Quality Control Charts: Scharadin Hotels

Quality Control Charts: Scharadin Hotels
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Quality Control Charts: Scharadin Hotels
Introduction
Continuous quality improvement of systems calls for understanding and measuring of process variation because such an understanding enables practitioners to eliminate extraneous processes. It is notable that the statistical process control enables practitioners to identify areas that are deteriorating in quality or areas that have improved. Crucial to the discussion is the fact that statistical control process uses control charts to monitor the aforementioned variations. What is a control chart? The term control chart could be elucidated as an ordered time series plot of important variables (Omar, 2010). The charts use statistics such as proportions, averages, upper and lower confidence intervals, or rates to produce plots that later define the variation of processes. Examples of such charts include the Xbar chart, Rchart, c-chart, and the P chart. In fact, the charts could be used to solve the problem of defective bills at Scharadin Hotels. It follows that this paper discusses the charts mentioned above and applies the concept to solve the problem at Scharadin Hotels.
Explain the differences between x-bar and R-charts. How can they be used together and why would it be important to use them together?
Quality control uses different charts to examine the variation of different processes. For example, Xbar and Rcharts are types of control charts used for monitoring data variables that have been collected over time. It is critical that even though the two charts may appear to be similar, they are different because they are created differently. As evidence, an Xbar chart plots the mean against the time while an Rchart plots the range against time. It is also advisable to use Xbar and Rcharts together because combining the two charts enables an analyst to determine if a process is stable and predictable. It is because Xbar charts will help the analyst in establishing the stability of a process while Rcharts will help the analyst in establishing whether the process is predictable. According to Oakland (2012), the two charts are used when assessing stability, when the data is collected in subgroups, when the data is time-ordered, and when the data is in variable form.
Explain the use of p-charts and c-charts. When would you use one rather than the other? Give examples of measurements for both p-charts and c-charts.
It is vital to highlight that p-charts and c-charts are also used for quality control to assess the variation of different processes. It follows that understanding the meaning of the two charts is essential because it lays a foundation for the upcoming discussion. A c-chart could be elucidated as an attributes control chart, which is used when data is collected in subgroups of the same size. Therefore, c-charts illustrate how a process measured in terms of the number of defects for every group varies with time. In this case, the term defect is used for any misplaced characteristic that is present or an omitted characteristic that is absent. On the contrary, p-charts show the proportion of defects instead of showing the actual counts of defects. However, like c-charts, p-charts measure the proportion of defects according to time (Oakland, 2012).
It is evident that even though both p-charts and c-charts measure variations over time, the two charts cannot be used under similar conditions because of differences between them. For instance, while p-charts are used for subgroups with varying sizes, c-charts must be used for subgroups with constant sizes. In addition, p charts inspect data, which is in the form of, "pass or fail" and "yes or no" while c-charts inspects data that can take on numerical values. In short, p-charts are used for binary data while c-charts are used for discrete data (Wheeler and Chambers, 2010). It follows that p-charts are used for binary data with varying sample sizes while c-charts are used for discrete data with constant sample sizes.
Set up three-sigma control limits with the given data
Considering the traits of the control charts mentioned above, it sufficed to conclude that a c-chart is appropriate for testing whether the system is in control or not. It is because the bills are takes on values between one and six, which implies that the type of dat...