Components Distribution Pattern Time Interval (Minutes) Breakdown Preventive 14 Oil filter Lognormal 10 5 9 Oil filter Weibull 10 5 6 Oil filter Exponential 10 5 15 Oil filter Exponential 10 5 1 Solar filter Weibull 10 5 14 Solar filter Lognormal 10 5 7 Clutch plate Lognormal 120 90 4 Clutch plate Exponential 120 90 Total minimum downtime for each critical components that shown in table 2‚ it can be seen by the following steps : Example : oil filter Distribution type : Weibull distribution Parameter
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MTH3301 Fall 2012 Practice problems Counting 1. A closet contains 6 different pairs of shoes. Five shoes are drawn at random. What is the probability that at least one pair of shoes is obtained? 2. At a camera factory‚ an inspector checks 20 cameras and finds that three of them need adjustment before they can be shipped. Another employee carelessly mixes the cameras up so that no one knows which is which. Thus‚ the inspector must recheck the cameras one at a time until he locates all the bad ones
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Solutions Manual Discrete-Event System Simulation Third Edition Jerry Banks John S. Carson II Barry L. Nelson David M. Nicol August 31‚ 2000 Contents 1 Introduction to Simulation 2 Simulation Examples 3 General Principles 4 Simulation Software 5 Statistical Models in Simulation 6 Queueing Models 7 Random-Number Generation 8 Random-Variate Generation 9 Input Modeling 10 Verification and Validation of Simulation Models 11 Output Analysis for a Single Model 12 Comparison and Evaluation of Alternative
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should not exceed 1000 per day. Therefore‚ x1 + 2x2 ≤ 1000 (time constrain). Other constrains are: x1 + x2 ≤ 1000 (Plastic constrain). x2 ≤ 500 (Dress constrain). And the non-negative constrains are x1 ≥0‚ x2 ≥0 Maximize the profit function: p = 3x1 + 5x2 2. What are the advantages of Linear programming techniques? Ans. Advantages— 1. The linear programming technique helps to make the best possible use of available productive resources (such as time‚ labour‚ machines etc
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using EGC diversity kombiner. In this paper the dual EGC ( Equal Gain Combiner ) Diversity system is consider. The ucorrelated Rayleigh fading is presented. The cumulative density function - CDF of the dual EGC output signals and the joint of output signal and its the first time derivative is determined. The probability density function -PDF of the dual EGC output signals and the joint of output signal and its the first time derivative is determined. Keywords – EGC‚ PDF‚ CDF‚ Fading‚ Rayleigh
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case they experience a delay that is an exponentially distributed random variable with mean 3ms. However‚ when packets are routed to the fast processor they experience a constant processing delay of Ims. a) (4 points) Derive and plot the cumulative distribution function and the probability density ofthe packet delay and b) (2 points) calculate its mean ~ value. c) (4 points) You collect the following packet delay measurements: 3‚4‚1‚2‚2‚3 ms. Estimate how a ’\ many additional samples you should collect
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References: Atkinson‚ A. B. and Harrison‚ A. J. (1978). Distribution of Total Wealth in Britain Bikhchandani‚ S.‚ Hirshleifer‚ D.‚ and Welch‚ I. (1992). A theory of fads‚ fashion‚ custom‚ and cultural change as informational cascades Blumenthal‚ M. A. (1988). Auctions with constrained information: Blind bidding
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from given probability distributions. The different steps of this simulation and assumption made are explained below. 1. Simulation for the repair time. It is given that the repair time follows Repair Time (days) Probability 1. .20 2. .45 3. .25 4. .10 ----- 1.00 To generate a random number from the above distribution‚ we use the following
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on the cumulative outline below: 0.00 > r2 < 0.20‚ then it will take 1 day; 0.20 > r2 < 0.65‚ then it will take 2 days; 0.65 > r2 < 0.90‚ then it will take 3 days; and 0.90 > r2 < 1.00‚ then it will take 4 days. Intervals between Breakdowns Intervals between breakdowns are a probability distribution. The variables will be random and range between 0 through 6 weeks. As the time continues‚ the probability will increase. To determine this number a function of x
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Probability density functions • Autocorrelation functions • Autospectral density functions Joint statistical properties for pairs of random processes: • Joint probability density functions • Cross correlation functions • Cross spectral density functions • Frequency response functions • Coherence function → Let us deal with basic statistical properties… ©Marco Tarabini Analysis of random data 4 Common applications of probability density and distribution functions‚ beyond a basic
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