Process_Control

Statistical Process Control A process that is performed on a daily basis which was used for a process design was preparing for work in the morning. There are different factors that affected this process design. Time and the tasks which are being performed play the key roles in determining what and how to improve this process design. The task in this process included waking up, taking a shower and essential restroom duties, ironing clothes to wear for work, cooking breakfast, getting dressed, and leaving for work. In this process design which was being evaluated, time was calculated in minutes. The operation viewed was the amount of time it took to get out of the bed and leave home for work. Multiple tasks contributed to the amount of time spent from the first process to the final process. The following charts were used to compare the initial process and time it took to leave home for work and the time it took to leave home for work after the process was calculated and changed. Data Collected Initial Process Days Of The Week The time it took to leave the house after getting out of bed. (Minutes) Monday 58 Tuesday 54 Wednesday 60 Thursday 50 Friday 50 Changed Process Days Of The Week The time it took to leave the house after getting out of bed. (Minutes) Monday 45 Tuesday 35 Wednesday 30 Thursday 30 Friday 30 In the first chart all the numbers represent the original everyday process and amount of time it took and in the second chart the numbers reflect the time it took after a process of elimination. When eliminating some elements or task that caused a bottleneck or were time consuming and could be rearranged, there was a positive affect on the process design. The minutes it took in the initial process decreased. Statistical process control is important in a process design because it can show the characteristics from a certain behavior, operation, or task over a period of time. Not only this but it shows the influence of different variables on the characteristic, where the location of the process is, how much variation is in the process at the time, and allows one to get the process under control or in a state of control. When establishing control limits means and ranges are calculated. The mean or average for the initial process was 54.4 minutes. This was determined by adding up all the minutes for each day of the week and dividing them by the number of days used which was 5. The mean or average for the changed process was 34 minutes. The same process was used to determine the mean or average in the changed process as was used to determine the mean or average in the first process. The range for this process design is 20.4. This data was determined by calculating the mean for both processes and subtracting the smallest measurement from the largest measurement. This calculation also shows the difference in the amount of time from the initial process and the changed process. The mean can be used to show a measurement of where the process is located and the range can be used to determine how much variation is in the process. When this process is completed, a control chart can by used to show how a process is performing over a period of time. The points would fall above or below a center line on the chart which would be the overall mean as shown by the calculations above. There should not be any points that fall outside the upper and lower control limits or this would be an abnormal pattern. Seasonal factors can affect the process performance data as well. Seasonal factors can be referred to as weather changes, items that are used seasonally such as long sleeves or items used in the summer versus items that will be used in the spring and fall. In the particular process design time change would be the seasonal factor that would affect the process performance data. There is a seasonal time change of each year. Depending upon the adjustment to the time change one may spend less time preparing for work or more time based on clock settings. When time goes back a hour one is forced to wake up earlier but might not be able to make the adjustment promptly and needs more time to sleep and adjust over a period of time. Just as if the time goes up one hour one might get up earlier depending on the individual. When the confidence interval is computed, the mean is computed in order to estimate the mean of the population. In the data above, the mean is already calculated. If one wanted to know the confidence interval shown in a bell shaped chart he she would need to know the standard deviation. This can be found for instance if one uses a normal distribution of 2.5 standard deviation and computed 95% confidence interval, one must compute the mean and standard error first. This can be done by taking 2.5 and dividing it by the square root of the mean which is the average calculated previously. One can find .95 by using a normal distribution calculator. The middle shaded area will represent the .95 and a normal distribution. The standard error would be multiplied by 1.96. Therefore, upper and lower control limits would be the mean plus or minus 1.96 times the standard error. This can be very useful because it can by used to determine how reliable this process or method is which is being used. References Chase, R. B., Jacobs, F. R., & Aquilano, N. J. (2006) Operations management for competitive advantage (11th ed.). New York: McGraw Hill/Irwin. Slide Share (2009) Basic Statistical Process Control Retrieved on April 28, 2010 from http://www.slideshare.net/newsearch/slideshow'q=basic+staticical+process&searchfrom=header