Intelligent Production Machines and Systems - First I*PROMS Virtual Conference

Table of contents

1. Copyright
2. IPROMS 2005 Sponsors
3. Preface
4. Introduction by Mr A Gentili, European Commission
5. Programme and Organising Committees
   1. Special Session Organisers
   2. Session Chairmen and Co-Chairmen
   3. Referees
   4. Facilitators
   5. I*PROMS Central Coordination and MEC Teams
6. The EU FP6 I*PROMS Network of Excellence for Innovative Production Machines and Systems
   1. Abstract
   2. 1. Rationale for Networks of Excellence
   3. 2. The I*PROMS Network of Excellence
   4. 3. The Clusters in I*PROMS
      1. 3.1. Advanced Production Machines (APM) Cluster
      2. 3.2. Production Automation and Control (PAC) Cluster
      3. 3.3. Innovative Design Technology (IDT) Cluster
      4. 3.4. Production Organisation and Management (POM) Cluster
   5. 4. I*PROMS Activities
   6. 5. Network Management
   7. 6. Impact of I*PROMS
   8. Acknowledgement
   9. References
7. A robustness index for scheduling based on sensitivity analysis
   1. Abstract
   2. 1. Introduction
   3. 2. Basics of Sensitivity Analysis
   4. 3. Job shop scheduling
   5. 4. Sensitivity analysis for schedules of job-shop environment
   6. 5. Measuring Robustness of Schedules
      1. 5.1. Background
      2. 5.2. The robustness index
   7. 6. Conclusion
   8. References
8. Computer aided procedure for selecting technological parameters in the drawing process
   1. Abstract
   2. 1. Introduction
   3. 2. Analytical methods
   4. 3. Analysis by FEM
   5. 4. Results and discussion
   6. 4. Conclusions
   7. References
9. Intelligent software agents as a basis for collaborative manufacturing systems
   1. Abstract
   2. 1. Introduction
   3. 2. Intelligent software agents
   4. 3. Agents in the manufacturing application domain
   5. 4. Agent-based process planning and scheduling
   6. 5. Agent-based inter-organisational coordination
      1. 5.1. The Agent.Enterprise approach
      2. 5.2. The MaBE approach
         1. 5.2.1. Description of the MaBE middleware
         2. 5.2.2. MaBE demonstrator functionalities
         3. 5.2.4. Latest developments in ontology mapping
   7. 6. Conclusions
   8. Acknowledgement
   9. References
10. Modelling and simulation on an RFID based manufacturing system
    1. Abstract
    2. 1. Introduction
    3. 2. RFID conception
    4. 3. Constraints in conventional manufacturing systems
    5. 4. A framework for RFID based manufacturing system
       1. 4.1. Machining stage
       2. 4.2. Assembly stage
       3. 4.3. Packaging stage
    6. 5. A case study on the machining process and assembling process
       1. 5.1. Model construction
       2. 5.2. Evaluation based on simulation
    7. 6. Conclusions
    8. Acknowledgements
    9. References
11. Production variable management: a software tool based on the connectance concept
    1. Abstract
    2. 1. Introduction
    3. 2. Tool For Action Plan Selection (TAPS)
       1. 2.1. Database Module
       2. 2.2. Analysis Module
       3. 2.3. Graphic User Interface (GUI)
       4. 2.4. Evaluation Module
    4. 3.0. Applications
    5. 4.0. Conclusion
    6. Acknowledgement
    7. References
12. Toward the Next Generation of Manufacturing Systems. FRABIHO: A Synthesis Model for Distributed Manufacturing
    1. Abstract
    2. 1. Introduction
    3. 2. Distributed Manufacturing Systems models
       1. 2. 1. Fractal Manufacturing Systems
       2. 2.2. Bionic Manufacturing Systems
       3. 2.3. Holonic Manufacturing Systems
    4. 3. DMS protomodel: FRABIHO
    5. 4. Modelling FRABIHO
    6. 4. Conclusions
    7. Acknowledgements
    8. References
13. An Enterprise Collaborative Portal with a Case-Based Reasoning Tool for Business Process Model Creation
    1. Abstract
    2. 1. Introduction
    3. 2. Enterprise Collaborative Portals, Business Process Modelling and Case Based Reasoning
    4. 3. Proposed approach
       1. 3.1. Collaborative authoring of process models
       2. 3.2. The proposed approach
    5. 4. System architecture
       1. 4.1. Graphical process modelling tool
       2. 4.2. Collaboration tool
       3. 4.3. Case-based reasoning tool
       4. 4.4. Portal services
    6. 5. Case study
    7. 6. Conclusions
    8. Acknowledgements
    9. References
14. Automatic formation of rules for feature recognition in solid models
    1. Abstract
    2. 1. Introduction
    3. 2. Automatic formation of feature recognition rules
       1. 2.1. Inductive learning
       2. 2.2. Training data creation
          1. 2.2.1. Proposed approach
          2. 2.2.2. Data format
          3. 2.2.3. Characteristic vector design
    4. 3. Illustrative example
       1. 3.1. Training data creation
          1. 3.1.1. Feature taxonomy
          2. 3.1.2. Feature coding schemes
          3. 3.1.3. Extraction of characteristic vectors
       2. 3.2. Rule formation
    5. 4. Testing
    6. 5. Conclusions
    7. Acknowledgements
    8. References
15. Backlash Error and Effects on the Accuracy of Vertical Machining Center
    1. Abstract
    2. 1. Introduction
    3. 2. Experimental procedures
       1. 2.1. The VM101 linear encored measurement System
       2. 2.2. Measurement process
    4. 3. Experimental results
       1. 3.1. Axis linear displacement error
       2. 3.2. Backlash error
    5. 4. The models of backlash error
