Off-line quality control and ill-designed data

‘Bad’ data resulting from ill-designed experiments or in-production/after-production monitoring require a careful use of proper statistical techniques for their analysis. Prior exploration of the available data is of paramout importance especially if we wish to apply off-line quality control techniques such as the Taguchi method. A stepwise approach is proposed involving data analysis and straightforward significance tests, which can ensure statistically valid and useful conclusions.