Search results for: Hidden Function Modeling.

Authors: S. M. Ali, N. R. Dhar

Abstract:

Tool wear and surface roughness prediction plays a significant role in machining industry for proper planning and control of machining parameters and optimization of cutting conditions. This paper deals with developing an artificial neural network (ANN) model as a function of cutting parameters in turning steel under minimum quantity lubrication (MQL). A feed-forward backpropagation network with twenty five hidden neurons has been selected as the optimum network. The co-efficient of determination (R2) between model predictions and experimental values are 0.9915, 0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra respectively. The results imply that the model can be used easily to forecast tool wear and surface roughness in response to cutting parameters.

Keywords: ANN, MQL, Surface Roughness, Tool Wear.

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Authors: Y. Z. Wu, Z. Dong, S. K. You

Abstract:

Global approximation using metamodel for complex mathematical function or computer model over a large variable domain is often needed in sensibility analysis, computer simulation, optimal control, and global design optimization of complex, multiphysics systems. To overcome the limitations of the existing response surface (RS), surrogate or metamodel modeling methods for complex models over large variable domain, a new adaptive and regressive RS modeling method using quadratic functions and local area model improvement schemes is introduced. The method applies an iterative and Latin hypercube sampling based RS update process, divides the entire domain of design variables into multiple cells, identifies rougher cells with large modeling error, and further divides these cells along the roughest dimension direction. A small number of additional sampling points from the original, expensive model are added over the small and isolated rough cells to improve the RS model locally until the model accuracy criteria are satisfied. The method then combines local RS cells to regenerate the global RS model with satisfactory accuracy. An effective RS cells sorting algorithm is also introduced to improve the efficiency of model evaluation. Benchmark tests are presented and use of the new metamodeling method to replace complex hybrid electrical vehicle powertrain performance model in vehicle design optimization and optimal control are discussed.

Keywords: Global approximation, polynomial response surface, domain decomposition, domain combination, multiphysics modeling, hybrid powertrain optimization

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Authors: F. Esmaeilzadeh, M. E. Zeighami, J. Fathi

Abstract:

This paper describes a one-dimensional numerical model for natural gas production from the dissociation of methane hydrate in hydrate-capped gas reservoir under depressurization and thermal stimulation. Some of the hydrate reservoirs discovered are overlying a free-gas layer, known as hydrate-capped gas reservoirs. These reservoirs are thought to be easiest and probably the first type of hydrate reservoirs to be produced. The mathematical equations that can be described this type of reservoir include mass balance, heat balance and kinetics of hydrate decomposition. These non-linear partial differential equations are solved using finite-difference fully implicit scheme. In the model, the effect of convection and conduction heat transfer, variation change of formation porosity, the effect of using different equations of state such as PR and ER and steam or hot water injection are considered. In addition distributions of pressure, temperature, saturation of gas, hydrate and water in the reservoir are evaluated. It is shown that the gas production rate is a sensitive function of well pressure.

Keywords: Hydrate reservoir, numerical modeling, depressurization, thermal stimulation, gas generation.

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Authors: Trien V. Do, Jong-Weon Lee

Abstract:

This paper describes a 3D modeling system in Augmented Reality environment, named 3DARModeler. It can be considered a simple version of 3D Studio Max with necessary functions for a modeling system such as creating objects, applying texture, adding animation, estimating real light sources and casting shadows. The 3DARModeler introduces convenient, and effective human-computer interaction to build 3D models by combining both the traditional input method (mouse/keyboard) and the tangible input method (markers). It has the ability to align a new virtual object with the existing parts of a model. The 3DARModeler targets nontechnical users. As such, they do not need much knowledge of computer graphics and modeling techniques. All they have to do is select basic objects, customize their attributes, and put them together to build a 3D model in a simple and intuitive way as if they were doing in the real world. Using the hierarchical modeling technique, the users are able to group several basic objects to manage them as a unified, complex object. The system can also connect with other 3D systems by importing and exporting VRML/3Ds Max files. A module of speech recognition is included in the system to provide flexible user interfaces.

