Special Issue "Advanced Soft Computing for Prognostic Health Management"

Description

Prognostic Health Management (PHM) is a research area of growing interest in the era of Industry 4.0 because it enables efficient management of machine life cycle and maximization of component's lifespan. Furthermore, it prevents from catastrophic damage of a component leading to a complete shutdown of overall production cycle [1]. This problem cannot be addressed by applying a regular maintenance carried out within pre-scheduled time periods because a component life is subject to various operational conditions. Tool may fail much earlier or later from what it is supposed to be. This aspect results in a growing popularity of soft computing techniques which can be utilized as efficient computational tool for predictive maintenance, maximization of product life cycle, planning and scheduling [2]. That is, it underpins a new paradigm “maintenance on-demand”. All of which allow advanced scheduling of maintenance activities, proactive allocation of replacement parts and enhanced fleet deployment decisions based on the estimated progression of component life consumption.

Period	01 Jan 2018 → 30 Nov 2018