Ops/571 Week 5 Paper

Words: 1082
Pages: 5

Statistical Process Control


Over the past five weeks, data has been collected from the process of getting my daughter, Sophie, ready for daycare in the morning. I have tracked six key areas, or steps, in the process: The time it takes to wake her up, The time it takes to get her to go to the bathroom, The time it takes to get her stuff ready, The time it takes to get her dressed, The time it takes to brush her teeth and hair, and The time it takes to get her into the car. In this paper, I will discuss what I have discovered based on this data, I will identify roadblocks to the process and recommend strategies to overcome them, and I will discuss the variables which affect the steps in the process. Finally I will discuss
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The final step in the process of getting her ready is getting her down to the car and secured in her car seat. This step has a mean of 3.79 and a standard deviation of only .88 minutes. Only very rarely does this step take more than three to four minutes, and this is generally due to an outside distraction, such as a cat running by that she has to point out and chase for a moment. The Quality Control Process Chart identifies the center of the sample mean to be 6.49, the upper control limit to be 13.85 and the lower control limit to be -0.88. The mean standard deviation is 2.66 minutes. Although there is a large variance in the time it takes to get Sophie ready in the morning, the chart shows that the mean time is consistently within the upper and lower control limits. Included in the attachment is the Quality Control Process Chart, a histogram for each step identifying trends, and a confidence interval for each step based on a 95% confidence interval. In conclusion, by tracking this data over the past five weeks, I have been able to identify trends in the process of getting Sophie ready for day care in the morning. The data has shown what steps in the process are consistent, with little standard deviation, and what steps vary widely and have a large standard deviation. By analyzing the data, I have been able to identify primary bottlenecks in the process, pinpoint the possible causes of these roadblocks, and make recommendations to