being down and billing was behind for more than four days, causing theperformance to be above acceptable values during that time period.When all systems are running normal and no variances are occurring, allprocesses should be within the limits of the statistical control chart.
Reference:Krajewski, L. J., Malhotra, M. K., & Ritzman, L. P. (2015). OperationsManagement: Processes and Supply Chains (11 ed.). Boston, MA: Pearson.Thread:Q1 Control ChartsPost:RE: Q1 Control ChartsAuthor:Posted Date:January 5, 2016 11:37 AMStatus:PublishedJana,Well explained, thank you.You mentioned that if "5 or more observations are above or below the pbar ornominal value, it should be evaluated and remedial action should be taken". Doyou think that should be true regardless of the number of your observations?Let's say you have 2 cases: one with 10 samples and one with 1,000,000samples. Would the number of samples matter? Would the time of theoccurrence matter (for example, if we see some suspicious activitysporadic throughout the day, versus in one particular shift)? Why, or why not?Also, let's say we are evaluating the number of errors, and let's say 50% of oursamples fall below the lower limit. Should we be concerned?Class, anyone should feel free to answer these questions and explain yourrationale.Thank you,Professor SavicIvana Savic