       1. 4.1. The ANN models of backlash error
       2. 4.2. The polynomial models of backlash error
    6. 5. Accuracy after backlash error compensated
    7. 6. Conclusions
    8. Acknowledgements
    9. References
16. BM_Virtual Enterprise Architecture Reference Model for Concurrent Engineering processes performance improvement: An experiment
    1. Abstract
    2. 1. Introduction
    3. 2. Concurrent Engineering Concept
    4. 3. BM_VEARM
    5. 4. The Experiment
       1. 4.1. Team work Description
          1. 4.1.1. Distributed CE Team
          2. 4.1.2. Agile CE Team According to BM_VEARM
          3. 4.1.3. Virtual CE Team According to BM_VEARM
       2. 4.2. Evaluation Criteria
    6. 5. Results
    7. 6. Conclusion
    8. References
17. Holistic Approach for Condition Monitoring and Prediction of Machine Axis
    1. Abstract
    2. 1. Introduction
    3. 2. Research Activities
       1. 2.1. IMS- Watchdog Agent™
       2. 2.2. Live Cycle Unit
       3. 2.3. Intelligent Spindle Unit
    4. 3. Test Routines
       1. 3.1. Friction – Indicator for Degradation
       2. 3.2. NC-Test Cycles – Uncovering of the Indicators
          1. 3.2.1. The Stiction Test
          2. 3.2.2. The Viscosity Test
       3. 3.3. Using Statistical Data
    5. 4. Outlook
    6. Acknowledgement
    7. References
18. Overcoming the challenges of product development and engineering changes in a distributed engineering environment
    1. Abstract
    2. 1. Introduction
    3. 2. Product data driven engineering workflow
    4. 3. Distributed workspace
       1. 3.1. How to share information in a distributed environment
       2. 3.2. Demands on a distributed workspace
       3. 3.3. Architecture of the distributed workspace
       4. 3.4. Organisation of collaboration
       5. 3.5. Security mechanisms deployed
    5. 4. Conclusions
    6. Acknowledgements
19. A problem solving approach to developing product support systems
    1. Abstract
    2. 1. Introduction
    3. 2. Background
       1. 2.1. Problem solving and reasoning techniques in AI
       2. 2.2. Reasoning techniques in product support
    4. 3. Problem solving approach to product support
       1. 3.1. Information object cluster
       2. 3.2. Problem characterisation
       3. 3.3. Knowledge reuse for previously solved problems
       4. 3.4. Knowledge adaptation for similar problems
       5. 3.5. Knowledge creation for new problems
    5. 4. Implementation
    6. 5. Conclusions and future work
    7. Acknowledgements
    8. References
20. An Object-Oriented Framework for Intelligent Product Manuals
    1. Abstract
    2. 1. Introduction
    3. 2. Problems on Documentation Systems Development
       1. 2.1. Web Enabled Documentation
       2. 2.2. Information Integration
       3. 2.3. Ensuring High Quality Information Systems
    4. 3. An Object-Oriented Framework for the Generation of Technical Documentation
    5. 4. Enabling Object Technologies
       1. 4.1. Servlet Technologies
       2. 4.2. Java Database Connectivity
       3. 4.3. XML Technology
       4. 4.4. Text Pattern Matching
    6. 5. System Architecture
    7. 6. Case Study
    8. 7. Discussion & Conclusions
    9. Acknowledgements
    10. References
21. Design and development of a decision support system for manufacturing systems
    1. Abstract
    2. 1. Introduction
    3. 2. The decision support system architecture
    4. 3. Design and Development of the DSS
       1. 3.1. Process Modelling Tool
       2. 3.2. Simulation Modelling Tool
       3. 3.3. Virtual Modelling Tool
       4. 3.4. Simulate and output analyzing tools
    5. 4. Conclusions
    6. 5. Acknowledgement
    7. References
22. E-supply application - Finnish case study
    1. Abstract
    2. 1. Introduction
    3. 2. Study approach
    4. 3. ICT in supply chain integration
       1. 3.1. Supply chain integration
       2. 3.2. Information integration with ICT
       3. 3.3. e-supply design
    5. 4. Case study
       1. 4.1. Case network
       2. 4.2. The evolution of e-supply chains
          1. 4.2.1. State of art – level I/II
          2. 4.2.2. The first step to the level III
          3. 4.2.3. The second step to the level IV
       3. 4.3. SteelNet system
    6. 5. Conclusion
    7. References
23. Knowledge-based manufacturing within the extended enterprise
    1. Abstract
    2. 1. Introduction
    3. 2. Knowledge representation
    4. 3. Representation of information for reconfigurable machine tools
    5. 4. Agent support for the extended enterprise
    6. 5. Customer supplier collaboration
    7. 6. Knowledge management within the extended enterprise
    8. 7. Conclusion
    9. Acknowledgement
    10. References
24. Potentials of Voice Interaction in Industrial Environments
    1. Abstract
    2. 1. Introduction
    3. 2. Criteria for the implementation of voice user interfaces
       1. 2.1. Communication with computers is still restricted—yet effective
       2. 2.2. Even large amounts of information can be easily input via voice, whereas output is limited
       3. 2.3. Suitable information for VUIs is one that can easily be put in words
       4. 2.4. Dealing with linguistic diversity and overcoming physical handicaps
       5. 2.5. Hands and eyes free, mobility provided
       6. 2.6. Straight usability – even in adverse conditions
       7. 2.7. Motivational aspects matter
       8. 2.8. Economical factors
