A manufacturing engineer is studying the dimensional variability of a particular component that isproduced on three machines. Each machine has two spindles, and four components are randomlyselected from each spindle. The results follow. Analyze the data, assuming that machines and spindlesare fixed factors.Machine 1Machine 2Machine 3Spindle11112814121416991510101511101311121512814131114Calculate the Determination Coefficient (as percentage) for the Model obtained. Use 2 decimal DigitsRespuesta:2.

Find the Given details below: Given details: Machine 1 Machine 2 Machine 3 Spindle 1 2 1 2…

Answered: A manufacturing engineer is studying…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter14: Data Mining

Section14.2: Classification Methods

Problem 3P

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Find Values of n and cHi-Tech Industries manufactures Z-Band radar scanners used to detect speed traps. The printed circuit boards in the scanners are purchased from an outside vendor. The vendor produces the boards to an AQL of 2 percent defectives and is willing to run a 5 percent risk (α) of having lots of this level or fewer defectives rejected. Hi-Tech considers lots of 8 percent ormore defectives (LTPD) unacceptable and wants to ensure that it will accept such poor quality lots no more than 10 percent of the time (β). A large shipment has just been delivered. What values of n and c should be selected to determine the quality of this lot?
The time to deliver packaged containers by a logistics company is found fromsamples of size 4. The mean and standard deviation of delivery times is estimated tobe 140 hours and 6 hours, respectively.(a) Find the 2 sigma and 3 sigma control limits for the average delivery time.(b) Explain a type I and type II error specifically in this context.(c) If the mean delivery time shifts to 145 hours, what is the probability of notdetecting this by the second sample after the shift?(d) What is the ARL? Explain
Z Pr(Z) 0.38 65 0.50 69 0.67 75 0.84 80 1.04 85 1.28 90 1.41 92 1.56 94 1.65 95 1.75 96 2.06 98 2.33 99 Barbara Flynn is in charge of maintaining hospital supplies at General Hospital. During the past year, the mean lead time demand for bandage BX-5 was 60 (and was normally distributed). Furthermore, the standard deviation for BX-5 was 6. Ms. Flynn would like to maintain a 90% service level. a) What safety stock level do you recommend for BX-5? Safety stock = units (round your response to the nearest whole number).
.A 45 kW rated solar power system has its power output and the Solar irradiance on the PV system measured during daylight hours over a day. Based on the following data, create a scatter plot of the power output of the PV system vs the solar irradiance and comment on the relationship between the two. Based on the data, can you tell which season this day was in? Solar Irradiance on the PV system (kW/m²) 0 0.079 0.333 0.571 0.751 0.86 0.914 0.93 0.904 0.803 0.606 0.345 0.054 Power output from the PV system (kW) 0 3.098 12.438 20.124 25.703 28.498 29.587 29.69 28.798 26.264 20.434 12.223 2
4. ABC Dog Food Company located in Ottawa sells large bags of dog food to warehouse clubs. ABC uses an automatic filling process to fill the bags. Weights of the filled bags are approximately normally distributed with a mean of 50 kilograms and a standard deviation of 1.25 kilograms. (a) What is the probability that a filled bag will weigh less than 49.5 kilograms? (b) What is the probability that a randomly sampled filled bag will weigh between 48.5 and 51 kilograms? (c) What is the minimum weight a bag of dog food could be and remain in the top 15% of all bags filled? (d) ABC is unable to adjust the mean of the filling process. However, it is able to adjust the standard deviation of the filling process. What would the standard deviation need to be so that 2% of all filled bags weigh more than 52 kilograms?
For the next 6 numbers: Refer to the Management Scientist output of a maximization LP problem. The constraints are defined as follows: Constraint 1: advertising budget ( ) Constraint 2: sales force availability ( ) Constraint 3: production level (=) Constraint 4: retail stores requirement ( ) Optimal Solution Objective Function Value - Variable. Constraint X1 X2 X1 X2 X3 X4 X3 X4 1 2 Variable 1 2 3 3 4 OBJECTIVE COEFFICIENT RANGES 4 Constraint RIGHT HAND SIDE RANGES Value Slack/Surplus Lover Limit 25.000 425.000 150.000 0.000 84.000 50.000 No Lover Linit No Lover Linit Lover Limit 48450.000 0.000 25.000 0.000 0.000 4950.000 1775.000 515.000 0.000 Reduced Costs Dual Prices Current Value 90.000 84.000 70.000 60.000 Current Value 0.000 0.000 0.000 45.000 5000.000 1800.000 600.000 150.000 3.000 0.000 60.000 -17.000 Upper Limit No Upper Linit 90.000 87.000 105.000 Upper Linit 5850.000 No Upper Limit 603.571 200.000
