Ops free essay sample

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. We will write a custom essay sample on Ops or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page 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 |65 |65 | |Tuesday |71 |70 |65 62 | |Wednesday |70 |64 |65 |65 | |Thursday |68 |60 |66 |60 | |Friday |70 |69 |70 |59 | |Weekly Total |349 |333 |331 |311 | |(in mins. | | | | | |Weekly Average |69. 8 |66. 6 |66. 2 |62. 2 | |(in mins. ) | | | | | Another important concept in statistical process control is standard deviation. Standard deviation helps us figure out how much variation from the average is present in a sample. In my particular example, each week varied with how quickly I got dressed and out of the house to make my bus. My mornings are usually very standard and routine. The time variation in my data comes from how much I prepare the night before, as well as how long I decide to shower in the morning. The standard deviation is necessary is order to calculate the upper and lower control limits. The control limits simply state that as long as the process is within three standard deviations of the average (either way), than the process is still at acceptable quality. My specific control limits were calculated as follows: [pic] pic] [pic] [pic] [pic] The first four tables are the weekly breakdown of all of the data that was collected throughout the last four weeks. The final table calculates the upper and lower control limits for the entire sample. Since I wake up every day at 6:30am and must leave the house by 7:40am, I have 70 minutes total to complete all of my tasks in the morning. According to my calculations on the final table, I need to leave the house anywhere between 7:34am and 7:39am. Doing so means that I have made my bus and my process has been a success for the day. Seasonal Factors Seasonal factors are defined as â€Å"the amount of correction needed in a time series to adjust for the season of the year† (Chase, Jacobs, Aquilano, 2006, Chapter 13). The word seasonal does not always mean weather. Seasonal in business terms is usually classified as an activity of some sort. In my situation, I don’t have any seasonal factors that can affect my morning routine. My husband has already left the house and I am alone in a stable environment (my home). Confidence Intervals Confidence intervals allow us to pinpoint data to a degree of confidence. The intervals are used to estimate the reliability of an estimate. Usually, the confidence levels that are calculated are 90%, 95%, and 99%. The confidence intervals for my particular situation are as follows: |Confidence Intervals |Lower Confidence Interval (mins. ) |Upper Confidence Interval (mins. ) | |90% |63. 989 |68. 411 | |95% |63. 023 |69. 77 | |99% |52. 41 |79. 999 | In other words, I am 90% confident that my morning routine will take between 64-68 minutes, 95% confident that my morning routine will take between 63-69 minutes, and I am 99% confident that my morning routine will take between 52-80 minutes. Conclusion After spending the last 5 weeks revising my entire morning routine, I believe that I have found a process that will help me better meet my goal of ot missing the bus before work. I put controls in place to set expectations for my process. Organizations can use controls the same way. Statistical process control helps managers ensure quality. They can analyze and improve any processes that are not living up to the expectation. Appendix A: Getting Ready in the Morning (Initial Flowchart) Appendix B: Getting Ready in the Morning (Final Flowchart) Reference Chase, R. B. , Jacobs, F. R. , Aquilano, N. J. (2006). Operations Management for Competitive Advantage (11th ed. ). Retrieved from https://ecampus. hoenix. edu/content/eBookLibrary2/content/eReader. aspx. eHow: How to Calculate Upper and Lower Control Limits. (2013). Retrieved from http://www. ehow. com/how_4963222_calculate-upper-lower-control-limits. html Get up No Yes Leave the house Eat Cook/Prepare Breakfast Leave the house Breakfast No Yes Hit Snooze button Grooming, brush teeth, shower, etc. Alarm goes off Leave the house Eat Cook/Prepare Breakfast Leave the house Breakfast? No Yes Get dressed Comb/brush hair Shower and brush teeth Get up Alarm goes off