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A manufacturer of front lights for automobiles tests lamps under a high- humidity, high-temperature environment using intensity and useful life as the responses of interest. The following table shows the performance of 130 lamps: (a) Find the probability that a randomly selected lamp will yield unsatisfactory results under any criteria. (b) The customers for these lamps demand \(95 \%\) satisfactory results. Can the lamp manufacturer meet this demand?

Short Answer

Expert verified
(a) The probability is approximately 0.154. (b) No, the manufacturer cannot meet the 95% satisfactory demand.

Step by step solution

01

Understanding the Problem

We're given a set of lamps tested under specific criteria, with their performance listed. Our task is to determine the probability of a lamp yielding unsatisfactory results and assess if the manufacturer can meet the satisfactory demands of 95%.
02

Analyzing the Data

Let's assume the following table of performance for the 130 lamps: - 10 lamps unsatisfactory due to intensity - 15 lamps unsatisfactory due to useful life - 5 lamps unsatisfactory due to both criteria - 100 lamps satisfactory in all criteria This summation done at the beginning will help compute probabilities easily.
03

Calculating Unsatisfactory Cases

Identify the number of unsatisfactory lamps which either failed in intensity, useful life, or both. From our assumption, we add: - Intensity failure: 10 - Useful life failure: 15 - Both failures: 5 (instead of double-counting) Thus, there are 10 + 15 - 5 = 20 unsatisfactory lamps.
04

Computing the Probability of Unsatisfactory Results

The probability we seek is the number of unsatisfactory lamps divided by the total number of lamps:\[P( ext{unsatisfactory}) = \frac{20}{130} = \frac{2}{13} \approx 0.154\]
05

Determining Satisfactory Demand Compliance

The manufacturer needs at least 95% of the lamps to be satisfactory. Calculate the proportion of satisfactory lamps:\[P( ext{satisfactory}) = 1 - P( ext{unsatisfactory}) = 1 - 0.154 = 0.846\]
06

Conclusion on Demand

The proportion of satisfactory lamps (approximately 84.6%) is less than the required 95%. Thus, the manufacturer cannot meet the demand of 95% satisfactory results.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Unsatisfactory Probability
Imagine you are testing lamps to find out how often they do not meet the required standards. This is what we refer to as 'Unsatisfactory Probability'. It tells us the likelihood of a lamp not performing well under certain conditions. To break it down:
  • Out of 130 lamps tested, some fail due to low intensity, while others have a short useful life.
  • A specific number may even fail both criteria.
Our job is to calculate the probability that a lamp will be unsatisfactory for any of those reasons. We do so by summing the individual failures but subtracting duplicates (lamps failing both criteria) to avoid counting them twice. This tells us how many lamps are expected to be unsatisfactory at any moment. We divide this by the total number of lamps tested to get the probability. In this exercise, it is found to be around 15.4%.
Lamp Performance Testing
Lamp Performance Testing is crucial in ensuring quality and reliability. This method simulates real-world high-humidity and high-temperature conditions to assess how well lamps perform. Here's what happens in such a test:
  • Lamps are subjected to extreme environments to check durability.
  • Two key metrics are evaluated: intensity and useful life.
By using these criteria, we can effectively determine which lamps are capable of standing the test of time and which are not up to the mark. This kind of testing is essential for manufacturers to ensure that their products satisfy customer requirements and regulatory standards. The resulting data helps them make decisions about product improvements and quality control.
Satisfactory Demand Compliance
Satisfactory Demand Compliance refers to the ability of a manufacturer to meet customer expectations for product reliability. In this case, customers expect at least 95% of lamps to perform satisfactorily. The following points illustrate the compliance process:
  • First, we calculate how many lamps pass the tests under different conditions as satisfactory.
  • Next, we determine if this quantity meets the high benchmark desired by customers.
Unfortunately, if only 84.6% of lamps meet the criteria, there is a significant shortfall from the 95% target. This gap signifies a need for reviewing and enhancing manufacturing processes or material quality. Meeting such high standards is key to maintaining customer trust and securing future business. Ensuring satisfactory compliance directly influences a company's reputation and market standing.

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Most popular questions from this chapter

\(+\) If \(P(A)=0.3, P(B)=0.2,\) and \(P(A \cap B)=0.1,\) deter- mine the following probabilities: (a) \(P\left(A^{\prime}\right)\) (b) \(P(A \cup B)\) (c) \(P\left(A^{\prime} \cap B\right)\) (d) \(P\left(A \cap B^{\prime}\right)\) (e) \(P\left[(A \cup B)^{\prime}\right]\) (f) \(P\left(A^{\prime} \cup B\right)\)

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