Comparison between maintenance policies based on q-Weibull and Weibull models

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Edilson Machado de Assis ◽  
Celso Luiz Santiago Figueirôa Filho ◽  
Gabriel Costa Lima ◽  
Gisele Maria de Oliveira Salles ◽  
Ailton Pinto
Keyword(s):  
Weibull Distribution ◽  
Preventive Maintenance ◽  
Weibull Model ◽  
Computational Effort ◽  
Numerical Comparison ◽  
Content Type ◽  
Optimal Interval ◽  
Maintenance Cycle ◽  
Weibull Models ◽  
Maintenance Policies

PurposeThe purpose of this article is to compare maintenance policies based on Weibull and q-Weibull models.Design/methodology/approachThis paper uses analytical developments, several figures and tables for graphical and numerical comparison. Previously published hydropower equipment data are used as examples.FindingsModels for optimal maintenance interval determination based on q-Weibull distribution were defined. Closed-form expressions were found, and this allows the application of the method with small computational effort.Practical implicationsThe use of the q-Weibull model to guide the definition of maintenance strategy allows decision-making to be more consistent with sample data. The flexibility of the q-Weibull model is able to produce failure rate modeling with five different formats: decreasing, constant, increasing, unimodal and U-shaped. In this way, the maintenance strategies resulting from this model should be more assertive.Originality/valueExpressions for determining the optimal interval of preventive maintenance were deduced from q-Weibull distribution. Expected costs per maintenance cycle of Brazilian hydropower equipment were calculated with q-Weibull and Weibull distributions. These results were compared in terms of absolute values and trends. Although a large number of works on corrective and preventive maintenance have been proposed, no applications of the q-Weibull distribution were found in literature.

On preventive maintenance policies: a selection framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Imad Alsyouf ◽  
Sadeque Hamdan ◽  
Mohammad Shamsuzzaman ◽  
Salah Haridy ◽  
Iyad Alawaysheh
Keyword(s):  
Preventive Maintenance ◽  
Fuzzy Ahp ◽  
Critical Component ◽  
Multi Objective Optimization ◽  
Maintenance Policy ◽  
Coolant Pump ◽  
Content Type ◽  
Multi Objective ◽  
Maintenance Policies ◽  
Preventive Maintenance Policy

PurposeThis paper develops a framework for selecting the most efficient and effective preventive maintenance policy using multiple-criteria decision making and multi-objective optimization.Design/methodology/approachThe critical component is identified with a list of maintenance policies, and then its failure data are collected and the optimization objective functions are defined. Fuzzy AHP is used to prioritize each objective based on the experts' questionnaire. Weighted comprehensive criterion method is used to solve the multi-objective models for each policy. Finally, the effectiveness and efficiency are calculated to select the best maintenance policy.FindingsFor a fleet of buses in hot climate environment where coolant pump is identified as the most critical component, it was found that block-GAN policy is the most efficient and effective one with a 10.24% of cost saving and 0.34 expected number of failures per cycle compared to age policy and block-BAO policy.Research limitations/implicationsOnly three maintenance policies are compared and studied. Other maintenance policies can also be considered in future.Practical implicationsThe proposed methodology is implemented in UAE for selecting a maintenance scheme for a critical component in a fleet of buses. It can be validated later in other Gulf countries.Originality/valueThis research lays a solid foundation for selecting the most efficient and effective preventive maintenance policy for different applications and sectors using MCDM and multi-objective optimization to improve reliability and avoid economic loss.

Modeling failure rate of a robotic welding station using generalized q-distributions

2015 ◽  
Vol 32 (2) ◽  
pp. 156-166 ◽  
Author(s):  
Edilson M. Assis ◽  
Ernesto P. Borges ◽  
Silvio A.B. Vieira de Melo ◽  
Leizer Schnitman
Keyword(s):  
Failure Rate ◽  
Least Squares Method ◽  
Weibull Model ◽  
Time Range ◽  
Additional Parameter ◽  
Robotic Welding ◽  
Estimation Of Parameters ◽  
Content Type ◽  
Weibull Models ◽  
Single Set

Purpose – The purpose of this paper is to compare four life data models, namely the exponential and the Weibull models, and their corresponding generalized versions, q-exponential and q-Weibull models, by means of one practical application. Design/methodology/approach – Application of the models to a practical example (a welding station), with estimation of parameters by the use of the least squares method, and the Akaike Information Criterion (AIC). Findings – The data of the example considered in this paper is divided into three regimes, decreasing, constant and increasing failure rate, and the q-Weibull model describes the bathtub curve displayed by the data with a single set of parameters. Practical implications – The simplicity and flexibility of the q-Weibull model may be very useful for practitioners of reliability analysis, and its benefits surpasses the inconvenience of the additional parameter, as AIC shows. Originality/value – The q-Weibull model is compared in detail with other three models, through the analysis of one example that clearly exhibits a bathtub curve, and it is shown that it can describe the whole time range with a single set of parameters.

