E-maintenance

E-maintenance is the synthesis of two major trends in today’s society: the growing importance of maintenance as a key technology and the rapid development of information and communication technology. E-maintenance gives the reader an overview of the possibilities offered by new and advanced information and communication technology to achieve efficient maintenance solutions in industry, energy production and transportation, thereby supporting sustainable development in society. Sixteen chapters cover a range of different technologies, such as: new micro sensors, on-line lubrication sensors, smart tags for condition monitoring, wireless communication and smart personal digital assistants. E-maintenance also discusses semantic data-structuring solutions; ontology structured communications; implementation of diagnostics and prognostics; and maintenance decision support by economic optimisation. It includes four industrial cases that are both described and analysed in detail, with an outline of a global application solution. E-maintenance is a useful tool for engineers and technicians who wish to develop e-maintenance in industrial sites. It is also a source of new and stimulating ideas for researchers looking to make the next step towards sustainable development. Preface Acknowledgements Contents Contributors Abbreviations 1 Introduction References 2 Maintenance Today and Future Trends 2.1 State of the Art in Management 2.2 Integrated Programmes and Planning Processes 2.2.1 Reliability-centred Maintenance 2.2.2 Total Productive Maintenance 2.2.3 Total Quality Maintenance 2.3 Strategies 2.3.1 Run-to-failure 2.3.2 Time-based Maintenance 2.3.3 Opportunity Maintenance 2.3.4 Design Out 2.3.5 Condition-based Maintenance 2.3.6 Summary 2.4 Maintenance Information and Control Systems 2.4.1 Features of the Typical Maintenance System: from SME to Global Enterprises 2.4.2 Limitations to the Penetration of Integrated Systems 2.5 State of the Art in Technology 2.5.1 Computing Tools 2.5.2 Measurement Tools and Services 2.5.3 Portable Instruments 2.5.4 Laboratory-based Services 2.6 New Paradigms: Customisation and Sustainability 2.7 New Developments in Decision Making 2.8 New Developments in Technological Tools 2.8.1 Wireless Sensors 2.8.2 Miniaturisation, Cost Reduction and MEMS 2.8.3 Disruptive Technologies and the Future 2.8.4 Pervasive Sensing and Intelligence 2.9 Conclusions References 3 Information and Communication Technologies Within E-maintenance 3.1 Introduction 3.2 Introduction to E-maintenance 3.2.1 Maintenance Today: What Are the Main Issues? 3.2.2 E-maintenance: Towards a Consensus or a Lot of Different Definitions? 3.2.3 E-maintenance: a Symbiosis Between Maintenance Services and Maintenance Technologies 3.3 ICT for E-maintenance 3.3.1 Miniaturisation Technologies for Data Acquisition 3.3.1.1 New Sensor Systems 3.3.1.2 Smart PDAs and Mobile Devices 3.3.1.3 Ubiquitous Computing 3.3.2 Standards for Data and Information Communication 3.3.2.1 Wireless Standards and Technologies 3.3.2.2 OSA-CBM Architecture 3.3.2.3 MIMOSA Protocols and OSA-EAI Architecture 3.3.3 Data and Information Processing and the Impact of Machine Learning Systems 3.4 Conclusions References 4 A New Integrated E-maintenance Concept 4.1 Introduction 4.2 E-maintenance Scenario Analysis 4.3 DynaWeb Integrated Solution 4.3.1 Standards and Technologies for Data Interoperability 4.3.2 Implementing the Solution 4.4 Intelligent Sensors 4.5 Information and Communication Infrastructure 4.6 