International Journal of Industrial Engineering & Production Research

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Main result of this paper is to derive the exact analytical expressions of information and covariance matrix for multivariate Pareto, Burr and related distributions. These distributions arise as tractable parametric models in reliability, actuarial science, economics, finance and telecommunications. We showed that all the calculations can be obtained from one main moment multidimensional integral whose expression is obtained through some particular change of variables. Indeed, we consider that this calculus technique for that improper integral has its own importance.

 

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Abstract: Nowadays knowledge is recognized as an important enabler for competitive advantages and many companies are beginning to establish knowledge management systems. Within the last few years many organizations tried to design a suitable knowledge management system and many of them were successful. This paper is to discover critical success factors (CSF) of knowledge management (KM) and their relationships in an effective way. A qualitative case study technique has been used in this paper for data collection and analysis. In this way, grounded theory (GT) research approach has been selected .The collected data are categorized and analyzed through specific stages of GT. A semantic network has been developed by categorized data showing the relationships between the extracted CSFs and finally a theory has been emerged. The semantic network and the emerged theory show the roadmap of success in KM area for the organizations.

 

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Main result of this paper is to derive the exact analytical expressions of information and covariance matrices for multivariate Burr III and logistic distributions. These distributions arise as tractable parametric models in price and income distributions, reliability, economics, Human population, some biological organisms to model agricultural population data and survival data. We showed that all the calculations can be obtained from one main moment multi dimensional integral whose expression is obtained through some particular change of variables. Indeed, we consider that this calculus technique for improper integral has its own importance .

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Modal parameter extraction of high speed shafts is of critical importance in mechanical design of turbo-pumps. Due to the complex geometry and peripheral components of turbo-pumps, difficulties can arise in determination of modal parameters. In this study, modal properties of a turbo-pump shaft, was studied by experimental modal analysis, and using different excitation techniques. An innovative suspending method is proposed to reduce noise-to-signal ratio, resulting from classic suspensions. Comparison of the experimental results obtained from the proposed suspension method and the traditional ones shows that the proposed approach was a promising method, when classic methods fall short of expectations in analysis of complex structures. To validate the experimental results, numerical solution was carried out using simplified geometric modeling combined with the Finite Element Method. The simplified modeling approach can be considered as a reliable theoretical method for numerical modal analysis of similar structures. Comparison of experimental and numerical results shows that there is a good conformity between the results of two approaches . 

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Microcasting Shape-Deposition-Manufacturing is an approach to Solid-Freeform-Fabrication (SFF) process which is a novel method for rapid automated manufacturing of near-net-shape multi-material parts with complex geometries. By this method, objects are made by sequentially depositing molten metal droplets on a substrate and shaping by a CNC tool, layer by layer. Important issues are concerned with remelting dept of substrate, cooling rate and stress build up. In the present study attempts were made to numerically model the heat transfer and phase change within the droplet/substrate, making a better understanding of process performance. Thus, making a brief literature review, a 2-D transient heat transfer Finite Element Analysis was carried out by the use of ANSYS multiphysics, in which solidification is handled using apparent capacity method. Verification was done by available experimental data in the open literature to ensure model predictions. The model was run under various process parameters and obtained results presented in the form of temperature fields, solidification profiles, cooling curves and remelting history curves. Solidification profile studies predict a columnar dendritic solidified structure in the vertical orientation which was in agreement with metallographic sections published earlier. Parametric studied were also carried out under different boundary conditions, initial temperature of the droplet and Substrate temperature. It was concluded that 1) the process is not sensitive to convection/radiation effects from the surface. 2) the main parameter that can control the maximum remelting dept is initial temperature of the droplet. the more drop temperature, the more remelting dept. This parameter also affects cooling rate during solidification. 3) Increasing substrate temperature showed a decreased cooling rate in solid, which can be used to reduce residual stresses, but it had a minor effect on the cooling rates during solidification .

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The paper is devoted to solution of some problems in nuclear power station generating unit intellectual control systems using genetic algorithms on the basis of control system model development, optimizations methods of their direct quality indices and improved integral quadratic estimates. Some mathematical vector models were obtained for control system multicriterion quality indices with due consideration of stability and quality indices criteria, this increasing the reliability of optimal control system synthesis. Optimal control systems with fuzzy controllers were synthesized for nuclear reactor, steam generator and steam turbine, thus allowing comparison between fuzzy controllers and traditional PID controllers. Mathematical models built for nuclear power station generating unit control systems, including nuclear reactor, steam generator, steam turbine and their control systems interacting under normal operational modes, which permitted to perform parametrical synthesis of system and to study various power unit control laws. On the basis of power unit control system models controllers were synthesized for normal operational modes.

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In the current study, a dual-channel supply chain is considered containing one manufacturer and two retailers. It is assumed that the manufacturer and retailers have the same decision powers. A game-theoretic approach is developed to analyze pricing decisions under the centralized and decentralized scenarios. First, the Nash model is established to obtain the equilibrium decisions in the decentralized case. Then, the centralized model is developed to maximize the total profit of the whole system. Finally, the equilibrium decisions are discussed and some managerial insights are revealed. 

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The number of nonconforming items in a sample is monitored using the fraction defective known as the np-chart. The performance of the np-chart in Phase II depends on the accuracy of the estimated parameter in Phase I. Although taking large sample sizes ensures the accuracy of the estimated parameter, it can be impractical for attributes in some cases. Recently, the traditional c-chart and the np-chart with some adjustments have been studied to guarantee the in-control performance. Due to technology progresses, researchers have faced high-quality processes with a very low rate of nonconformity, for which traditional control charts are inadequate. To ameliorate such inaccuracy, this study develops a new method for designing the np-chart, such that the in-control performance is guaranteed with a pre-defined probability. The proposed method uses Cornish-Fisher expansions and the bootstrap method to guarantee the desired conditional in-control average run length. Through a simulation study, this study shows that the proposed adjustments improve the np-charts’ in-control performance.

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In recent years, it has been proven that integrating statistical process control, maintenance policy, and production can bring more benefits for the entire production systems. In the literature of triple-concept integrated models, it has generally been assumed that the observations are independent. However, the existence of correlated structures in some practical applications put the traditional control charts in trouble. The mixed EWMA-CUSUM (MEC) control chart and the ARMA control chart are effective tools to monitor the mean of autocorrelated processes. This paper proposes an integrated model subject to some constraints for determining the decision variables of triple concepts in the presence of autocorrelated data. Three types of autocorrelated processes are investigated to study their effects on the results. Moreover, the results of the MEC and ARMA charts are compared. Due to the complexity of the model, a particle swarm optimization (PSO) algorithm is applied to select optimal decision variables. An industrial example and extensive comparisons are provided