A Mathematical Model for Soil-Water Characteristic Curve by Weibull Distribution

2021 ◽  
Author(s):  
Deng-li Pan ◽  
Wan kui Ni ◽  
Chen-yun Kang ◽  
Xiang-fei Lü ◽  
Hai-man Wang
Keyword(s):  
Mathematical Model ◽  
Weibull Distribution ◽  
Soil Water ◽  
Characteristic Curve ◽  
Weibull Model ◽  
Soil Behavior ◽  
Soil Water Characteristic Curve ◽  
Weibull Models ◽  
Two Parameters ◽  
Fitting Accuracy

Abstract The soil-water characteristic curve (SWCC) plays a crucial role in unsaturated soil behavior. However, none of the models are fully applicable to all soil classes. Therefore, it is necessary to come up with more different models to best-fit the measured SWCC data. In this paper, a mathematical model (that is, Weibull model) for the soil-water characteristic curve was proposed based on two-parameters Weibull distribution. It only contains two parameters a and n, the effects of which on the SWCC are independent. The Brutsaert, van Genutchen, Boltzman and Weibull models were fitted to 24 SWCC data sets from UNSODA 2.0. The quality of fit for these models was compared. Results showed that Weibull model was desirably accurate to fit data from a variety of soil classes with 0.999 for R2 and 0.010 for RMSE. Taking into account the \(\overline {{{R^2}}}\), RMSE and ∑Ri criteria, it is therefore suggested that the exponential-based Weibull model had a higher fitting accuracy and performed marginally better than the Brutsaert and VG models. As respect to the criteria of AICc, the Weibull and Brutsaert models performed almost equally well but both had a better performance than VG model. The VG model had the largest average number of iterations, as such, it was relatively difficult to fit. However, the Boltzman model had a lower fitting accuracy and less flexibility in comparison with the other models. Consequently, the Weibull model could be used as an alternative to the soil-water characteristic curve models.

Preventive maintenance (PM) planning: a review

2017 ◽  
Vol 23 (2) ◽  
pp. 114-143 ◽  
Author(s):  
Ernnie Illyani Basri ◽  
Izatul Hamimi Abdul Razak ◽  
Hasnida Ab-Samat ◽  
Shahrul Kamaruddin
Keyword(s):  
Preventive Maintenance ◽  
Mathematical Formulation ◽  
Holistic View ◽  
Content Type ◽  
Maintenance System ◽  
Comprehensive Information ◽  
System Review ◽  
Maintenance Policies ◽  
Mathematical Computation ◽  
Planning Concept

Purpose The purpose of this paper is to provide comprehensive information on preventive maintenance (PM) planning and methods used in the industry in order to achieve an effective maintenance system. Design/methodology/approach The literature review is organized in a way that provides the general overview of the researches done in the PM. This paper discusses the literatures that had been reviewed on four main topics, which are the holistic view of maintenance policies, PM planning, PM planning concept and PM planning-based in developing optimal planning in executing PM actions. Findings PM policy is one of the original proactive techniques that has been used since the start of researches on maintenance system. Review of the methods presented in this paper shows that most researches analyse effectiveness using artificial intelligence, simulation, mathematical formulation, matrix formation, critical analysis and multi-criteria method. While in practice, PM activities were either planned based on cost, time or failure. Research trends on planning and methods for PM show that the variation of approaches used over the year from early 1990s until today. Practical implications Research about PM is known to be extensively conducted and majority of companies applied the policy in their production line. However, most analysis and method suggested in published literatures were done based on mathematical computation rather than focussing on solution to real problems in the industry. This normally would lead to the problems in understanding by the practitioner. Therefore, this paper presented researches on PM planning and suggested on the methods that are practical, simple and effective for application in the real industry. Originality/value The originality of this paper comes from its detail analysis of PM planning in term of its research focus and also direction for application. Extensive reviews on the methods adopted in relation to PM planning based on the planning-based such as cost-based, time-based and failure-based were also provided.

scholarly journals ON DISCRETE WEIBULL DISTRIBUTION

2014 ◽  
Vol 20 (79) ◽  
pp. 1-9
Author(s):  
ALI HUSEEN ALWAKEEL
Keyword(s):  
Distribution Function ◽  
Weibull Distribution ◽  
Hazard Function ◽  
Random Variable ◽  
Weibull Model ◽  
Cumulative Distribution ◽  
Probability Mass Function ◽  
Failure Rate Function ◽  
Weibull Models ◽  
Discrete Values

Most of the Weibull models studied in the literature were appropriate for modelling a continuous random variable which assumes the variable takes on real values over the interval [0,∞]. One of the new studies in statistics is when the variables take on discrete values. The idea was first introduced by Nakagawa and Osaki, as they introduced discrete Weibull distribution with two shape parameters q and β where      0 < q < 1 and b > 0. Weibull models for modelling discrete random variables assume only non-negative integer values. Such models are useful for modelling for example; the number of cycles to failure when components are subjected to cyclical loading. Discrete Weibull models can be obtained as the discrete counterparts of either the distribution function or the failure rate function of the standard Weibull model. Which lead to different models. This paper discusses the discrete model which is the counterpart of the standard two-parameter Weibull distribution. It covers the determination of the probability mass function, cumulative distribution function, survivor function, hazard function, and the pseudo-hazard function.

