Theory of Faults (ToF)

Digital Statistic Quality Control in Complex Systems

Abstract

When projects and infrastructure facilities are complex, traditional forecasting and managerial tools are rendered ineffective. The epistemic reliance of projects and infrastructures on information suggests a data-driven domain.  Although there is a gap in reliable data, data about faults accrues in systems. 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 a 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 segmentation and risk affiliation are expounded. Digital Signal Processing analysis broadens the understanding of effects of time and morphology, such as faults multiplication and propagation, and cost and time overruns. An application for project management is presented by a case-study.

ToF contributes a 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.