Citation:
Eker OF, Camci F, Jennions IK (2012) Major challenges in prognostics: study on benchmarking prognostic datasets. Proceedings of the 1st European Conference of the Prognostics and Health Management Society, Dresden, Germany, 3-5 July 2012, PHM Society, pp.148-155
Abstract:
Even though prognostics has been defined to be one of the most difficult tasks in Condition Based Maintenance (CBM), many studies have reported promising results in recent years. The nature of the prognostics problem is different from diagnostics with its own challenges. There exist two major approaches to prognostics: data-driven and physics-based models. This paper aims to present the major challenges in both of these approaches by examining a number of published datasets for their suitability for analysis. Data-driven methods require sufficient samples that were run until failure whereas physics-based methods need physics of failure progression.