Monitoring & Diagnostics: The Way to Optimized Maintenance and High Reliability

Sponsored by: AREVA GmbH

Focused on:

  • Maintenance
  • Diagnostics

Date: 22 November


Time: 3PM London/10AM New York

As rarely as possible, as early as necessary - this is the headline of predictive-maintenance; the transition from preventive- to predictive- reduces the cost of ownership by maintaining the reliability and availability of an asset or plant. Unnecessary work is avoided; maintenance on a running machine which is in good condition puts the assets in jeopardy rather than improving them.

Safety has the highest priority in nuclear industry. Systems and technology used for monitoring and diagnoses in nuclear power plants are correspondently advanced and certified. Adaptation to any industrial areas, to fit the specific needs is however easily achievable, as much in terms of technology as of commercial margins and still take profit from the high safety level and accumulated experiences AREVA has done.

One example of the adaptation potential of AREVAs "nuclear" systems is the industrial leakage detection system LEOS (see previous webinar on Enhanced Pipeline Safety). A robust radiation proof system of steel and sintered ceramic inlets with micro holes, to allow diffusion of humidity into the system (gradient of gas concentration), is redesigned using a permeable plastic tube instead, allowing the detection of the smallest leaks at the earliest stage of the development of a risk, which is especially important in environmentally sensitive areas or when dealing with dangerous gases like chlorine, making visual inspection and NDT on the pipes dispensable.

With AREVA's fully flexible and open diagnostic platform, different physical principles are utilized depending on the monitoring task and application. This may be changes in the acoustic pattern of machines, the vibration behaviour of rotating machinery, the dynamic characteristics of valves and drives or the determination of usage factors by fatigue or creep phenomena. All this can be used to evaluate the condition of the assets and give trends of the asset health status and the operation point of the machine / system, to optimize maintenance cycle and the remaining lifetime.

Combining Big Data Analytics including machine-learning tools with rule-based diagnostics derived from expert knowledge, software tools automatically monitor these patterns allowing the specialist to concentrate on critical cases. A remote access to the data allows bundling fleet wide information on may assets in a very efficient way and AREVAs remote diagnostic centre with its nuclear industry roots fully complies to the latest cyber security standards.

The webinar will highlight AREVAs experiences, lessons learnt and will demonstrate methods to optimize maintenance and reliability.

Presented by

Philipp Miesen,

Business Development Manager Asset & Lifetime Management Services & Tools

Philipp Miesen joined AREVA in 2008 as Design Engineer for Electrical and I&C Equipment Qualification according to nuclear regulations.

From 2010 to 2013 he was Project Manager and Technical Responsible for Equipment & Self-Standing-Systems Qualification for a Nuclear Power Plant Project.

In 2013, he was appointed Business Development Manager for Asset and Lifetime Management Services and Tools.

He has a university degree in Mechanical Engineering (2007) from Universidad Técnica de Manabí – Ecuador.

Dr. Gerrit Gloth,

Management of Asset Management Products and Expert for Vibration Monitoring

Gerrit Gloth joined AREVA in 2005 and is currently head of the section for asset management products. Leading a group of specialists with very different expertise he is responsible for the product management, technical sales support and project management for various monitoring and diagnostic systems like vibration, loose parts, leakage and seismic monitoring systems as-well-as diagnoses for rotating machinery. The ample portfolio is completed by an expert system which is capable to use and combine information from various proprietary or third-party systems.

Before joining AREVA, he worked for German Aerospace Center DLR as an expert for structural dynamics using both numerical and experimental methods. He managed vibration tests on large aerospace structures like prototype aircrafts and satellites.

He graduated in Germany in 1997 with a Ph.D. (Dr.-Ing.) in Mechanical Engineering with a thesis on aero-elastic phenomena of rotating airfoils, after having studied physics at the University of Hamburg and working on high-energy physics at the hadron-electron collider HERA. In the meantime he has gained more than 10 years of experience in managing and developing several monitoring systems based on very different physical principles and applying them in different environments like nuclear and conventional power plants as-well-as in the chemical and oil&gas industry.

Key Learning Objectives

  • Learn what monitoring and diagnostics systems are established in nuclear and other plants
  • Learn how these systems work
  • Learn how these systems can assist to optimize maintenance and reliability
  • Learn how you can benefit


  • Head of Maintenance
  • Operational Excellence Manager
  • Project Manager
  • Product Mnager