Ops 561- Week 5
Process Improvement Plan
OPS 571
April 22, 2013
Richard Franchetti, Facilitator
Process Improvement Plan
In week one of this class, I was tasked to design a flowchart for a process in my daily life that I can improve. I chose my morning routine before work. My goal is to get out of the house by 7:38am Monday-Friday in order to catch my bus for work at 7:41am. I have trouble keeping track of time, usually missing the bus about one time every two weeks. I have discovered through the flowchart in week one, that my entire process has serious flaws. All of the bottlenecks were identified and improved upon as necessary. After collecting data over the past four weeks, I see changes in the process, using time as the metric. This paper will display the data that has been collected, as well as the calculations for the control limits, discuss the effect of the seasonal factors, and discuss the confidence intervals and their usefulness.
Control Limits Control limits are an easy way to find out if something is statistically wrong with a process. There are upper and lower control limits for every process. If the data in the sample falls outside of either of the two limits, this usually means that there is a problem with the process. Control limits help to assure quality ("Ehow: How To Calculate Upper And Lower Control Limits", 2013). If for some reason, any data points were to fall outside of the control limits, we could use statistical process control to analyze the procedures that are used and make improvements as necessary. In order to calculate my control limits, I had to first collect data for each workday in weeks 1-4. Table 1 (see below) shows all of the data that was collected in the past four weeks.
Table 1: Data Collected (in mins.)
| |Week 1 |Week 2 |Week 3 |Week 4 |
|Monday |70 |70
OPS 571
April 22, 2013
Richard Franchetti, Facilitator
Process Improvement Plan
In week one of this class, I was tasked to design a flowchart for a process in my daily life that I can improve. I chose my morning routine before work. My goal is to get out of the house by 7:38am Monday-Friday in order to catch my bus for work at 7:41am. I have trouble keeping track of time, usually missing the bus about one time every two weeks. I have discovered through the flowchart in week one, that my entire process has serious flaws. All of the bottlenecks were identified and improved upon as necessary. After collecting data over the past four weeks, I see changes in the process, using time as the metric. This paper will display the data that has been collected, as well as the calculations for the control limits, discuss the effect of the seasonal factors, and discuss the confidence intervals and their usefulness.
Control Limits Control limits are an easy way to find out if something is statistically wrong with a process. There are upper and lower control limits for every process. If the data in the sample falls outside of either of the two limits, this usually means that there is a problem with the process. Control limits help to assure quality ("Ehow: How To Calculate Upper And Lower Control Limits", 2013). If for some reason, any data points were to fall outside of the control limits, we could use statistical process control to analyze the procedures that are used and make improvements as necessary. In order to calculate my control limits, I had to first collect data for each workday in weeks 1-4. Table 1 (see below) shows all of the data that was collected in the past four weeks.
Table 1: Data Collected (in mins.)
| |Week 1 |Week 2 |Week 3 |Week 4 |
|Monday |70 |70