Abstract
<jats:title>Abstract</jats:title> <jats:p>Process predictability may be impaired in two ways — by lack of process information and by lack of process repetitiveness (process is partially repetitive (semi‐repetitive) or not repetitive at all). In this four‐part series, we address statistical engineering implications of the latter, namely, how lack of complete repetitiveness affects engineering and managerial decisions, required in the analysis and design of semi‐repetitive processes and in their management. In this first part, we deliver an overview of the other three parts of the series, addressing statistical engineering questions and problems this series is intended to respond to, and the adaptations needed (relative to repetitive or non‐repetitive processes). In particular, we address the dual‐component variation of semi‐repetitive processes (second part), measuring process repetitiveness (third part) and assessing reliability of process‐time predictions, as we move from repetitive to semi‐repetitive to non‐repetitive processes (fourth part).</jats:p>