Employees tend to stay late at office at the final week of the month mostly because of the need to complete monthly closing reports. Amount of cars reduces as the weeks run in a monthly cycle. Total cycle time needs to be as less and independent as possible. Cycle time that easily reacts under any influences will make decisions harder to conclude as observations are not consistent. Seasonal factor is the adjustable correctional value in a given time series of the season of the year. The table below records the seasonal factor that adjusts the next month’s cycle time to 300 minutes comparing to the current 347.14 minutes. Week (mins) | Past Cycle Time (mins) | Average Cycle Time for each Week (mins) | Seasonal Factor | Expected Cycle Time (mins) | Average Cycle Time for each Week (mins) | Next Month 's Seasonal Forecast …show more content…
2). 95% is set as the confidence level for the above data. The sample size is below 15 and the chart below depicts the distribution of average mean for the five weeks being normal (University of Phoenix, 2010, Estimation and Confidence Intervals, p. 305). The distribution scale put to use is the t-distribution satisfying the above conditions. The interval that encloses the true population parameter in a 95% confidence level base on the current data is from 61.98% to 79.57%. Conclusion The process undergoing the plan records a nearly stable result from the (SPC) within the control limits, producing seasonal factors for next month forecast and nearly a high confidence interval for its confidence level. The process is still open for modifications as the plan has point out areas for improvements. The SPC pattern’s requires the data to be graphically stable, the average mean are not to be heavily leaning against the seasonal factors and the confidence interval must increase so that the quickest cycle time is