Case A focuses on identifying the faults in out-of-control scenarios (a)–(e). Generate a total of 1200 profile samples with 200 samples in each class, as plotted in Fig. 6. The five OOC scenarios are specified as follows: (a) mean shift of the “block” reference signals: $x1\u2192x1+0.1\sigma x11K\xd71$, resulting in $\chi ~1,\u22c5,m=b1,m(x1+0.1\sigma x11K\xd71)+b2,mx2+\epsilon 1,m$, $\chi ~2,\u22c5,m=b3,m(x1+$$0.1\sigma x11K\xd71)2+0.1\sigma x11K\xd71)2+b4,mx3+\epsilon 2,m$, and $\chi ~4,\u22c5,m=b7,m(x1+$$0.1\sigma x11K\xd71)+\epsilon 4,m$; (b) superimposition of a sinusoid term on the “block” signal: $x1\u2192x1+0.1\sigma x1ys$, *y*_{s} is a sine function, resulting in $\chi ~1,\u22c5,m=b1,m(x1+0.1\sigma x1ys)+b2,mx2+\epsilon 1,m$, $\chi ~2,\u22c5,m=b3,m(x1+$$\sigma x1ys)2+b4,mx3+\epsilon 2,m$, and $\chi ~4,\u22c5,m=b7,m(x1+0.1\sigma x1ys)+\epsilon 4,m$; (c) increase in the standard deviation of the error term *e*_{1}: $\sigma \epsilon 1.m\u21923\sigma \epsilon 1.m$, leading to $\chi ~1,\u22c5,m=b1,mx1+b2,mx2+\epsilon ~1,m$, where $\epsilon ~1,m\u223cN(0,(3\xd70.5)2)$; (d) mean shift of the model parameter *b*_{1}: $\mu b1\u2192\mu b1+5\sigma b1$, yielding $\chi ~1,\u22c5,m=b~1,mx1+b2,mx2+\epsilon 1,m$, where $b~1,m\u223cN(\mu b1+5\sigma b1,\sigma b12)$; and (e) increase in the standard deviation of the model parameter *b*_{1}: $\sigma b1\u21924\sigma b1$, giving $\chi ~1,\u22c5,m=b~1,mx1+b2,mx2+\epsilon 1,m$, where $b~1,m\u223cN(\mu b1,(4\sigma b1)2)$.