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Comparison of off-line with in-process data validated both the double-slit die and the experimental methodology.
The automated system is shown to offer advantages over manual approaches in key areas while providing consistent and reproducible in-process data.
The cyber-physical systems of Industry 4.0 are expected to generate vast amount of in-process data and revolutionise the way data, knowledge and wisdom is captured and reused in manufacturing industries.
The latter involves non parametric estimation of conditional quantiles of a response variable from in-process data and allows process engineers to discover and visualise optimal ranges that are associated with quality improvements.
The smart tool 1 developed by authors, can provide real time in-process data on cutting forces.
Statistical analysis of release and in-process data coupled with in-depth process knowledge obtained through risk assessment and criticality analysis can provide the means of identifying opportunities to optimize the current process and/or identify areas where enhanced detection mechanisms are needed to ultimately improve end product quality.
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The presence of autocorrelation in process data has adverse effects on the performance of control charts.
KBM networks represent a method of expressing and combining different types of knowledge, usually available for modelling chemical and biochemical processes: mechanistic, heuristic and knowledge hidden in process data records.
The multivariate Shewhart control procedure is a popular statistical process-control technique to objectively detect unusual points of variability in process data.
The presence of autocorrelation in the process data can result in significant effect on the statistical performance of control charts.
In this process, data are coded in order to organise them into meaningful groups.
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