Cost-effectiveness Based Decision Support System 4.7 DynaWeb Demonstrations 4.8 Conclusions References 5 Intelligent Wireless Sensors 5.1 Introduction 5.1.1 Fundamental Definitions 5.1.1.1 Definition of an Intelligent Sensor or Smart Transducer 5.1.1.2 Effectiveness of Conventional Sensors 5.1.2 Benefits of Using Intelligent Sensors 5.1.3 Businesses Driven Development of Intelligent Sensors 5.2 State-of-the-art Intelligent Sensors 5.2.1 Several Functions Within One Platform 5.2.2 Hardware 5.2.3 Wireless RF Standards 5.2.4 Intelligent Sensor Networks 5.3 Expected Features and Design of Intelligent Sensors 5.3.1 Conventional Sensors 5.3.2 Examples of Application of Conventional Sensors 5.3.2 Expected Features of Intelligent Sensors 5.3.2.1 Applications in Engineering Areas 5.3.2.2 Future Directions for Intelligent Sensors 5.3.3 Processing Capacity Offered by the Use of Intelligent Sensors 5.3.4 General Design Requirements for Intelligent Sensors 5.3.4.1 Quantifiable Requirements 5.3.4.2 Unquantifiable Requirements 5.4 Hardware Requirements for Wireless Sensors 5.4.1 Hardware Components 5.4.1.1 Analogue-to-digital Converter Unit 5.4.1.2 Sensing Unit 5.4.1.3 Power Sources 5.4.1.4 Housekeeping and Information Processing 5.4.2 ZigBee as a Suggested Communication Technology 5.4.2.1 ZigBee Interference 5.4.2.2 Network Topologies Offered by ZigBee Protocol 5.4.2.3 Performance and Network Reliability Assessment 5.5 Power Reduction Methods Available in ZigBee Protocol 5.5.1 Orthogonal Signalling – Used for 2.45 GHz 5.5.2 Warm-up Power Loss – DSSS 5.5.3 Transmitting and Receiving 5.5.4 Recovery Effect in Batteries 5.5.5 Cost Based Routing Algorithm – Link Quality and Hop Count 5.5.6 Power Consumption Tests 5.6 Conclusions References Bibliography 6 MEMS Sensors 6.1 Introduction 6.2 State-of-the-art of MEMS 6.3 Characteristics of MEMS Sensors 6.4 Specification of Multi-MEMS Sensor Platform 6.4.1 Introduction 6.4.2 Objectives 6.4.3 Possible Profiles of Intelligent Sensors 6.4.3.1 Autonomy Intelligent Sensor – Profile 1 6.4.3.2 Cooperation Intelligent Sensor – Profile 2 6.4.3.3 Slave Master Intelligent Sensor – Profile 3 6.4.3.4 Simplest Intelligent Sensor – Profile 4 6.5 Simulation of a Multi-MEMS Sensor Platform 6.5.1 Sensing Unit 6.5.2 Processing Unit 6.5.3 Hardware Implementation 6.5.4 Data Sampling 6.5.5 Local Decision Making Based on Condition 6.5.6 Threshold with Event Triggering 6.5.7 Data Pre-processing 6.5.8 Transmission on Intervals 6.6 Power Management 6.6.1 Sleep Mode 6.6.2 Performance versus Power Consumption 6.6.3 Energy Harvesting System 6.6.4 Energy Transducers 6.6.4.1 Piezo Film 6.6.4.2 Piezo Buzzer 6.6.4.3 Piezoelectric Fibre Composites 6.6.4.4 Electromagnetic Generators 6.6.4.5 Solar Panels 6.6.4.6 Heating Transducer 6.6.5 Energy Converting and Storing Subsystems 6.6.6 Implementation of an Energy Harvester 6.6.6.1 Hardware Structure and Implementation 6.6.6.2 The Work Process of the System 6.7 Conclusions References 7 Lubricating Oil Sensors 7.1 Introduction 7.2 State-of-the-art 7.2.1 Oxidation 7.2.2 Viscosity 7.2.3 Corrosion 7.2.4 Water 7.2.5 Particles 7.2.6 Others 7.3 New Sensor Developments 7.3.1 Detection of Solid Contaminants 7.3.1.1 Fibre Optic Solid Contaminant Sensors 7.3.1.2 Particle Sensors 7.3.2 Water Detection 7.3.2.1 Water Sensor Development 7.3.3 Lubrication Deterioration by Ageing 7.4 Conclusions References 8 Smart Tags 8.1 Introduction 8.2 Overview of the Technology 8.2.1 Technical Basics 8.2.1.1 RFID Tags 8.2.1.2 RFID Smart Labels 8.2.1.3 Tagging Mode (Active versus Passive) 8.2.1.4 Read-only versus Read-write 8.2.1.5 RFID Readers 8.2.1.6 Key Attributes 8.2.2 RFID Software Considerations 8.2.3 RFID Standards 8.2.4 Costs Involved 8.2.5 Advantages and Disadvantages 8.2.6 Privacy Issues 8.2.7 Applications for RFID 8.3 Real-time Locating Systems Using Active RFID 8.3.1 Time of Arrival 8.3.2 Time Difference of Arrival 8.3.3 Angle of Arrival 8.3.4 Received Signal Strength Induction 8.3.5 LANDMARC 8.4 Background to Applications of RFID 8.5 Review of RFID Applications in Maintenance 8.6 Applications and Scenarios 8.6.1 Tools 8.6.2 Spare Parts 8.6.3 Machines 8.6.4 Personnel 8.7 Smart Tag Demonstrators 8.7.1 Inventory Tracking (Passive) 8.7.2 Asset Identification and Query System for PDAs (Passive) 8.7.3 Mobile Assets Positioning System (Active) 8.8 Conclusions References Bibliography 9 Mobile Devices and Services 9.1 Introduction 9.2 Mobile Devices in Maintenance Management 9.3 Role of PDA Within DynaWeb 9.4 Description of Typical PDA Usage Scenario in Maintenance Operations 9.5 Wireless Communication 9.6 Technical Requirements 9.7 Practical Limitations Today 9.8 Mobile User Interface Issues 9.9 Trends 9.10 Conclusions References 10 Wireless Communication 10.1 Introduction 10.2 State-of-the-art 10.2.1 WLANs (IEEE 802.11) 10.2.2 Bluetooth (IEEE 802.15.1) 10.2.3 ZigBee (IEEE 802.15.4) 10.2.4 Assessment of Previous Technologies to Support E-maintenance Applications 10.2.5 Conclusions 10.3 New Developments 10.3.1 Wireless Gateway 10.3.2 Wireless Collector 10.4 Conclusions and Recommendations References 11 Semantic Web Services for Distributed Intelligence 11.1 Introduction 11.2 State-of-art in Application of the Semantic Web to Industrial Automation 11.2.1 What Is Ontology? 11.2.2 Advantages of Semantic Web Techniques 11.2.2.1 Improved Web Search 11.2.2.2 Better Integration 11.2.2.3 Lexicon Flexibility and Standardisation 11.2.2.4 Composition of Complex Systems 11.2.3 Semantic Web Languages 11.2.4 Semantic Web Platforms 11.2.4.1 Protégé 2000 11.2.4.2 Altova Semantic Works 2008 11.2.4.3 SMORE 11.2.5 Semantic Web Development in Industrial Automation 11.2.5.1 OntoServ.NET 11.2.5.2 Obelix 11.2.5.3 Rewerse 11.2.5.4 Knowledge Web 11.2.5.5 Other Related Works 11.3 Web Services for Dynamic Condition Based Maintenance 11.3.1 Web Service for Condition Monitoring 11.3.2 Web Service for Diagnosis Based on Vibration and Oil Data 11.3.3 Web Service for Prognosis 11.3.3.1 Proportional Hazard Model 11.3.3.2 Exponential Curve Fitting 11.3.4 Web Service for Scheduling 11.3.5 Testing Web Services 11.4 Conclusions References 12 Strategies for Maintenance Cost-effectiveness 12.1 Introduction 12.2 Development of Strategies for Cost-effectiveness 12.2.1 Theoretical Background 12.2.1.1 Maintenance Related Economic Factors 12.2.1.2 Diagnosis Techniques 12.2.1.3 Maintenance Management IT-systems 12.2.2 The Role of Maintenance in Company Business 12.3 Development of a Maintenance Decision Support System (MDSS) 12.3.1 Objectives of MDSS 12.3.2 MDSS Toolsets and Tools 12.3.2.1 Accurate Maintenance Decisions: PreVib, ProFail and ResLife 12.3.2.2 Maintenance Cost-effectiveness: MMME and MainSave 12.3.3.3 Simulation of the Most Cost-effective Solution (AltSim) 12.4 Conclusions References 13 Dynamic and Cost-effective Maintenance Decisions 13.1 Introduction 13.2 MDSS for Dynamic and Cost-effective Maintenance Decisions 13.2.1 Deterministic and Probabilistic Approaches 13.2.2 Dynamic and Cost-effective Maintenance Decisions 13.2.3 Application Scenario of