Statistical Process Control for Photopolymer Manufacturing: Sampling, Control Charts, Drift and Multivariate Signals

Statistical process control (SPC) is useful in photopolymer manufacturing only when the plotted quantity is a stable, meaningful process or product characteristic. A control chart cannot repair a changing measurement method, mixed resin populations or an unstable sampling plan. This review develops an SPC architecture for photopolymer production that begins with measurement- system adequacy and rational subgrouping. Univariate charts are used where one variable has a clear causal interpretation; multivariate methods are reserved for correlated optical, thermal, rheological or dimensional signals and require an interpretable reaction plan. Control limits are distinguished from engineering specification limits: a process can be statistically stable yet incapable, or statistically out of control while all observations remain within specification. Drift is treated as evidence to investigate resin history, lamp/optics, environment, wash media, post-cure or measurement state. The central conclusion is that SPC is an early- warning system for a defined process state, not an automated release decision and not proof of causality.

ER-296 · Version 0.3.