Ops-571 Assignment

1162 Words Jan 21st, 2011 5 Pages

Process Improvement Plan
University of Phoenix
OPS/571 – Operations Management

Process Improvement Plan Successful organizations continuously strive to improve the processes they have in place. Process improvement leads to better quality control, higher efficiencies and lower costs. In order to implement a process improvement plan, it is necessary to collect and analyze data from the process. In this paper, I present an analysis of the metric data collected for the process I identified during week #1. As part of the analysis, the control and confidence limits are calculated, as well as other relevant statistics. With this information, a process improvement
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It is possible that traffic in my route is lighter earlier in the week and that it turns a lot heavier towards the end of the week. Friday in particular seems to be a day in which the average driving time is a lot longer than, say, Wednesday. This seasonality pattern is the reason which both Wednesday and Friday appeared to be out of control. In an actual real-world corporate problem, say, if production in a plant were being analyzed, any instances in which the process goes out of control would have to be studied and necessary measures implemented to ensure the process is within its control limits at all times (Chase, Jacobs, & Aquilano, 2006).

Confidence intervals A confidence interval is the range of values where the population parameter falls with a specified probability; this probability is referred to as level of confidence (Lind, Marchal, & Wathen, 2010.) For the process under consideration, the parameter of interest is the mean driving time. Given the inherent variability of traffic conditions in urban areas, it is appropriate to find the confidence interval with a 90% level of confidence.
There are only 25 numbers in the sample collected. For purposes of analysis, it will be considered that the process itself is normally distributed, and its standard deviation is unknown. Under these conditions, the formula that gives the confidence interval is:

where n is the sample size, t is the t-student value for the respective level of

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