    4. 3. Conclusion
    5. References
25. Real Time Integrated Transportation System
    1. Abstract
    2. 1. Introduction
    3. 2. Proposed System
    4. 3. RTITS Components
       1. 3.1. Mobile Units
       2. 3.2. Central Server
    5. 4. Working of Real Time Integrated Transportation System
       1. 4.1. Operations
       2. 4.2. Use Case Model for RTITS
    6. 5. Conclusion
    7. Acknowledgement
    8. References
26. Study On Manufacture Resource Evaluating System Of the ASP-based Platform
    1. Abstract
    2. 1. Introduction
    3. 2. The Synthesis Evaluation System of Manufacturing Resources
       1. 2.1. The Forming Process of Virtual Enterprise
       2. 2.2. Two-stage Decision Model of Manufacture Resources
    4. 3. Synthesis Evaluation algorithm of Manufacture Resources
       1. 3.1. Weighing Measurement of Various Index
       2. 3.2. Comprehensive Sequencing of Manufacture Resources
    5. 4. Conclusion
    6. References
27. User Interfaces for Service Oriented Architectures
    1. Abstract
    2. 1. Motivation
    3. 2. Approach
       1. 2.1. Process
       2. 2.2. Interface
    4. 3. User interfaces for services
       1. 3.1. Interfaces for process overview and control
       2. 3.2. Interfaces for interactive services
          1. 3.2.1. Simple Service User Interfaces
          2. 3.2.2. Complex Service User Interfaces
          3. 3.2.3. Multi-Service User Interfaces
          4. 3.2.4. Service Application User Interfaces
    5. 4. Interfaces for an SOA-based Portal
    6. 5. Future work
    7. 6. Acknowledgements
    8. References
28. A Roaming Vehicle for Entity Relocation
    1. Abstract
    2. 1.0. Introduction
    3. 2.0. Platform design
    4. 3.0. Control circuit architecture
    5. 4.0. Control algorithm
    6. 5.0. Experimentation Results
    7. 5.1. Load versus time of travel
    8. 5.2. Load versus current
    9. 5.3. Station stopping response distances
    10. 6.0. Conclusion
    11. Acknowledgements
    12. References
29. A system for automatic end-quality assessment of vacuum cleaner motors
    1. Abstract
    2. 1. Introduction
    3. 2. System architecture
    4. 3. Diagnostic modules
    5. 4. Diagnostic system performance
    6. 5. Diagnostic system evaluation
    7. 6. Conclusion
    8. Acknowledgements
    9. References
30. Agent technology used for monitoring of automotive production
    1. Abstract
    2. 1. Current situation
       1. 1.1. Software support in automotive plants
       2. 1.2. State of the art for software agents in manufacturing environments
    3. 2. Research and application development steps
       1. 2.1. Closed control loops and connection of monitoring and order management
       2. 2.2. Virtual Startup
    4. 3. Agent based production monitoring
    5. 4. Conclusion
    6. References
31. An Intelligent System for Manufacturing Fibre Optic Components
    1. Abstract
    2. 1. Introduction
    3. 2. Problem definition
    4. 3. Laser-to-fibre coupling algorithm
    5. 4. Evolutionary algorithm
    6. 5. Experimental settings and results
       1. 5.1. Experimental set up
       2. 5.2. EA settings
       3. 5.3. Results
    7. 6. Conclusions
    8. Acknowledgements
    9. References
32. Automatic detection of Mediterranean water eddies from satellite imagery of the Atlantic Ocean
    1. Abstract
    2. 1. Introduction
    3. 2. Automatic identification of oceanic eddies
    4. 3. Problem domain
    5. 4. Proposed algorithm
       1. 4.1. SST image pre-processing
       2. 4.2. Numerical feature extraction
       3. 4.3. ANN meddy identification
    6. 5. Experimental settings and identification results
       1. 5.1. Experimental set up and algorithm implementation
       2. 5.2. Experimental results
    7. 6. Discussion
    8. 7. Conclusions and further work
    9. Acknowledgements
    10. References
33. Complementary agents for intelligent cluster sensors technology
    1. Abstract
    2. 1. A Challenging technology
    3. 2. Systems characteristics
    4. 3. Sensor Structure
    5. 4. Intelligent agents
    6. 5. Single-agent and Multi or hybrid agent systems
    7. 6. Example of agent’s functionalities
    8. 7. Intelligent sensor functionalities
       1. 7.1. Compensation functionality
       2. 7.2. Computing functionality
       3. 7.3. Communication functionality
       4. 7.4. Validation functionality
       5. 7.5. Integration functionality
       6. 7.6. Data fusion functionality
    9. 8. Practical expectations for intelligent sensors
       1. 8.1. Sensor Master/clusters set-up for single/hybrid processes
       2. 8.2. In process Parameter evaluation
       3. 8.3. Extreme environment sensors for manufacturing processes and cutting interfaces
       4. 8.4. Plug and Play sensors with standardization of interfaces
    10. 9. Conclusion
    11. Acknowledgment
    12. References
34. Fuzzy Logic Modelling of a Powder Coating System
    1. Abstract
    2. 1. Introduction
    3. 2. Fuzzy modelling and the design methodology for the fuzzy-logic based powder coating system
    4. 3. Experimental design and material setup
    5. 4. Assessing powder deposition using response surface method
    6. 5. The fuzzy-logic based powder coating system
       1. 5.1. Performance evaluation of the fuzzy-logic based powder coaling system
    7. 6. Conclusion
    8. Acknowledgement
    9. References
