<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Performance improvement is taken as the primary goal in the asset management. Advanced data analysis is needed to efficiently integrate condition monitoring data into the operation and maintenance. Intelligent stress and condition indices have been developed for control and condition monitoring by combining generalized norms with efficient nonlinear scaling. These nonlinear scaling methodologies can also be used to handle performance measures used for management since management oriented indicators can be presented in the same scale as intelligent condition and stress indices. Performance indicators are responses of the process, machine or system to the stress contributions analyzed from process and condition monitoring data. Scaled values are directly used in intelligent temporal analysis to calculate fluctuations and trends. All these methodologies can be used in prognostics and fatigue prediction. The meanings of the variables are beneficial in extracting expert knowledge and representing information in natural language. The idea of dividing the problems into the variable specific meanings and the directions of interactions provides various improvements for performance monitoring and decision making. The integrated temporal analysis and uncertainty processing facilitates the efficient use of domain expertise. Measurements can be monitored with generalized statistical process control (GSPC) based on the same scaling functions.</p></abstract>

Performance improvement is taken as the primary goal in the asset management. Advanced data analysis is needed to efficiently integrate condition monitoring data into the operation and maintenance. Intelligent stress and condition indices have been developed for control and condition monitoring by combining generalized norms with efficient nonlinear scaling. These nonlinear scaling methodologies can also be used to handle performance measures used for management since management oriented indicators can be presented in the same scale as intelligent condition and stress indices. Performance indicators are responses of the process, machine or system to the stress contributions analyzed from process and condition monitoring data. Scaled values are directly used in intelligent temporal analysis to calculate fluctuations and trends. All these methodologies can be used in prognostics and fatigue prediction. The meanings of the variables are beneficial in extracting expert knowledge and representing information in natural language. The idea of dividing the problems into the variable specific meanings and the directions of interactions provides various improvements for performance monitoring and decision making. The integrated temporal analysis and uncertainty processing facilitates the efficient use of domain expertise. Measurements can be monitored with generalized statistical process control (GSPC) based on the same scaling functions.

Intelligent Performance Analysis with a Natural Language Interface

Management Systems in Production Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Intelligent Performance Analysis with a Natural Language Interface"}

Performance improvement is taken as the primary goal in the asset management. Advanced data analysis is needed to efficiently integrate condition monitoring...

Intelligent Performance Analysis with a Natural Language Interface

Article Category: Special Issue Title: Maintenance Performance Measurement and Management Challenges: from Sensing to Decision Support

Pubblicato online: 01 ago 2017

Pagine: 168 - 175

Ricevuto: 01 ott 2016

Accettato: 01 apr 2017

DOI: https://doi.org/10.1515/mspe-2017-0025

Parole chiave
data analysis, nonlinear scaling, trend analysis, fuzzy systems, natural language

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Intelligent Performance Analysis with a Natural Language Interface

Article Category: Special Issue Title: Maintenance Performance Measurement and Management Challenges: from Sensing to Decision Support

Pubblicato online: 01 ago 2017

Pagine: 168 - 175

Ricevuto: 01 ott 2016

Accettato: 01 apr 2017

DOI: https://doi.org/10.1515/mspe-2017-0025

Parole chiavedata analysis, nonlinear scaling, trend analysis, fuzzy systems, natural language

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Parole chiave
data analysis, nonlinear scaling, trend analysis, fuzzy systems, natural language