Erkki Jantunen

TL;DR: In this article, the authors provide a critical review of the predictive health monitoring methods of the entire defect evolution process i.e. wear evolution over the whole lifetime and suggest enhancements for rolling element bearing monitoring.

TL;DR: In this article, the authors present a summary of the monitoring methods, signal analysis and diagnostic techniques for tool wear and failure monitoring in drilling that have been tested and reported in the literature.

TL;DR: In this article, the authors propose a descriptive model of the wear evolution process in rolling bearings over the whole lifetime, which uses a wide range of empirical findings in the literature to describe the wear interactions and evolution in the five-stage scenario: running-in, steadystate, defect initiation, defect propagation, and damage growth.

TL;DR: In this article, a dynamic model of wear evolution that considers the topographical and tribological changes over the lifetime is presented, which suggests the use of multiple force diagrams to simulate the dynamic impact and utilises several models of contact mechanics to estimate the transition points between the wear evolution stages.

TL;DR: E-maintenance gives the reader an overview of the possibilities offered by new and advanced information and communication technology to achieve efficient maintenance solutions in industry, energy production and transportation, thereby supporting sustainable development in society.