A statistical model of routine process monitoring variates and conformance assessment for radiation processing

Abstract

Modeling a routine radiation process monitoring variate consists of identifying a statistical model that accurately forecasts process variate solution space and provides an inference structure by which processed product conformance to dose range specifications can be assessed with a high degree of surety. This paper shall identify and describe the structural characteristics of the process variates associated with the various forms of routine radiation process monitoring and demonstrate the Bivariate Normal Joint Probability distribution model applicability to routine radiation processing end to end. The routine radiation process end to end consists of:a.Performance qualification dose mapping (PQ)b.Capability/reliability assessmentc.Process target optimization (PTO)d.Statistical process control (SPC) of the routine processe.Product conformance assessment of processed products to dose range specifications.The significance of this model is it is a probabilistic risk/confidence assessment of the process output variate. This treats the sampled variate output as expressing the aggregate variance of all expressing predictor variables (common cause), accurately treats output variates as random variates (solution space) and avoids the errors of the current routine radiation process monitoring industry model.