35. Image segmentation using fuzzy min-max neural networks for wood defect detection
    1. Abstract
    2. 1. Introduction
    3. 2. Image segmentation method
       1. 2.1. Seed selection process
       2. 2.2. Input patterns
       3. 2.3. Fuzzy min-max neural network for image segmentation
          1. 2.3.1. FMMIS learning algorithm
       4. 2.4. Output of the FMMIS
    4. 3. Methods
    5. 4. Experimental results
    6. 5. Conclusions
    7. Acknowledgements
    8. References
36. Integrating human personnel, robots, and machines in manufacturing plants using ubiquitous augmented reality and smart agents
    1. Abstract
    2. 1. Introduction
    3. 2. Related work
    4. 3. Semantic network for manufacturing plants
       1. 3.1. The Smart-Connected-Control Platform
       2. 3.2. Integrating human personnel
    5. 4. High-level architecture
    6. 5. Application areas
       1. 5.1. Advanced just-in-time maintenance
       2. 5.2. Customized production
       3. 5.3. Error reporting, diagnosis and self-healing
    7. 6. Conclusions
    8. Acknowledgements
    9. References
37. Neural Networks in Automated Visual Inspection of Manufacturing Parts
    1. Abstract
    2. 1. Introduction
    3. 2. Higher-order neural networks
    4. 3. Coarse coding representation
    5. 4. System structure
    6. 5. Genetic algorithms in HONN topology optinnisation
    7. 6. Results
    8. 7. Conclusions
    9. References
38. Petri net controller synthesis using theory of regions
    1. Abstract
    2. 1. Introduction
    3. 2. PN controller design problem w.r.t. a desired behavior
       1. 2.1. The desired controlled behavior
       2. 2.2. The PN controller design problem
    4. 3. Control places design
       1. 3.1. Some basic relations
       2. 3.1. Pure control places
       3. 3.3. Impure control places
    5. 4. An actual deadlock problem in a railway network
    6. 5. Conclusion
    7. Acknowledgement
    8. References
39. Quality Control of High Pressure Die Casting using a Neural Network
    1. Abstract
    2. 1. Introduction
    3. 2. High Pressure Die Casting
    4. 3. Modelling the High Pressure Die Casting Process
    5. 4. Modelling Results and Discussion
    6. 5. Proposed Control Mechanism
    7. 6. Conclusion
    8. 7. Future Work
    9. 7. Acknowledgment
    10. References
40. Robot kinematic calibration using Genetic Algorithms
    1. Abstract
    2. 1. Introduction
    3. 2. Robot calibration problem
       1. 2.1. Principle
       2. 2.2. The Denavit-Hartenberg model
    4. 3. Genetic Algorithms
    5. 4. Robot error model
    6. 5. Calibration algorithm
    7. 6. Implementation
       1. 6.1. Four different Types of configurations
       2. 6.2. Finding the best parameters
    8. 7. A Case Study
    9. 8. Conclusions
    10. Acknowledgement
    11. References
41. A performance evaluation approach of an inventory system with batch orders
    1. Abstract
    2. 1. Introduction
    3. 2. The inventory system
    4. 3. Performance evaluation
       1. 3.1. The manufacturing plant model
       2. 3.2. The transport system model
       3. 3.3. Order to delivery lead-time and inventory on order
       4. 3.4. Total inventory cost estimation
    5. 4. Numerical results
    6. 5. Conclusion
    7. 6. Acknowledgement:
    8. References
42. Applications of machine learning in manufacturing
    1. Abstract
    2. 1. Introduction
    3. 2. Machine learning approaches to classification learning
       1. 2.1. Inductive learning
       2. 2.2. Instance-based learning
       3. 2.3. Neural networks
       4. 2.4. Genetic algorithms
    4. 3. Applications of machine learning techniques in manufacturing
    5. 4. Conclusions
    6. Acknowledgements
    7. References
43. Applications of RULES-3 Induction System
    1. Abstract
    2. 1. Introduction
    3. 2. RULES-3 Inductive Learning Algorithm
    4. 3. Applications of RULES-3 Algorithm
       1. 3.1. Industrial Visual Inspection
       2. 3.2. Banknote Recognition
       3. 3.3. Signature Recognition
       4. 3.4. Number plate Recognition
       5. 3.5. Inspection of ceramic tiles
       6. 3.6. Rat code Recognition
       7. 3.7. Dynamic System Identification
       8. 3.8. Data Mining
       9. 3.9. Cell Formation Application
       10. 3.10. Other Applications
    5. 4. Conclusion
    6. References
44. Correlation Analysis of Environmental Pollutants and Meteorological Variables Applying Neuronal Networks
    1. Abstract
    2. 1. Introduction
       1. 1.1. Principal air pollutants features
       2. 1.2. The Air Quality Index (AQI)
    3. 2. Model and Theoretical Fundament
       1. 2.1. Variable definition
       2. 2.2. Proposed Model
       3. 2.2.1. Data Base, and Pre-processing
       4. 2.2.2. Clustering Method
       5. 2.2.3. Classifier Design
       6. 2.2.4. Classifier Optimization
    4. 3. Experimental Results
       1. 3.1. Data Clustering for SO2 and PM10 concentrations
       2. 3.2. AQI estimation for SO2, PM10 and Meteorological variables
    5. 4. Conclusions
    6. Acknowledgements
    7. References
45. Early design analysis using rough set theory
    1. Abstract
    2. 1. Introduction
    3. 2. Design Concepts Analysis
    4. 3. Rough Sets Theory and Unavailable Information
       1. 3.1. Basic notions
       2. 3.2. Unavailable information
    5. 4. An Approach to the Handling of Non-Relevant Attributes in Design Concepts Analysis
