A stage-wise non-Gaussian statistical process control strategy

Abstract The article delves into the development of a Non-Gaussian Process Monitoring Strategy for Copper Cathode Manufacturing Unit (CCMU). monitoring strategy being devised highlighted issue multi-stage process via usage Multi-block Independent Component Analysis (MBICA) techniques. MBICA is multi-block variant ICA technique which prevalently used laden with non-Gaussian or non-normal data. Development involved detection fault(s) and their subsequent diagnosis. Detection was carried out by employment I 2 control chart whose limit established Bootstrap procedure. diagnosis detected fault diagnostic statistic. An amalgamation Multivariate Exponentially Weighted Moving Average (MEWMA) are also known as MBICA-MEWMA approach proposed incipient fault(s). thus developed showcased CCMU specialised in manufacture copper cathode has got varied practical applications. able to detect diagnose faults appreciable accuracy.