Keywords: 3D Modeling, Augmented Reality, GeometricModeling, Virtual Reality

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Authors: Xin Zhao, Yin-fan Zhu, Wei-ping Wang, Qun Li

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The Influence Diagrams (IDs) is a kind of Probabilistic Belief Networks for graphic modeling. The usage of IDs can improve the communication among field experts, modelers, and decision makers, by showing the issue frame discussed from a high-level point of view. This paper enhances the Time-Sliced Influence Diagrams (TSIDs, or called Dynamic IDs) based formalism from a Discrete Event Systems Modeling and Simulation (DES M&S) perspective, for Exploring Analysis (EA) modeling. The enhancements enable a modeler to specify times occurred of endogenous events dynamically with stochastic sampling as model running and to describe the inter- influences among them with variable nodes in a dynamic situation that the existing TSIDs fails to capture. The new class of model is named Dynamic-Stochastic Influence Diagrams (DSIDs). The paper includes a description of the modeling formalism and the hiberarchy simulators implementing its simulation algorithm, and shows a case study to illustrate its enhancements.

Keywords: Time-sliced influence diagrams, discrete event systems, dynamic-stochastic influence diagrams, modeling formalism, simulation algorithm.

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Authors: Sumit Kumar, Sunil Kumar, Chandan Deep Singh

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This paper presents modeling and simulation of flexible robot in an underwater environment. The underwater environment completely contrasts with ground or space environment. The robot in an underwater situation is subjected to various dynamic forces like buoyancy forces, hydrostatic and hydrodynamic forces. The underwater robot is modeled as Rayleigh beam. The developed model further allows estimating the deflection of tip in two directions. The complete dynamics of the underwater robot is analyzed, which is the main focus of this investigation. The control of robot trajectory is not discussed in this paper. Simulation is performed using Symbol Shakti software.

Keywords: Bond graph modeling, dynamics. modeling, Rayleigh beam, underwater robot.

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Authors: Takashi Mitsuishi, Koji Saigusa

Abstract:

This paper presents circular polar coordinates transformation of periodic fuzzy membership function. The purpose is identification of domain of periodic membership functions in consequent part of IF-THEN rules. Proposed methods in this paper remove complicatedness concerning domain of periodic membership function from defuzzification in fuzzy approximate reasoning. Defuzzification on circular polar coordinates is also proposed.

Keywords: Defuzzification, periodic membership function, polar coordinates transformation.

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Authors: Hoi-Lam Ma, Sai-Ho Chung

Abstract:

In traditional integrated berth allocation with quay crane assignment models, time dimension is usually assumed in hourly based. However, nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time. Therefore, the traditional hourly-based modeling approach may cause significant berth and quay crane idling, and consequently cannot meet their practical needs. In this connection, a 15-minute-based modeling approach is requested by industrial practitioners. Accordingly, a Three-level Genetic Algorithm (3LGA) with Quay Crane (QC) shifting heuristics is designed to fulfill the research gap. The objective function here is to minimize the total service time. Preliminary numerical results show that the proposed 15-minute-based approach can reduce the berth and QC idling significantly.

Keywords: Transshipment, integrated berth allocation, variable-in-time quay crane assignment, quay crane assignment.

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Authors: Ethar H. Khalil, Bahaa I. Kazem

Abstract:

In this work a software simulation model has been proposed for two driven wheels mobile robot path planning; that can navigate in dynamic environment with static distributed obstacles. The work involves utilizing Bezier curve method in a proposed N order matrix form; for engineering the mobile robot path. The Bezier curve drawbacks in this field have been diagnosed. Two directions: Up and Right function has been proposed; Probability Recursive Function (PRF) to overcome those drawbacks. PRF functionality has been developed through a proposed; obstacle detection function, optimization function which has the capability of prediction the optimum path without comparison between all feasible paths, and N order Bezier curve function that ensures the drawing of the obtained path. The simulation results that have been taken showed; the mobile robot travels successfully from starting point and reaching its goal point. All obstacles that are located in its way have been avoided. This navigation is being done successfully using the proposed PRF techniques.

Keywords: Mobile robot, path planning, Bezier curve.

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Authors: Kahloul Laid, Chaoui Allaoua

Abstract:

Code mobility technologies attract more and more developers and consumers. Numerous domains are concerned, many platforms are developed and interest applications are realized. However, developing good software products requires modeling, analyzing and proving steps. The choice of models and modeling languages is so critical on these steps. Formal tools are powerful in analyzing and proving steps. However, poorness of classical modeling language to model mobility requires proposition of new models. The objective of this paper is to provide a specific formalism “Coloured Reconfigurable Nets" and to show how this one seems to be adequate to model different kinds of code mobility.

Keywords: Code mobility, modelling mobility, labelled reconfigurable nets, Coloured reconfigurable nets, mobile code design paradigms.