    6. 5. A Case Study
       1. 5.1. Application of Dissimilar Objects Algorithm
       2. 5.2. A Comparative Study
    7. 6. Conclusions
    8. References
46. Hypermedia-based adaptive expert system for advanced performance support
    1. Abstract
    2. 1. Introduction
    3. 2. Advanced performance support systems
    4. 3. Integrated fault data model for diagnostic expert systems
    5. 4. Adaptive retrieval of hypermedia-based technical information using data semantics
       1. 4.1. Semantic data model for technical information
       2. 4.2. Stereotype model for user knowledge
       3. 4.3. User knowledge-based strategy for adaptive support using conditional semantic rules
    6. 5. Integrated adaptive diagnostic expert system for a forklift truck
    7. 6. Conclusions
    8. References
47. Intelligent SERM (Strategic Enterprise Resource Management)
    1. Abstract
    2. 1. Introduction
    3. 2. A brief overview of SERM
    4. 3. Intelligent agents
    5. 4. SERM agents
    6. 5. Conclusion
    7. Acknowledgement
    8. References
48. Performance analysis of two-machine continuous-flow model with delay Iyad Mourani, Sophie Hennequin, Xiaolan Xie
    1. Abstract
    2. 1. Introduction
    3. 2. Production line with delay
    4. 3. Performance analysis
    5. 4. Numerical results
       1. A. Case of exponential distributed random variables
       2. B. Case of random variables of Weibull distributions
    6. 5. Conclusions
    7. Acknowledgement
    8. References
49. RULES-IS: An Immune-network inspired machine learning algorithm
    1. Abstract
    2. 1. Introduction
    3. 2. Immune-System-inspired Rule Extraction Algorithm
       1. 2.1. Representation of Antibody and Antigen
       2. 2.2. Immune Network
       3. 2.3. Matching Algorithm
       4. 2.4. Antibody Generation via Combination
       5. 2.5. Antibody Generation from Antigen
       6. 2.6. Decomposition
       7. 2.7. Incremental Learning Memory
       8. 2.8. Overall Algorithm
    4. 3. Results and Discussion
       1. 3.1. Complete Data
       2. 3.1.1. Season Classification Problem
       3. 3.1.2. Flower Identification Problem
       4. 3.1.3. Iris Data Set
       5. 3.2. Incomplete Data
    5. 4. Conclusions and Further Work
    6. Acknowledgements
    7. References
50. Semantic modelling of product support knowledge
    1. Abstract
    2. 1. Introduction
    3. 2. Background and related work
       1. 2.1. Product support
       2. 2.2. Product support and knowledge engineering
    4. 3. Knowledge modelling approach
       1. 3.1. Product support knowledge sets
       2. 3.2. From data to knowledge
       3. 3.3. Conceptual modelling
       4. 3.3.1. First phase
       5. 3.3.2. Second phase
       6. 3.4. Knowledge base and product support documents
       7. 3.5. Implementation
    5. 4. Conclusions and future work
    6. Acknowledgements
    7. References
51. SO2 concentrations forecasting for different hours in advance for the city of Salamanca, Gto., Mexico.
    1. Abstract
    2. 1. Introduction
    3. 2. Methodology
       1. 2.1. Pre-processing
       2. 2.2. General Description of GRNN
       3. 2.3. GRNN Training
       4. 2.4. GRNN Simulation
    4. 3. Results
    5. 4. Conclusions
    6. 5. Further Work
    7. References
52. Towards interactive analysis of virtual manufacturing simulations
    1. Abstract
    2. 1. Introduction
    3. 2. Assumptions
    4. 3. An overall framework
    5. 4. Modeling the manufacturing system
    6. 5. Preliminary Tier 1 calculations
    7. 6. Pre-simulation, real-time visualization, and interactive analysis
    8. 7. Conclusions
    9. References
53. An integrated knowledge-based system for sheet metal processing
    1. Abstract
    2. 1. Introduction
    3. 2. The modular structure of the system
       1. 2.1. Modeling module
       2. 2.2. Nesting module
       3. 2.3. Process-planning module
       4. 2.4. NC-programming module
       5. 2.5. Simulation & reporting module
    4. 3. The knowledge base of the system
       1. 3.1. The Nesting Rule Base
       2. 3.2. The Optimization Algorithm Library
          1. 3.2.1. Sheet metal nesting algorithm
          2. 3.2.2. Punching tool sequencing algorithm
          3. 3.2.3. Cutting sequencing algorithm
       3. 3.3. The Process Rule Base
    5. 4. Case study
    6. 5. Conclusions
    7. Acknowledgement
    8. References
54. Artificial intelligence methods a challenge for the modern polymer chemistry
    1. Abstract
    2. 1. Introduction
    3. 2. Polymer structures and properties
       1. 2.1. Polymer structure
       2. 2.2. Polymer properties
    4. 3. Designee solution
       1. 3.1. Genetic algorithm approach
       2. 3.2. Multiobjective Tabu Search
       3. 3.3. Neural network approach
    5. 4. Results and discussions
    6. 5. Conclusions
    7. Acknowledgement
    8. References
55. Construction using combined materials - possibilities and limits
    1. Abstract
    2. 1. Introduction
    3. 2. Material choice - the design engineer’s task
    4. 3. Using plastic deformation to increase load-bearing capacity
    5. 4. Combining composites and metal in the design of high speed air separators
    6. 5. Development of ceramic ventilators for hot gas circulation at temperatures up to 1350°C
    7. 6. Conclusion
    8. Acknowledgement
    9. 7. References
56. Evolutionary Neuro-Fuzzy Modeling in Parametric Design
