y:2018:i:4:p:406-428