MDSS 13.3 Data Required to Run MDSS 13.3.1 Datasets 13.3.2 Data Gathering 13.4 Database Required for MDSS 13.4.1 MDSS Data Model 13.4.2 Mapping to Company Data Models 13.4.3 Mapping to CRIS/MIMOSA 13.4.4 CRIS/MIMOSA Database User-interface 13.4.5 Test of CRIS/MIMOSA Database User-interface 13.5 Case Studies for Applying MDSS 13.5.1 Toolset 1: PreVib, ProFail and ResLife 13.5.2 Toolset 2: AltSim 13.5.3 Toolset 3: MMME and MainSave 13.6 Results and Discussions 13.7 Conclusions References 14 Industrial Demonstrations of E-maintenance Solutions 14.1 Global Demonstration in a Milling Machine Environment 14.1.1 Objectives of the Test and Demonstrations 14.1.2 Description of the Test Platform 14.1.3 Description of the DynaWeb Components Tested 14.1.3.1 Smart Tags and PDA Support 14.1.3.2 Handheld PDA Vibration Data Collector 14.1.3.3 Vibration Measurement System 14.1.3.4 Oil Sensors 14.1.3.5 Communication 14.1.3.6 MDSS 14.1.4 Economical Evaluation 14.1.5 Conclusions 14.2 Foundry Hydraulic System Demonstrator 14.2.1 Objectives of the Test and Demonstrations 14.2.2 Description of the Test Platform 14.2.3 Description of the DynaWeb Components Tested 14.2.3.1 Sensor Measuring Oxidation of the Lubricant by Spectroscopy of Visible Light 14.2.3.2 TESSnet Platform 14.2.3.3 Data Storage in the Global MIMOSA Database 14.2.4 Reference Measurements and Software 14.2.5 Results 14.2.5.1 Sensor Measuring Oxidation of the Lubricant by Spectroscopy of Visible Light 14.2.5.2 Data Storage and Communication 14.2.6 Technical Evaluation 14.2.7 Economical Evaluation 14.2.8 Conclusions and Recommendations 14.2.8.1 Conclusions 14.2.8.2 Recommendations 14.3 Automatic Strip Stamping and Cutting Machine Demonstrator 14.3.1 Objectives of the Test and Demonstrations 14.3.1.1 Isolated Validation 14.3.1.2 Integrated Validation 14.3.2 Description of the Test Platform 14.3.3 Description of the DynaWeb Components Tested 14.3.4 Reference Testing Procedure 14.3.4.1 Procedure for Internal Tests 14.3.4.2 Procedure for Integration Tests 14.3.5 Results 14.3.5.1 Preliminary Tests 14.3.5.2 Internal Tests 14.3.5.3 Integration Tests 14.3.6 Conclusions 14.4 Machine Tool Demonstrator 14.4.1 Objectives of the Test and Demonstrations 14.4.2 Description of the Test Platform 14.4.3 Description of the DynaWeb Components Tested 14.4.4 Reference Measurements/Software 14.4.5 Results 14.4.6 Technical Evaluation 14.4.7 Economical Evaluation 14.4.8 Conclusions and Recommendations 14.5 Maritime Lubrication System Demonstrator 14.5.1 Objectives of the Test and Demonstrations 14.5.2 Description of the Test Platform 14.5.2.1 The Sampling System 14.5.2.2 Testing Method 14.5.2.3 Technical Specifications of the Test Rig 14.5.3 Description of the DynaWeb Components Tested 14.5.4 Reference Measurements/Software 14.5.5 Results of the Demonstration 14.5.6 Technical Evaluation 14.5.7 Economical Evaluation 14.5.8 Conclusions References 15 E-training in Maintenance 15.1 Introduction 15.2 The Need for Maintenance E-training 15.3 E-learning Technologies 15.3.1 Adaptive Learning 15.3.2 Learning Objects, Standards and Interoperability 15.3.3 Learning Management Systems 15.3.4 Moodle LMS 15.3.5 Advanced Learning Technologies 15.3.6 Vocational Training in Maintenance 15.4 E-training for E-maintenance 15.4.1 Dynamite E-training: the DynaTrain Platform 15.4.2 Vibration Sensing 15.4.3 Data Acquisition 15.4.4 Inventory Tracking System 15.4.5 Prognosis Web Services 15.4.6 MIMOSA Translator 15.5 Conclusions References 16 Conclusions and Future Perspectives