|Publication type:||Conference other|
|Type of review:||Not specified|
|Title:||Predictive-prescriptive analytics for combustion monitoring in gas turbine power plants|
|Conference details:||Predictive Maintenance, Swiss Association for Analytics (SAA), Lausanne, 27 September 2017|
|Subjects:||Predictive Maintenance; Analytics; Emission prediction|
|Subject (DDC):||003: Systems|
|Abstract:||Why do many Predictive Maintenance systems fail? The proposition of Predictive Maintenance paradigm is that a failure of a give system can be expected and predicted. However, complex systems in industrial applications are rarely stable, and the expected time to failure can vary rapidly as the operating conditions and regime change. Therefore, a clear strategy must be devised regarding how and when to act upon received prediction. We refer to this strategy as Prescriptive Maintenance, and describe it as an optimization problem. In this talk we discuss an example of moving from Predictive to Prescriptive Maintenance scheme using as an example a system we developed in collaboration with GE Power (Switzerland).|
|Fulltext version:||Published version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||Life Sciences and Facility Management|
|Organisational Unit:||Institute of Computational Life Sciences (ICLS)|
|Published as part of the ZHAW project:||Predictive - Prescriptive Analytics for Emission & Combustion Monitoring Agents in Gas Turbine Combined Cycle Power Plants|
|Appears in collections:||Publikationen Life Sciences und Facility Management|
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