Salih Seckin Erol (PhD)

Prognostics and health management (PHM) is an engineering discipline that purpose on maintaining system behaviour and function; and ensure task success, safety, and effectiveness. It is an advanced approach to minimize maintenance costs while maximizing operational availability and utilization of critical systems. PHM researches for developing sensor hardware and algorithms to detect anomalies, diagnose problems that cause the anomalies, and compute a probability distribution of time to failure. PHM technology should be part of routine maintenance for assets especially that have critical tasks. Gathering and analysing data over mechanical systems allows to plan in advance for repairs or replacement of systems and avoid unexpected downtime, minimize maintenance cost, and uptime of the assets optimized by remotely inspection and remote diagnosis of the systems.

eliability is an important issue to consider for mechanical systems. Periodic maintenance is not good enough for safety-critical systems like gearboxes in ground, air and sea vehicles. Prognostics and health management (PHM) was first raised by the U.S. armed force, which should ideally be able to predict faults and schedule maintenance only when necessary by monitoring the system condition. This seminar introduces the methods for predicting the future behavior of a system’s health and the remaining useful life to determine an appropriate maintenance schedule. This highly interdisciplinary engineering approach incorporates sensing technologies, physics of failure, machine learning, modern statistics and reliability engineering.

Different algorithms as well as measurement data integrated with PHM contains a comprehensive set of practises, some of which require Matlab similar programs; making this an ideal for graduate students in mechanical, civil, aerospace, electrical, industrial engineering, as well as researchers and maintenance engineers in the above fields.

MS Teams: https://teams.microsoft.com/l/meetup-join/19%3ameeting_MDQ0YjU5NWUtMDk5NC00NGQ0LWE4MmQtNTk0MzNiMGUwNGQ3%40thread.v2/0?context=%7b%22Tid%

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