    1. Abstract
    2. 1. Introduction
    3. 2. Background issues
    4. 3. The Proposed Methodology
       1. 3.1. Design entities and associative relations
       2. 3.2. Solution search with GAs
       3. 3.3. Transition to fuzzy model with ANN
    5. 4. Conclusions
    6. Acknowledgements
    7. References
57. Intelligent Conceptual Design of Robot Grippers for Assembly Tasks
    1. Abstract
    2. 1. Introduction
    3. 2. Conceptual Design and Configuration Problems
    4. 3. Intelligent Gripper Design System
       1. 3.1. Importing CAD Models
       2. 3.2. Recognising Geometric Structures
          1. 3.2.1. Reference Box
          2. 3.2.2. Solid Object Checkers
       3. 3.3. Determining Information about the Imported Components
       4. 3.4. Grouping Components
       5. 3.5. Generating the Optimum Gripping Solution
    5. 4. Example Application
    6. 5. Conclusion and Further Work
    7. Acknowledgements
    8. References
58. Knowledge-based and requirements-driven product development
    1. Abstract
    2. 1. Introduction
    3. 2. The knowledge society
       1. 2.1. Innovation and vision
       2. 2.2. PRIME
    4. 3. Starting point: requirements
       1. 3.1. Requirement engineering
       2. 3.2. Configuration and change management
    5. 4. Intelligent design support
    6. 5. Conclusions
    7. Acknowledgement
    8. References
59. Participatory innovative design technology tools for enhancing production systems and environment
    1. Abstract
    2. 1. Introduction
    3. 2. Technologies supporting participatory design
       1. 2.1. Video Exposure Monitoring (VEM)
       2. 2.2. Virtual Environments (VEs)
       3. 2.3. Participation
    4. 3. Application examples
       1. 3.1. Case 1: Steel factory
       2. 3.2. Case 2: Medium size factories
       3. 3.3. Case 3: Vehicle manufactures
       4. 3.4. Case 4: Contamination problems in production systems
    5. 4. Application fields and future development
    6. 5. Conclusions
    7. Acknowledgements
    8. References
60. Statistics supporting the design process via Kansei Engineering
    1. Abstract
    2. 1. Introduction
    3. 2. Kansei Engineering methodology
    4. 3. Examination of the semantic space
    5. 4. Prediction Models
    6. 5. Conclusions
    7. Acknowledgement
    8. References
61. A case-based reasoning of computer-aided process planning system for rotational parts
    1. Abstract
    2. 1. Introduction
    3. 2. Background and previous related research
    4. 3. The case-based approach
    5. 4. Proposed CAPP
       1. 4.1. Description of the proposed CBR system
    6. 5. Components of the case-based reasoning (CBR) system
       1. 5.1. Parts database and similarity system
       2. 5.2. Case retrieval
       3. 5.3. Case adaptation
    7. 4. Conclusions
    8. Acknowledgements
    9. References
62. A knowledge-based system to schedule multi-skilled labor with variable demand
    1. Abstract
    2. 1. Introduction
    3. 2. Problem definition
    4. 3. Shift-assignment model
    5. 4. The proposed knowledge-based system
    6. 5. Computational results
    7. 6. Conclusion
    8. 7. Future work
    9. Acknowledgments
    10. References
63. Application of reinforcement learning to a mobile robot in reaching recharging station operation
    1. Abstract
    2. 1. Introduction
    3. 2. Background/literature review
    4. 3. System implementation
    5. 4. Experiments
       1. 4.1. Reinforcement Learning Rate
       2. 4.2. RL vs. non-AI control
    6. 5. Results and analysis
       1. 5. I RL rate
       2. 5.2. RL vs. non-Aï control
    7. 6. Conclusions
    8. References
64. Intelligent manufacturing strategy selection
    1. Abstract
    2. 1. Introduction
    3. 2. Literature review
    4. 3. Causal strategy selection
       1. 3.1. Game theory
       2. 3.2. Dynamic causal mining
       3. 3.3. Causal game theory
    5. 4. An illustrative example
    6. 5. Conclusion
    7. Acknowledgement
    8. Reference
65. Operating policy generation using a reinforcement learning agent in a melt facility
    1. Abstract
    2. 1. Overview
    3. 2. Problem Formulation
       1. 2.1. Overview
       2. 2.2. Metal demand
       3. 2.3. State definition
       4. 2.4. Action Selection
    4. 3. RL agent design
       1. 3.1. General structure
       2. 3.2. Agent reward
    5. 4. Results and discussion
    6. 5. Conclusion
    7. References
66. Quantitative utilities for the ‘intelligent’ definition of CNC programs for the high speed milling of complex parts
    1. Abstract
    2. 1. Introduction
    3. 2. CAM planning process
       1. 2.1. Analysis of the stability of process
       2. 2.2. Force definition
    4. 3. Example
    5. 4. Conclusions
    6. Acknowledgments
    7. References
67. Using artificial neural networks for process planning of cylindrical machined components
    1. Abstract
    2. 1. Introduction
    3. 2. Background and previous related research
       1. 2.1. Applications of expert systems in CAPP
       2. 2.2. Applications of fuzzy reasoning in CAPP
       3. 2.3. Applications of neural networte in CAPP
    4. 3. Proposed CAPP methodology for process selection
       1. 3.1. Objectives and scope
       2. 3.2. Strategy for development of the neural network architecture
          1. 3.2.1. Identification of network input and output variables
          2. 3.2.2. Preparation of the set of training examples
