Theory of Faults (ToF)

Digital Statistic Quality Control in Complex Systems

Abstract

Complexity in projects and infrastructure facilities render traditional forecasting and managerial tools ineffective. Complexity manifests in data entropy coupled with materiel flow.  Based on faults analysis, an explicatory theory [ToF] is developed mathematically, expanded by numerical experiments, validated by case-studies, and related to practice by participatory paradigm. ToF is applicable for systems characterized by Log-normal PDF. It is shown that power function magnitude distribution is a mathematical outcome of Log-normal PDF. Power function indicates complexity. Complex effects such as avalanche, and emergent traits such as risk behaviours are expounded. Information constraint, information entropy and Digital Signal Processing analysis broadens the understanding of effects of time and morphology, such as bifurcation, multiplication, propagation, and cost and time overruns.

ToF contributes modelling framework and management tools under complexity, it has been used to decipher systems’ morphology and behaviour, to direct Quality Control, and to facilitate digital control.