Nocaf Drinks, Inc., a producer of decaffeinated coffee, bottles Nocaf. Each bottle should have a net weight of 4 ounces. The machine that fills the bottles with coffee is new, and the operations manager wants to make sure that it is properly adjusted. The operations manager takes a sample of n = 8 bottles and records the average and range in ounces for each sample. The data for several samples are given in the following table. Note that every sample consists of 8 bottles. SAMPLE SAMPLE SAMPLE SAMPLE SAMPLE RANGE AVERAGE SAMPLE RANGE AVERAGE 0.41 4.00 E 0.56 4.17 B 0.55 4.16 F 0.62 3.93 0.44 3.99 0.54 3.98 0.48 4.00 H 0.44 4.01 Is the machine properly adjusted and in control?
Nocaf Drinks, Inc., a producer of decaffeinated coffee, bottles Nocaf. Each bottle should have a net weight of 4 ounces. The machine that fills the bottles with coffee is new, and the operations manager wants to make sure that it is properly adjusted. The operations manager takes a sample of n = 8 bottles and records the average and range in ounces for each sample. The data for several samples are given in the following table. Note that every sample consists of 8 bottles. SAMPLE SAMPLE SAMPLE RANGE SAMPLE SAMPLE RANGE AVERAGE SAMPLE AVERAGE 0.41 4.00 E 0.56 4.17 B 0.55 4.16 F 0.62 3.93 C 0.44 3.99 0.54 3.98 0.48 4.00 H 0.44 4.01 Is the machine properly adjusted and in control?
The mean annual earning for U.S. workers with advanced degrees is $80,977 with a standard deviation of $100,895; the distribution is highly right-skewed. Use this information to answer questions 7 to 10 below. A random sample of n = 86 workers is drawn, and their annual earnings recorded. What is the expected value of the sample mean of their annual earnings? What is the standard deviation of the sample mean of their annual earnings? what is the probability that the sample mean is at least $100,000? The actual sample mean earnings for the random sample of 86 workers with advanced degrees was $82,105. What is the sampling error?
Given a normal distribution with μ= 105 and σ = 20, and given you select a sample of n = 16, complete parts (a) through (d). a. What is the probability that X is less than 92? P(X<92) 0.0047 (Type an integer or decimal rounded to four decimal places as needed.) b. What is the probability that X is between 92 and 93.5? P(92 X 93.5)= 0.0061 (Type an integer or decimal rounded to four decimal places as needed.) c. What is the probability that X is above 105.2? P(X 105.2)= 0.4840 (Type an integer or decimal rounded to four decimal places as needed.) d. There is a 67% chance that X is above what value? X = (Type an integer or decimal rounded to two decimal places as needed.)
The controller for McGarvey Manufacturing Company felt that the number of purchase orders alone did not explain the monthly purchasing cost. He knew that nonstandard orders (for example, one requiring an overseas supplier) took more time and effort. He collected data on the number of nonstandard orders for the past 12 months and added that information to the data on purchasing cost and total number of purchase orders. Month January February March May July August September October November December Purchasing Cost Intercept X variable 1 X variable 2 Required: $19,250 18,050 18,200 18,050 19,345 19,500 19,670 20,940 19,430 20,020 18,800 19,340 Number of Purchase Orders 370 330 320 410 400 450 460 560 440 600 470 480 Number of Nonstandard Orders 61 40 35 73 55 30 80 51 75 12 27 Multiple regression was run on the above data; the coefficients shown by the regression program are: 14,530 (rounded to the nearest dollar) 6.30 (rounded to the nearest cent) 16.8 (rounded to the nearest cent) 1.…
Two processes are used to produce forgings used in an aircraft wing assembly. Of 200 forgings selected from process 1.12 do not conform to the strength specifications. Where as of 300 forgings selected from process. 2.6 are nonconforming. Test the hypothesis that the two processes have identical fractions nonconforming.Use a=0.05, and explain the result

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