Ebook: Asset Condition, Information Systems and Decision Models

Asset Condition, Information Systems and Decision Models, is the second volume of the Engineering Asset Management Review Series. The manuscripts provide examples of implementations of asset information systems as well as some practical applications of condition data for diagnostics and prognostics. The increasing trend is towards prognostics rather than diagnostics, hence the need for assessment and decision models that promote the conversion of condition data into prognostic information to improve life-cycle planning for engineered assets. The research papers included here serve to support the on-going development of Condition Monitoring standards.

This volume comprises selected papers from the 1st, 2nd, and 3rd World Congresses on Engineering Asset Management, which were convened under the auspices of ISEAM in collaboration with a number of organisations, including CIEAM Australia, Asset Management Council Australia, BINDT UK, and Chinese Academy of Sciences, Beijing University of Chemical Technology, China.

Asset Condition, Information Systems and Decision Models will be of particular interest to finance, maintenance, and operations personnel whose roles directly affect the capability value of engineering asset base, as well as asset managers in both industry and government.

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Asset Condition, Information Systems and Decision Models, is the second volume of the Engineering Asset Management Review Series. The manuscripts provide examples of implementations of asset information systems as well as some practical applications of condition data for diagnostics and prognostics. The increasing trend is towards prognostics rather than diagnostics, hence the need for assessment and decision models that promote the conversion of condition data into prognostic information to improve life-cycle planning for engineered assets. The research papers included here serve to support the on-going development of Condition Monitoring standards.

This volume comprises selected papers from the 1st, 2nd, and 3rd World Congresses on Engineering Asset Management, which were convened under the auspices of ISEAM in collaboration with a number of organisations, including CIEAM Australia, Asset Management Council Australia, BINDT UK, and Chinese Academy of Sciences, Beijing University of Chemical Technology, China.

Asset Condition, Information Systems and Decision Models will be of particular interest to finance, maintenance, and operations personnel whose roles directly affect the capability value of engineering asset base, as well as asset managers in both industry and government.

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Asset Condition, Information Systems and Decision Models, is the second volume of the Engineering Asset Management Review Series. The manuscripts provide examples of implementations of asset information systems as well as some practical applications of condition data for diagnostics and prognostics. The increasing trend is towards prognostics rather than diagnostics, hence the need for assessment and decision models that promote the conversion of condition data into prognostic information to improve life-cycle planning for engineered assets. The research papers included here serve to support the on-going development of Condition Monitoring standards.

This volume comprises selected papers from the 1st, 2nd, and 3rd World Congresses on Engineering Asset Management, which were convened under the auspices of ISEAM in collaboration with a number of organisations, including CIEAM Australia, Asset Management Council Australia, BINDT UK, and Chinese Academy of Sciences, Beijing University of Chemical Technology, China.

Asset Condition, Information Systems and Decision Models will be of particular interest to finance, maintenance, and operations personnel whose roles directly affect the capability value of engineering asset base, as well as asset managers in both industry and government.
Content:
Front Matter....Pages i-xiii
Approaches to Information Quality Management: State of the Practice of UK Asset-Intensive Organisations....Pages 1-18
Information Systems Implementation for Asset Management: A Theoretical Perspective....Pages 19-69
Improving Asset Management Process Modelling and Integration....Pages 71-87
Utilising Reliability and Condition Monitoring Data for Asset Health Prognosis....Pages 89-103
Vibration-Based Wear Assessment in Slurry Pumps....Pages 105-123
The Concept of the Distributed Diagnostic System for Structural Health Monitoring of Critical Elements of Infrastructure Objects....Pages 125-131
Optimising Preventive Maintenance Strategy for Production Lines....Pages 133-147
A Flexible Asset Maintenance Decision-Making Process Model....Pages 149-168
Machine Prognostics Based on Health State Estimation Using SVM....Pages 169-186
Modeling Risk in Discrete Multistate Repairable Systems....Pages 187-205
Managing the Risks of Adverse Operational Requirements in Power Generation – Case Study in Gas and Hydro Turbines....Pages 207-218
Field-Wide Integrated Planning in a Complex and Remote Operational Environment: Reflections Based on an Industrial Case Study....Pages 219-232
Back Matter....Pages 233-234

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Asset Condition, Information Systems and Decision Models, is the second volume of the Engineering Asset Management Review Series. The manuscripts provide examples of implementations of asset information systems as well as some practical applications of condition data for diagnostics and prognostics. The increasing trend is towards prognostics rather than diagnostics, hence the need for assessment and decision models that promote the conversion of condition data into prognostic information to improve life-cycle planning for engineered assets. The research papers included here serve to support the on-going development of Condition Monitoring standards.

This volume comprises selected papers from the 1st, 2nd, and 3rd World Congresses on Engineering Asset Management, which were convened under the auspices of ISEAM in collaboration with a number of organisations, including CIEAM Australia, Asset Management Council Australia, BINDT UK, and Chinese Academy of Sciences, Beijing University of Chemical Technology, China.

Asset Condition, Information Systems and Decision Models will be of particular interest to finance, maintenance, and operations personnel whose roles directly affect the capability value of engineering asset base, as well as asset managers in both industry and government.
Content:
Front Matter....Pages i-xiii
Approaches to Information Quality Management: State of the Practice of UK Asset-Intensive Organisations....Pages 1-18
Information Systems Implementation for Asset Management: A Theoretical Perspective....Pages 19-69
Improving Asset Management Process Modelling and Integration....Pages 71-87
Utilising Reliability and Condition Monitoring Data for Asset Health Prognosis....Pages 89-103
Vibration-Based Wear Assessment in Slurry Pumps....Pages 105-123
The Concept of the Distributed Diagnostic System for Structural Health Monitoring of Critical Elements of Infrastructure Objects....Pages 125-131
Optimising Preventive Maintenance Strategy for Production Lines....Pages 133-147
A Flexible Asset Maintenance Decision-Making Process Model....Pages 149-168
Machine Prognostics Based on Health State Estimation Using SVM....Pages 169-186
Modeling Risk in Discrete Multistate Repairable Systems....Pages 187-205
Managing the Risks of Adverse Operational Requirements in Power Generation – Case Study in Gas and Hydro Turbines....Pages 207-218
Field-Wide Integrated Planning in a Complex and Remote Operational Environment: Reflections Based on an Industrial Case Study....Pages 219-232
Back Matter....Pages 233-234
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