Solving Probability of Process: Sketching Functions & Annual Savings

In summary: The new process has a smaller standard deviation, which means it produces more consistent weights. This means that the mean weight will be closer to the nominal weight of 1.2 grams, resulting in less waste and therefore cost savings. Using the normal distribution tables, we can calculate the probability of a piece of paper being lighter than 1.2 grams for both processes. The closer the mean weight is to 1.2 grams, the smaller the probability will be.In summary, the question asks for the functions that model the current and new paper manufacturing processes, and the annual savings made possible by the new process. The functions can be modeled using normal distribution tables, assuming a normal distribution for both processes. The annual savings will be determined by the
  • #1
zaka
3
0
Hi, I'm trying to solve the following question, but unsure how to approach it.

A paper manufacturing process states (in its specifications) that each piece of paper's weight will be less than the nomial weight of 1.2 grams on NO MORE than 1 occasion in 100. Currently, the process produces to any required mean piece of paper weight with a standard deviation of 0.01 grams. A new process is available which makes to a more consistent weight, the standard deviation of weights being 0.008 grams.

Q1) Sketch the functions that model these 2 cases (current and new process).

Both processes can make 20,000 sheets of paper per minute, and will be required to work for a 40 hour week, 50 weeks a year. The price of paper is around £2 per kilogram.

Q2) Find the annual savings made possible by the new process.


For question one, how are the functions stetched? I thought of using normal distribution tables to work out this question by letting Probability(u < 1.2) = 0.01, however nowhere in the question does it state that the process is normally distributed so I think that's wrong (I have no idea how to approach this question as you can tell).

Any help would be much appriciated.
 
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  • #2
You can assume a normal distribution. This is the usual procedure in problems like this. The trick is to define the mean weight for each of these processes so that for the given standard deviation the probability of light weight is no more than 1%.

The cost saving will be determined by the difference in mean weight between the processes.
 

1. What is the purpose of solving probability of process when sketching functions?

The purpose of solving probability of process when sketching functions is to determine the likelihood of a specific outcome occurring based on a set of known variables. This helps in understanding the behavior and patterns of the process being studied.

2. How is annual savings related to solving probability of process?

Annual savings can be calculated using probability of process when sketching functions to determine the expected outcome and potential risks associated with a particular process. This can help in making informed decisions to optimize savings.

3. What are the key steps involved in solving probability of process for sketching functions?

The key steps involved in solving probability of process for sketching functions include identifying the variables and their probabilities, constructing a probability distribution, calculating the expected value and variance, and interpreting the results to make informed decisions.

4. What are some common tools used for solving probability of process when sketching functions?

Some common tools used for solving probability of process when sketching functions include mathematical formulas, statistical software, and data visualization techniques such as histograms and scatter plots.

5. How can solving probability of process benefit scientific research and experiments?

Solving probability of process can benefit scientific research and experiments by providing a quantitative understanding of the likelihood of outcomes and potential risks involved. This can help in designing more effective experiments and making data-driven conclusions.

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