The control charts are built around a specific product parameter that requires monitoring because of its impact on the over-all quality of the product. The next step is to establish a set of control variables including an average (X) and a range (R). These can be ascertained using the data in week one and calculating the X ( in this case it is 54. 2) and R (55-53=2) for the data. Then we can calculate an Upper Control Limit (UCL) and a Lower Control Limit (LCL). UCL = X + R ( 54. 2 + 2) =56. 2 LCL = X-R (54. 2-2)=52. 2

These Control limits are used to detect signals in process data that indicate that a process is not in control. Hence the time taken can vary from 52. 2 minutes to 56. 2 minutes. This helps in identifying trends. Also it shows the data taken on Friday (53) is indicating a strong trend towards the LCL. Seasonal Factors There are some seasonal factors that can affect the time taken in getting ready. For instance, the time taken on Friday is least because the person might be in a hurry to go to office and spend the weekend

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with the family. Similarly the time taken on Monday is highest may be due to Monday morning blues.

Seasonal factors can affect the drying cycle also. Confidence Interval Confidence Interval is an interval estimate of population parameter. Instead of estimating our process in minutes on a particular day, we have taken the interval (Week) and we can then check on collecting the data for a different interval (Week two). But if we are considering the usefulness of Confidence Interval in forecasting, we might not get the satisfactory results. It is common to attach a confidence band (that is, statistical control limits) to the regression line to reduce the unexplained error.

But when use the regression line as a forecasting device by projecting it into the future, the error may not be correctly defined by the projected confidence band. This is because the Confidence Interval is based on past data; it may not hold for projected data points and therefore cannot be used with the same Confidence (Chase? Jacobs? Aquilano:, 2005) Conclusion The design of the flowchart and depicting the data clearly through control chart helps in improving the performance (in this case reduce the time taken to get ready).

The sole objective of this process control plan was to measure the process and suggest the improvement plan. We can reduce the time taken to get ready and leave for work by rearranging the tasks in such a way that the overall operation can be completed in least time. It is essential to find which task is taking more time and could be eliminated and what the bottlenecks of this process design are. Bottlenecks are resources whose capacity is less than the demand placed upon it that may occur in manufacturing processes with machines, labor, or specialized tools. (Chase-Jacobs-Aquilano:, 2005).

Improving the performance of the bottleneck is the best way to improve the performance of the process. The review time can be curtailed by approximately 5 minutes in order to reduce the total time. Also we can check if the dryer needed some repair and hence the drying time can be reduced and eating time can be clubbed with review time. In other words, review of to do list can be performed while eating the breakfast. If we rearrange the drying time, eating time and reviewing time, we can bring a positive affect on the process design. References Chase? Jacobs? Aquilano:. (2005). Operations Management for Competitve Advantage.

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