6. A die forge press operates an average of 1000 hr/yr. Under a minimal repair concept, machinefailures generated a nonhomogenous Poisson process having the following intensity function with tmeasured in operating hours: p(t) = 0.0000391 to.7. When the machine has failed, the repair timeis lognormal with tmed -7.0 hours and a shape parameter of 0.8.a) Given the NHPP (Non-Homogeneous Poisson Process) time dependent parameter of thisproblem, p(t), does the system show reliability growth (decreasing rate of occurrence offailure) or aging (increasing rate of occurrence of failure)?b) Write the expression for and calculate the number of expected failures of the press during amission time of 5 years, 5,000 hr, m(5,000).c) Write the expression for and calculate the MTTR, meantime to repair. Given s = 0.8,comment on the overall shape or skewness, low skew, high skew, ~ symmetric, of theLognormal model.

a) To determine if the system shows reliability growth or aging, we need to examine the behavior of…

Answered: 6. A die forge press operates an…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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A group of researchers are working to determine the historic sea levels of the body of water. They are attempting to do this by taking samples around the body of water and in a nearby cave and after analyzing sediment cores from around the body of water to those in the cave. The Climatologist that is working in the cave is trying to determine the age and growth rate of stalactites, to get a more accurate picture of the age of the existing stalactites. The following table contains the estimated age (to the nearest thousand) of the sample and the length of the sample in micrometers. Find a linear model that express length as a function of the age. Round your answers to 2 decimal places Age (nearest thousand) Length in thousands of years = Micrometers 7906 9043 10091 10808 11024 11235 11532 76 87 97 104 106 108 111 x+13.6151 o where x is the age
Question 7 The following plots have been obtained for a time series. a) Suggest an appropriate ARIMA model based on the below plots. 120- 90- 60- 30- acf 1980 Jan 0.2- 0.1- 0.0 -0.1- 1990 Jan 12 lag [1M] 18 2000 Jan Month pacf 0.2- 0.1- 0.0 -0.1- 2010 Jan 12 lag [1M] 18 2020 Jan 24 h) The following ARIMA output has been obtained from R. Based on this output
A group of researchers are working to determine the historic sea levels of the body of water. They are attempting to do this by taking samples around the body of water and in a nearby cave and after analyzing sediment cores from around the body of water to those in the cave. The Climatologist that is working in the cave is trying to determine the age and growth rate of stalactites, to get a more accurate picture of the age of the existing stalactites. The following table contains the estimated age (to the nearest hundred) of the sample and the length of the sample in centimeters. Find a linear model that express length as a function of the age. Round your answers to 2 decimal places Age (nearest hundred) Length I+ 6 8 9 10 14 18 20 Centimeters 582.44 776.39 873.22 970.97 1358.68 1746.44 1940.97 where x is the age in hundreds of years
The logarithm of the ratio of the output to the input current of a transistor is called its current gain. If cur-rent gain measurements made on a certain transistor are normally distributed with μ = 1.8 and σ = 0.05, find theprobability that the current gain will exceed the requiredminimum value of 6.0.
The type of battery in Jim's laptop has a lifetime X (in years) which follows a Weibull distribution with parameters α=2 and β=4. The type of battery in Jim's tablet has a lifetime Y (in years) which follows an exponential distribution with parameter λ=1/4.Find E(XY−2Y).(Answer as a decimal number, and round to 2 decimal places).
1. Supercavitation is a propulsion technology for undersea vehicles that can greatly increase their speed. It occurs above approximately 50 meters per second when pressure drops sufficiently to allow the water to dissociate into water vapor, forming a gas bubble behind the vehicle. When the gas bubble completely encloses the vehicle, supercavitation is said to occur. Eight tests were conducted on a scale model of an undersea vehicle in a towing basin with the average observed speed x = 102.2 meters per second. Assume that speed is normally distributed with known standard deviation o =4 meters per second. 1.1. Test the hypothesis H0 : µ=100 versus H1: µ < 100 using a=0.05. 1.2. What is the P-value for the test in part 1.1.? 1.3. Compute the type II error if the true mean speed is as low as 95 meters per second. 1.4. What sample size would be required to detect a true mean speed as low as 95 meters per second if you are willing to accept a type Il error of 0.15?
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Suppose X has a lognormal distribution with parameters mu = 1.5 and sigma = 0.2 . Find the 33rd percentile?
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A Sample size 25 is piaked up at Jandoy om a 00 ith a logean of100 population which is nommally distibuted and vagbnce of 36, caleyate-
Refer to the accompanying data display that results from a sample of airport data speeds in Mbps. Complete parts (a) through (c) below. . TInterval (13.046,22.15) x=17.598 Sx=16.01712719 n=50 a. What is the number of degrees of freedom that should be used for finding the critical value tα/2? df=__ (Type a whole number.) b. Find the critical value tα/2corresponding to a 95% confidence level. tα/2= (Round to two decimal places as needed.) c. Give a brief general description of the number of degrees of freedom. A. The number of degrees of freedom for a collection of sample data is the number of unique, non-repeated sample values. B. The number of degrees of freedom for a collection of sample data is the number of sample values that are determined after certain restrictions have been imposed on all data values. C. The number of degrees of freedom for a collection of sample data is the number of sample values that can vary…

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