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Authors: Kristina Davoian, Wolfram-M. Lippe

Abstract:

Evolutionary Programming (EP) represents a methodology of Evolutionary Algorithms (EA) in which mutation is considered as a main reproduction operator. This paper presents a novel EP approach for Artificial Neural Networks (ANN) learning. The proposed strategy consists of two components: the self-adaptive, which contains phenotype information and the dynamic, which is described by genotype. Self-adaptation is achieved by the addition of a value, called the network weight, which depends on a total number of hidden layers and an average number of neurons in hidden layers. The dynamic component changes its value depending on the fitness of a chromosome, exposed to mutation. Thus, the mutation step size is controlled by two components, encapsulated in the algorithm, which adjust it according to the characteristics of a predefined ANN architecture and the fitness of a particular chromosome. The comparative analysis of the proposed approach and the classical EP (Gaussian mutation) showed, that that the significant acceleration of the evolution process is achieved by using both phenotype and genotype information in the mutation strategy.

Keywords: Artificial Neural Networks (ANN), Learning Theory, Evolutionary Programming (EP), Mutation, Self-Adaptation.

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Authors: Alok Kumar Routa, Priya Ranjan Mohanty

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Complex seismic signatures are generated due to the complexity of the subsurface which is difficult to interpret. In the present study, an attempt has been made to model the complex subsurface using the Ray tracing modeling technique. Add to this, for the imaging of these geological features, Kirchhoff’s prestack depth migration is applied over the synthetic common shot gather dataset. It is found that the Kirchhoff’s migration technique in addition with the Ray tracing modeling concept has the flexibility towards the imaging of various complex geology which gives satisfactory results with proper delineation of the reflectors at their respective true depth position. The entire work has been carried out under the MATLAB environment.

Keywords: Kirchhoff’s migration, Prestack depth migration, Ray tracing modeling, Velocity model.

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Authors: Seung-Won Jung, Hye-Soo Kim, Le Thanh Ha, Seung-Jin Baek, Sung-Jea Ko

Abstract:

In this paper, a novel deinterlacing algorithm is proposed. The proposed algorithm approximates the distribution of the luminance into a polynomial function. Instead of using one polynomial function for all pixels, different polynomial functions are used for the uniform, texture, and directional edge regions. The function coefficients for each region are computed by matrix multiplications. Experimental results demonstrate that the proposed method performs better than the conventional algorithms.

Keywords: Deinterlacing, polynomial interpolation.

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Authors: Usha Sridhar, Sridhar Mandyam

Abstract:

We propose a multi-agent based utilitarian approach to model and understand information flows in social networks that lead to Pareto optimal informational exchanges. We model the individual expected utility function of the agents to reflect the net value of information received. We show how this model, adapted from a theorem by Karl Borch dealing with an actuarial Risk Exchange concept in the Insurance industry, can be used for social network analysis. We develop a utilitarian framework that allows us to interpret Pareto optimal exchanges of value as potential information flows, while achieving a maximization of a sum of expected utilities of information of the group of agents. We examine some interesting conditions on the utility function under which the flows are optimal. We illustrate the promise of this new approach to attach economic value to information in networks with a synthetic example.

Keywords: Borch's Theorem , Economic value of information, Information Exchange, Pareto Optimal Solution, Social Networks, Utility Functions

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Authors: Khaing Win Mar, Thinn Thu Naing

Abstract:

Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.

Keywords: Precipitation prediction, monthly precipitation, neural network models, Myanmar.

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Authors: M. Abdulkawi, Z. K. Eshkuvatov, N. M. A. Nik Long

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This manuscript presents a method for the numerical solution of the Cauchy type singular integral equations of the first kind, over a finite segment which is bounded at the end points of the finite segment. The Chebyshev polynomials of the second kind with the corresponding weight function have been used to approximate the density function. The force function is approximated by using the Chebyshev polynomials of the first kind. It is shown that the numerical solution of characteristic singular integral equation is identical with the exact solution, when the force function is a cubic function. Moreover, it also shown that this numerical method gives exact solution for other singular integral equations with degenerate kernels.

Keywords: Singular integral equations, Cauchy kernel, Chebyshev polynomials, interpolation.

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Authors: Joonas Pääkkönen

Abstract:

In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling.

