Artificial Intelligence and Control Charts: A Big Problem

We use the data of some published papers to compare those authors findings with ours. From the analysis we get different results: the cause is that they use the Probability Limits of the PI (Probability Interval) as they were the Confidence Limits (Control Limits of the Control Charts, CCs). The Control Limits in the Shewhart CCs are based on the Normal Distribution (Central Limit Theorem, CLT) and are not valid for non-normal distributed data: consequently, the decisions about the “In Control” (IC) and “Out Of Control” (OOC) states of the process are wrong. The Control Limits of the CCs are wrongly computed, due to unsound knowledge of the fundamental concept of Confidence Interval. Minitab and other software e (e.g. JMP, SAS) use the “T Charts”, claimed to be a good method for deal-ing with “rare events”, but their computed Control Limits of the CCs are wrong. The same happens for the Confidence Limits of the parameters of the distribution involved in the papers (Weibull, Inverse Weibull, Gamma, Binomial, Maxwell). We will show that the Re-liability Integral Theory (RIT) is able to solve these problems and the Sequential way of dealing with data.