Asset maintenance engineering methodologies

Content: Chapter 1 - Introduction1.1 Background1.2 Book structureChapter 2 - Terology Activity2.1 Background2.2 Concept of Terology vs Maintenance2.3 Terology as a multidisciplinary issue2.4 Terology and the environment2.5 Related conceptsChapter 3 - Physical Assets Acquisition and Withdrawal3.1 Background3.2 Purchase of physical assets3.3 Maintenance of physical assets3.4 Resources and budgeting3.5 Econometric models3.6 Life Cycle Costing3.7 Withdrawal3.8 Methods for replacing assets3.9 Case studyChapter 4 - Diagnosis of Maintenance State4.1 Background4.2 Holistic Diagnosis Model4.3 Questionnaires4.4 The Explanation Sheets4.5 Organization and analysis of information collected4.6 Elimination criteria4.7 Elimination Grid4.8 Establishment of an improvement action plan4.9 Case StudyChapter 5 - Maintenance Management5.1 Background5.2 Maintenance planning5.3 Maintenance control5.4 Maintenance resources5.5 Maintenance budget5.6 The Strategic Asset Management Plan5.7 Case Study Chapter 6 - Maintenance Resources6.1 Background6.2 Human Resources6.3 Spare Parts6.4 Tools6.5 Case StudyChapter 7 - Integrated Systems for Maintenance Management7.1 Background7.2 Software and hardware options7.3 Structure of information systems for maintenance7.4 A CMMS/EAM exampleChapter 8 - Expert Systems for Fault Diagnosis8.1 Background8.2 Profile of an ES for Fault Diagnosis8.3 Rule-based Expert Systems8.4 Case Based Reasoning 8.5 Bayesian Models8.6 Data Mining8.7 Performance Measures8.8 Usability and system interfaces8.9 Expert System exampleChapter 9 - Maintenance 4.09.1 Background9.2 Big Data9.3 Internet of things9.4 Sensorization and data communications9.5 Hardware and software optionsChapter 10 - Forecasting10.1 Background10.2 Time Series Forecasting10.3 Neural networks10.4 Discrete Systems Simulation10.5 Support Vector Machine10.6 Other prediction techniques10.7 A Case StudyChapter 11 - Maintenance Logistics11.1 Background11.2 Warehouse management systems and inventories11.3 Basic identification tools11.4 Transport systems11.5 Route planning11.6 Tools to aid logistics11.7 A Case StudyChapter 12 - Condition Monitoring12.1 Background12.2 Techniques for condition monitoring12.3 Types of sensors12.4 Data acquisition12.5 On-condition on-line12.6 On-condition with delay12.7 Technology for on-line condition monitoring12.8 Technology for offline condition monitoring12.9 Augmented Reality to aid condition maintenance12.10 Holography12.11 A Case StudyChapter 13 - Dynamic Modelling13.1 Background13.2 Fault Trees13.3 Markov chains13.3.1 Main description of the method13.4 Hidden Markov Models13.5 Petri networks13.6 A Case StudyChapter 14 - 3D Systems14.1 Background14.2 3D models for maintenance14.3 3D models and maintenance planning14.4 3D models and fault diagnosis14.5 3D models and the robots14.6 Software tools14.7 A Case StudyChapter 15 - Reliability15.1 Background15.2 Reliability concept15.3 Reliability analysis15.4 FMEA / FMECA15.5 RAMS15.6 A Case Study Chapter 16 - Management Methodologies16.1 Background16.2 5S16.3 Lean Maintenance16.4 A3 method16.5 GUT matrix16.6 6 Sigma16.7 PDCA16.8 Ishikawa diagram16.9 Brainstorming16.10 SWOT analysis16.11 Hoshin Kanri16.12 A Case StudyChapter 17 - Maintenance Standards17.1 Background17.2 NP 4492 Maintenance Services Series17.3 IEC 60300 Dependability Series17.4 IEC 60812 FMEA17.5 IEC 62278 / EN 50126 RAMS17.6 Other standardsChapter 18 - Maintenance Projects Managing18.1 Background18.2 PERT18.3 CPM18.4 PERT-CPM Networks18.5 Other methodologies18.6 Case studyChapter 19 - Maintenance Training19.1 Background19.2 E/B-Learning19.3 Intelligent Learning Systems19.4 Learning through 3D models19.5 Learning through the use of sensors19.6 Learning through Virtual Reality19.7 Learning through Augmented RealityChapter 20 - Terology Behind Tomorrow