ON DISCRETE WEIBULL DISTRIBUTION

2014 ◽  
Vol 20 (79) ◽  
pp. 1
Author(s):  
علي عبد الحسين الوكيل
Keyword(s):  
Distribution Function ◽  
Weibull Distribution ◽  
Hazard Function ◽  
Random Variable ◽  
Weibull Model ◽  
Cumulative Distribution ◽  
Probability Mass Function ◽  
Failure Rate Function ◽  
Weibull Models ◽  
Discrete Values

  Most of the Weibull models studied in the literature were appropriate for modelling a continuous random variable which assume the variable takes on real values over the interval [0,∞]. One of the new studies in statistics is when the variables takes on discrete values. The idea was first introduced by Nakagawa and Osaki, as they introduced discrete Weibull distribution with two shape parameters q and β where      0 < q < 1 and b > 0. Weibull models for modelling discrete random variables assume only non-negative integer values. Such models are useful for modelling for example; the number of cycles to failure when components are subjected to cyclical loading. Discrete Weibull models can be obtained as the discrete counter parts of either the distribution function or the failure rate function of the standard Weibull model. Which lead to different models. This paper discusses the discrete model which is the counter part of the standard two-parameter Weibull distribution. It covers the determination of the probability mass function, cumulative distribution function, survivor function, hazard function, and the pseudo-hazard function.

Periodic and sequential preventive maintenance policies

1986 ◽  
Vol 23 (2) ◽  
pp. 536-542 ◽  
Author(s):  
Toshio Nakagawa
Keyword(s):  
Weibull Distribution ◽  
Preventive Maintenance ◽  
Minimal Repair ◽  
Expected Cost ◽  
Optimal Policies ◽  
Failure Distribution ◽  
Maintenance Policies

This paper considers periodic and sequential preventive maintenance (PM) policies for the system with minimal repair at failure: the PM is done (i) at periodic times kx and (ii) at constant intervals xk (k = 1, 2, ···, N). The system has a different failure distribution between PM'S and is replaced at the Nth PM. The optimal policies which minimize the expected cost rates are discussed. The optimal x and N of periodic PM and {xk} of sequential PM are easily computed in a Weibull distribution case.

Periodic and sequential preventive maintenance policies

1986 ◽  
Vol 23 (02) ◽  
pp. 536-542 ◽  
Author(s):  
Toshio Nakagawa
Keyword(s):  
Weibull Distribution ◽  
Preventive Maintenance ◽  
Minimal Repair ◽  
Expected Cost ◽  
Optimal Policies ◽  
Failure Distribution ◽  
Maintenance Policies

This paper considers periodic and sequential preventive maintenance (PM) policies for the system with minimal repair at failure: the PM is done (i) at periodic timeskxand (ii) at constant intervalsxk(k= 1, 2, ···, N). The system has a different failure distribution between PM'S and is replaced at the Nth PM. The optimal policies which minimize the expected cost rates are discussed. The optimalxand N of periodic PM and {xk} of sequential PM are easily computed in a Weibull distribution case.

Motion in frequency domain for harmonic balance simulation of electrical machines

2018 ◽  
Vol 37 (4) ◽  
pp. 1449-1460
Author(s):  
Markus Wick ◽  
Sebastian Grabmaier ◽  
Matthias Juettner ◽  
Wolfgang Rucker
Keyword(s):  
Steady State ◽  
Frequency Domain ◽  
Efficient Method ◽  
Harmonic Balance ◽  
Eddy Currents ◽  
Computational Effort ◽  
Electrical Machines ◽  
Accurate Approximation ◽  
Content Type ◽  
Magnetic Devices

Purpose The high computational effort of steady-state simulations limits the optimization of electrical machines. Stationary solvers calculate a fast but less accurate approximation without eddy-currents and hysteresis losses. The harmonic balance approach is known for efficient and accurate simulations of magnetic devices in the frequency domain. But it lacks an efficient method for the motion of the geometry. Design/methodology/approach The high computational effort of steady-state simulations limits the optimization of electrical machines. Stationary solvers calculate a fast but less accurate approximation without eddy-currents and hysteresis losses. The harmonic balance approach is known for efficient and accurate simulations of magnetic devices in the frequency domain. But it lacks an efficient method for the motion of the geometry. Findings The three-phase symmetry reduces the simulated geometry to the sixth part of one pole. The motion transforms to a frequency offset in the angular Fourier series decomposition. The calculation overhead of the Fourier integrals is negligible. The air impedance approximation increases the accuracy and yields a convergence speed of three iterations per decade. Research limitations/implications Only linear materials and two-dimensional geometries are shown for clearness. Researchers are encouraged to adopt recent harmonic balance findings and to evaluate the performance and accuracy of both formulations for larger applications. Practical implications This method offers fast-frequency domain simulations in the optimization process of rotating machines and so an efficient way to treat time-dependent effects such as eddy-currents or voltage-driven coils. Originality/value This paper proposes a new, efficient and accurate method to simulate a rotating machine in the frequency domain.

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