          3. 3.2.3. Designing, training and validating of the neural network
          4. 3.2.3. Designing, training and validating of the neural network
       3. 3.3. Illustrative examples and results
    5. 4. Conclusions
    6. Acknowledgements
    7. References
68. Active Interpolated Surfaces for Robotic Arm Control: The Potential for High Speed Implementation in FPGA
    1. Abstract
    2. 1. Introduction
    3. 2. Method
       1. 2.1. Definition of the problem
       2. 2.2. Implementation of the interpolated surfaces
       3. 2.3. 3-dimensional virtual model using Webots robot simulation package
       4. 2.4. Modelling using a PUMA robot data
       5. 2.5. Active Surface interpolation algorithm
       6. 2.6. Adaptation - switching sides
    4. 3. Results
    5. 4. Discussion
    6. Acknowledgements
    7. References
69. Design and Implementation of a Web Based Mobile Robot
    1. Abstract
    2. 1. Introduction
    3. 2. Developed Web Based Mobile Hobot: SUNAR
       1. 2.1. Vehicle Motion System
       2. 2.2. Camera Motion System
       3. 2.3. Communication System
       4. 2.4. Control Center
       5. 2.5. Software Developed
       6. 2.6. Vision System of SUNAR
    4. 3. Results and Conclusions
    5. References
70. Docking of Autonomous Vehicles: A Comparison of Model-Independent Guidance Methods
    1. Abstract
    2. 1. Introduction
    3. 2. Line-of-Sight Based Task-Space Sensing
    4. 3. Model-Independent Guidance Methodologies
       1. 3.1. Guidance Based on Passive Sensing
       2. 3.2. Guidance Based on Active Sensing
    5. 4. Simulations
       1. 4.1. Set-up and Procedure
       2. 4.2. Examples
    6. 5. Discussion and Conclusions
    7. Acknowledgements
    8. References
71. Simulation and Optimisation of a Tendon-Based Stewart Platform
    1. Abstract
    2. 1. Introduction
       1. 1.1. The Challenge of a Tendon-based Stewart Platform
    3. 2. Simulation of controllable workspace
       1. 2.1. The kinematic model
          1. 2.1.1. Assumptions
          2. 2.1.2. Force-Torque-Equilibrium
       2. 2.2. The simulation tool
       3. 2.3. Controllable workspace of the prototype
    4. 3. Optimisation
       1. 3.1. Reduction of mechanical fasteners of the platform
       2. 3.2. Tetraeder structure
    5. Conclusions / Further Work
    6. Acknowledgements
    7. References
72. Visual servoing of a robotic manipulator based on fuzzy logic control for handling fabric lying on a table
    1. Abstract
    2. 1. Introduction
    3. 2. The robot sewing process
       1. 2.1. The control system
       2. 2.2. Image features extraction
    4. 3. Experimental results
    5. 4. Conclusions
    6. Acknowledgements
    7. References
73. A Computer Aided Design System for Product Oriented Manufacturing Systems Reconfiguration
    1. Abstract
    2. 1. Introduction
    3. 2. Product Oriented Manufacturing Systems
    4. 3. Computer Aided Design System for POMS
       1. 3.1. CADS POMS components and structure
       2. 3.2. Fundamental concepts and data sets
    5. 4. Conclusion
    6. Acknowledgements
    7. References
74. A Distributed Control Environment for Reconfigurable Manufacturing
    1. Abstract
    2. 1. Introduction
    3. 2. Reconfiguration requirements on lower level control
       1. 2.1. Requirements introduced through the domain
       2. 2.2. Reconfiguration process requirements
       3. 2.3. Requirements for engineering of reconfiguration applications
    4. 3. IEC 61499 as a reference model for reconfigurable distributed control at real-time level
       1. 3.1. Main characteristics of IEC 61499
       2. 3.2. Management interface of IEC 61499 devices
    5. 4. Engineering & runtime environment for distributed automation and control systems
       1. 4.1. Approach for controlled evolution
       2. 4.2. Modelling of control and evolution control
       3. 4.3. Execution environment for control and evolution control applications
          1. 4.3.1. Description of the execution environment
    6. 5. Demonstration prototype
    7. 6. Summary and conclusions
    8. Acknowledgements
    9. References
75. A multi-agent scheduler for reconfigurable manufacturing systems
    1. Abstract
    2. 1. Introduction
    3. 2. Scheduling challenges in RMS
       1. 2.1. Layout
       2. 2.2. Performance measures
       3. 2.3. Distributed Scheduling
       4. 2.4. RMS Scheduler Requirements
    4. 3. Multi-agent scheduling
       1. 3.1. Multi-agent systems
       2. 3.2. Resource allocation
    5. 4. A Multi-Agent Scheduler for RMS
       1. 4.1. Overview
       2. 4.2. The agents
       3. 4.3. Allocation of tasks
    6. 5. Simulation tests
    7. 6. Conclusions
    8. Acknowledgements
    9. References
76. Custom-Fit: A knowledge-based manufacturing system enabling the creation of Custom-Fit Products to improve the Quality of Life
    1. Abstract
    2. 1. Introduction
    3. 2. Applications
    4. 3. Objectives
       1. 3.1. Technical & Scientific Objectives
       2. 3.2. Social & Policy Objectives
       3. 3.3. Core
       4. 3.4. Implication on Business & Consumer
          1. 3.4.1. Capturing Technology
          2. 3.4.2. Design technology and systems
          3. 3.4.3. Rapid manufacturing processes, machines and materials
    5. 4. Conclusions
    6. Acknowledgements
    7. References
77. Hybrid Manufacturing Technologies
