Question

The production manager at Sunny Soda, Inc. is interested in tracking the quality of the company's 12- oz bottle filling line. The manager collected 15 samples of 4 bottles each and calculated the overall mean filling was 12.001 oz and the overall range was 0.1267 oz. data. I have performed the calculations for the X-double bar and R-bar to save you time. See problem 24 at the end of the chapter.) (This is based on raw sample Step 1: Estimating the distribution 1. What is being measured to monitor the process? Is it an attribute measure? Or variable measure? What is the historical distribution of the process output? (That is, what are the distribution values?) 2. 3. What control chart(s) that should be used for these measures?

Answer 1

The student's question involves using variable measures like the filling volume of 12-oz soda bottles and applies quality control charts (№-bar and R-bar) to monitor and manage the production process.

Step-by-step explanation:

The student's question relates to the monitoring of a production process using quality control charts. The process being measured is the filling of 12-oz bottles with soda, which is a variable measure since it refers to quantities like volume that are measurable and can vary continuously. The historical distribution of the process output, in this case, would typically be assumed to follow a normal distribution, as it's a common assumption for processes like bottle filling controlled by many random variables.

To monitor the quality of the filling line, two common types of control charts are used, the №-bar chart and the R-bar chart. The №-bar chart is used to monitor the process mean, and the R-bar chart is used to monitor the variability of the process. Together, these charts help ensure that the bottle filling process remains consistent and within specified limits.