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Authors: Daniel Siahaan, Aditya Prapanca

Abstract:

The emerging Semantic Web has been attracted many researchers and developers. New applications have been developed on top of Semantic Web and many supporting tools introduced to improve its software development process. Metadata modeling is one of development process where supporting tools exists. The existing tools are lack of readability and easiness for a domain knowledge expert to graphically models a problem in semantic model. In this paper, a metadata modeling tool called RDFGraph is proposed. This tool is meant to solve those problems. RDFGraph is also designed to work with modern database management systems that support RDF and to improve the performance of the query execution process. The testing result shows that the rules used in RDFGraph follows the W3C standard and the graphical model produced in this tool is properly translated and correct.

Keywords: CASE tool, data modeling, semantic web

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Authors: Anežka Jurčíková, Miroslav Rosmanit

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The subject of this paper is to verify the behavior of the truss-type CHS joint which is beyond the scope of use of the EN 1993-1-8. This is performed by using the numerical modeling in program ANSYS and the analytical methods recommended in the CIDECT publication. The recommendations for numerical modeling of such types of joints as well as for evaluation of load-bearing capacity of the joint are given in this paper. The results from both analytical and numerical models are compared.

Keywords: ANSYS, CHS joints, FEM, Lattice structure

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Authors: Ε. Giovanis

Abstract:

In this paper we present an autoregressive model with neural networks modeling and standard error backpropagation algorithm training optimization in order to predict the gross domestic product (GDP) growth rate of four countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer after the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model in the out-of-sample period. The idea behind this approach is to propose a parametric regression with weighted variables in order to test for the statistical significance and the magnitude of the estimated autoregressive coefficients and simultaneously to estimate the forecasts.

Keywords: Autoregressive model, Error back-propagation Feed-Forward neural networks, , Gross Domestic Product

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Authors: Randa Ibrahim Elanwar, Mohsen Rashwan, Samia Mashali

Abstract:

In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.

Keywords: Arabic, Hidden Markov Models, online handwriting, word segmentation

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Authors: Nadia M. G. AL-Saidi

Abstract:

Since 1984 many schemes have been proposed for digital signature protocol, among them those that based on discrete log and factorizations. However a new identification scheme based on iterated function (IFS) systems are proposed and proved to be more efficient. In this study the proposed identification scheme is transformed into a digital signature scheme by using a one way hash function. It is a generalization of the GQ signature schemes. The attractor of the IFS is used to obtain public key from a private one, and in the encryption and decryption of a hash function. Our aim is to provide techniques and tools which may be useful towards developing cryptographic protocols. Comparisons between the proposed scheme and fractal digital signature scheme based on RSA setting, as well as, with the conventional Guillou-Quisquater signature, and RSA signature schemes is performed to prove that, the proposed scheme is efficient and with high performance.

Keywords: Digital signature, Fractal, Iterated function systems(IFS), Guillou-Quisquater (GQ) protocol, Zero-knowledge (ZK)

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Authors: Kausik Halder, Nabendu Chaki, Ranjan Dasgupta

Abstract:

We present a modeling framework that supports the engineering of early requirements specifications for design of learner centric dynamic Learning Management System. The framework is based on i* modeling tool and Means End Analysis, that adopts primitive concepts for modeling early requirements (such as actor, goal, and strategic dependency). We show how pedagogical and computational requirements for designing a learner centric Learning Management system can be adapted for the automatic early requirement engineering specifications. Finally, we presented a model on a Learner Quanta based adaptive Courseware. Our early requirement analysis shows that how means end analysis reveals gaps and inconsistencies in early requirements specifications that are by no means trivial to discover without the help of formal analysis tool.

Keywords: Adaptive Courseware, Early Requirement Engineering, Means End Analysis, Organizational Modeling, Requirement Modeling.

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Authors: Ehsan Mahdavi

Abstract:

In this paper, we apply the Exp-function method to Rosenau-Kawahara and Rosenau-KdV equations. Rosenau-Kawahara equation is the combination of the Rosenau and standard Kawahara equations and Rosenau-KdV equation is the combination of the Rosenau and standard KdV equations. These equations are nonlinear partial differential equations (NPDE) which play an important role in mathematical physics. Exp-function method is easy, succinct and powerful to implement to nonlinear partial differential equations arising in mathematical physics. We mainly try to present an application of Exp-function method and offer solutions for common errors wich occur during some of the recent works.

Keywords: Exp-function method, Rosenau Kawahara equation, Rosenau Korteweg-de Vries equation, nonlinear partial differential equation.

