Asked by Grace Mackosso on Apr 24, 2024

A quality analyst wants to construct a sample mean chart for controlling a packaging process. He knows from past experience that when the process is operating as intended, packaging weight is normally distributed with a mean of twenty ounces, and a process standard deviation of two ounces. Each day last week, he randomly selected four packages and weighed each. The data from that activity appears below.  Weight  Day  Package 1 Package 2 Package 3  Package 4  Monday 23222324 Tuesday 23211921 Wednesday 20192021 Thursday 18192019 Friday 18202220\begin{array} { | l | l | l | l | l | } \hline & { \text { Weight } } \\\hline \text { Day } & \text { Package } 1 & \text { Package } 2 & \text { Package 3 } & \text { Package 4 } \\\hline \text { Monday } & 23 & 22 & 23 & 24 \\\hline \text { Tuesday } & 23 & 21 & 19 & 21 \\\hline \text { Wednesday } & 20 & 19 & 20 & 21 \\\hline \text { Thursday } & 18 & 19 & 20 & 19 \\\hline \text { Friday } & 18 & 20 & 22 & 20 \\\hline\end{array} Day  Monday  Tuesday  Wednesday  Thursday  Friday  Weight  Package 12323201818 Package 22221191920 Package 3 2319202022 Package 4 2421211920 (a) If he sets an upper control limit of 21 and a lower control limit of 19 around the target value of twenty ounces, what is the probability of concluding that this process is out of control when it is actually in control?
(b) With the UCL and LCL of part a, what do you conclude about this process-is it in control?

Sample Mean Chart

A type of control chart used to monitor the central tendency of a process over time by plotting the mean of each sample drawn from the process.

Upper Control Limit

The Upper Control Limit is the highest value on a control chart that a process variable is expected to go, indicating a point beyond which the process is considered out of control.

Lower Control Limit

The threshold below which the process output is considered to be statistically out of control in a control chart.

  • Understand the fundamentals of statistical process control (SPC) and its importance in quality control.
  • Calculate and interpret control limits and process capabilities in different control chart types (e.g., X-bar, R-chart, p-chart, and c-chart).
  • Analyze sample data to determine if a process is in statistical control.