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Authors: Totok R. Biyanto, Sonny Irawan, Hiskia J. Ginting, Matradji, Ya’umar, A. I. Fitri

Abstract:

Steam injection is the most suitable of Enhanced Oil Recovery (EOR) methods to recover high viscosity oil. This is due to the capabilities of steam to reduce oil viscosity and increase the sweep capability of oil from the injection well toward the production well. Oil operating conditions in production should be match well with the operating condition target at the bottom of the production well. It is influenced by oil properties and reservoir rock properties. Hence, the operating condition should be optimized. Optimization requires three components i.e., objective function, model, and optimization technique. In this paper, the objective function is to obtain the optimum operating condition at the production well. The model was built using Darcy equation and mass-energy balance. The optimization technique utilizes Duelist Algorithm due to the effectiveness of its algorithm to obtain the desirable optimization results at the optimum operating condition.

Keywords: Enhanced oil recovery, steam injection, operating conditions, modeling, optimization, Duelist algorithm.

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Authors: Faezeh Mohammadi, Ebrahim Ebrahimi, Neda Azimi

Abstract:

Use of ultrasound waves is one of the techniques for increasing the mixing and mass transfer in the microdevices. Ultrasound propagation into liquid medium leads to stimulation of the fluid, creates turbulence and so increases the mixing performance. In this study, CFD modeling of two-phase flow in a pitted micromixer equipped with a piezoelectric with frequency of 1.7 MHz has been studied. CFD modeling of micromixer at different velocity of fluid flow in the absence of ultrasound waves and with ultrasound application has been performed. The hydrodynamic of fluid flow and mixing efficiency for using ultrasound has been compared with the layout of no ultrasound application. The result of CFD modeling shows well agreements with the experimental results. The results showed that the flow pattern inside the micromixer in the absence of ultrasound waves is parallel, while when ultrasound has been applied, it is not parallel. In fact, propagation of ultrasound energy into the fluid flow in the studied micromixer changed the hydrodynamic and the forms of the flow pattern and caused to mixing enhancement. In general, from the CFD modeling results, it can be concluded that the applying ultrasound energy into the liquid medium causes an increase in the turbulences and mixing and consequently, improves the mass transfer rate within the micromixer.

Keywords: CFD modeling, ultrasound, mixing, mass transfer.

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Authors: R. N. Patel

Abstract:

This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.

Keywords: Area control error, Artificial intelligence, Automatic generation control, Genetic Algorithms and modeling, ISE, ITAE, Particle swarm optimization.

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Authors: Kyu Han Kim, Soon Kyu Kwon, Heung Sun Yoon, Jong Tae Kim

Abstract:

In this paper, we demonstrate the adaptive least-mean-square (LMS) filter modeling using SystemC. SystemC is a modeling language that allows designer to model both hardware and software component and makes it possible to design from high level system of abstraction to low level system of abstraction. We produced five adaptive least-mean-square filter models that are classed as five abstraction levels using SystemC proceeding from the abstract model to the more concrete model.

Keywords: Adaptive Filter, Least-Mean-Square Algorithm, SystemC, Transversal Fir Filter.

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Authors: Grzegorz Zinkiewicz

Abstract:

The paper explores affective potential implicit in Bergman’s movies. This is done by the use of affect theory and the concept of affect in terms of paradigmatic and syntagmatic relations, from both diachronic and synchronic perspective. Since its inception in the early 2000s, affect theory has been applied to a number of academic fields. In Film Studies, it offers new avenues for discovering deeper, hidden layers of a given film. The aim is to show that the form and content of the films by Ingmar Bergman are determined by their inner affects that function independently of the viewer and, to an extent, are autonomous entities that can be analysed in separation from the auteur and actual characters. The paper discovers layers in Ingmar Bergman films and focuses on aspects that are often marginalised or studied from other viewpoints such as the connection between the content and visual side. As a result, a revaluation of Bergman films is possible that is more consistent with his original interpretations and comments included in his lectures, interviews and autobiography.

Keywords: Affect theory, experimental cinema, Ingmar Bergman, film as autonomous entity.

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Authors: F. Urem, K. Fertalj, Ž. Mikulić

Abstract:

This paper presents the possibilities of using Weibull statistical distribution in modeling the distribution of defects in ERP systems. There follows a case study, which examines helpdesk records of defects that were reported as the result of one ERP subsystem upgrade. The result of the applied modeling is in modeling the reliability of the ERP system from a user perspective with estimated parameters like expected maximum number of defects in one day or predicted minimum of defects between two upgrades. Applied measurement-based analysis framework is proved to be suitable in predicting future states of the reliability of the observed ERP subsystems.

Keywords: ERP, reliability, Weibull

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