    1. Abstract
    2. 1. Motivation
    3. 2. Charakterisation of Hybrid Manufacturing Methods
    4. 3. Thermally Assisted Hybrid Processes
    5. 4. Chemically Assisted Hybrid Processes
    6. 5. Mechanically Assisted Hybrid processes
    7. 6. Conclusion
    8. Appendix A. Authors
    9. References
78. Reconfigurable Robots towards the Manufacturing of the Future
    1. Abstract
    2. 1. Introduction
    3. 2. Robot Platforms
    4. 3. Mechatronic modules
    5. 4. Design, motion planning and control aspects
    6. 5. Challenges and perspectives
    7. 6. Conclusions
    8. 7. Acknowledgements
    9. References
79. Robotised nano manufacturing: current developments and future trends
    1. Abstract
    2. 1. Introduction
    3. 2. Current developments
       1. 2.1. Nano motion and positioning
       2. 2.2. SPM-based nano vision and manipulation
       3. 2.3. Nano gripping and 3D handling
    4. 3. Future trends
       1. 3.1. Object-oriented nano manipulation
       2. 3.2. Versatile 3D nano handling
       3. 3.3. Automatic or semi-automatic 3D nano assembly
       4. 3.4. Nano rapid prototyping and rapid tooling
       5. 3.5. Hybrid nano handling and manufacturing
    5. 4. Conclusion
    6. Acknowledgements
    7. References
80. Simulation of manufacturing processes using multi-agent technology
    1. Abstract
    2. 1. Introduction
    3. 2. Agent-based planning and simulation
    4. 3. Time Synchronization
       1. 3.1. Confirmed Time Windows Synchronization
    5. 4. System architecture
       1. 4.1. Simulation agents
          1. 4.1.1. Agent structure
          2. 4.1.2. Contracting and Negotiation
       2. 4.2. Time synchronization and control
       3. 4.3. Visualization and data evaluation
          1. 4.3.1. Logical Visio
          2. 4.3.2. Analytical Visio
          3. 4.3.3. 3D Visio
          4. 4.3.4. Log Manager
    6. 5. Conclusions and future work
    7. 6. Acknowledgements
    8. References
81. The reality of functionally graded material products
    1. Abstract
    2. 1. Introduction1
    3. 2. Rapid Manufacturing
       1. 2.1. Monomaterial
       2. 2.2. Multimaterial
    4. 3. Functionally Graded Materials
       1. 3.1. History of Functionally Graded Materials
       2. 3.2. Rapid Manufacturing and FGM
    5. 4. Modeling FGM structures
    6. 5. Innerspace principles
       1. 5.1. Domains
       2. 5.2. Props
          1. ISO prop
          2. Vari prop
          3. Distribution functions
          4. Absolute distribution junction
          5. Relative distribution function
    7. 6. Conclusion
    8. References
82. Acoustic Holography in Solids for Computer-Human Interaction
    1. Abstract
    2. 1. Introduction
    3. 2. Acoustic source localisation methods
    4. 3. Optic Holography
    5. 4. Acoustic Holography
    6. 5. Rayleigh-Sommerfeld Algorithm
    7. 6. Material and applications
    8. 8. Experimental and simulation results
    9. 7. Conclusion
    10. Acknowledgements
    11. References
83. Acoustic pattern registration for a new type of human-computer interface
    1. Abstract
    2. 1. Introduction
    3. 2. Acoustic signal pattern registration and matching
    4. 3. Experimentation
    5. 4. Conclusion
    6. Acknowledgements
    7. References
84. Expressive Gesture in Tangible Acoustic Interfaces
    1. Abstract
    2. 1. Introduction
    3. 2. The EyesWeb 4 platform
    4. 3. Expressive gesture in TAIs
    5. 4. TAI interfaces in EyesWeb
    6. Conclusions and future work
    7. Acknowledgements
    8. References
85. Hardware structure of tangible acoustic interface systems
    1. Abstract
    2. 1. Introduction
    3. 2. Operating principle of tangible acoustic interfaces
    4. 3. Acoustic Sensors and signal conditioning
    5. 4. Embedded Digital Signal Processing (DSP) system
    6. 5. Multi-channel AD converter and interface with DSP
    7. 6. Results and conclusion
    8. Acknowledgements
    9. References
86. Impact Localisation Techniques for Tangible Acoustic Interfaces
    1. Abstract
    2. 1. Introduction
    3. 2. TDOA Approach
    4. 3. LTM Approach
    5. 4. Implementation
    6. 5. Conclusion
    7. Acknowledge ments
    8. References
87. In-air passive acoustic source localization in reverberant environments
    1. Abstract
    2. 1. Introduction
    3. 2. Methods used in passive source localization
    4. 3. TDOA method based on PHAT
       1. 3.1. Mathematical model of TDOA based on cross correlation
       2. 3.2. The phase transform
    5. 4. MATLAB simulation results
    6. 5. Experimental tests
    7. 6. Conclusions
    8. Acknowledgements
    9. References
88. A framework for the integration of a trajectory pre-shaping technique into an advanced machine tool system
    1. Abstract
    2. 1. Introduction
    3. 2. Overview of the Analytical Technique
       1. 2.1. General characteristics of the technique
       2. 2.2. Requirements
       3. 2.3. Outline of design with velocity loop model
    4. 3. Integrating Into a Machine Tool System
       1. 3.1. Preparing motion profiles
       2. 3.2. Implementing trajectory pre-shaping
       3. 3.3. Obtaining parametric models
       4. 3.4. The integration of main components
          1. 3.4.1. Core level
          2. 3.4.2. Middle level
          3. 3.4.3. Top level
    5. 6. Conclusion
    6. References
89. Accurate 3D modelling for automated inspection: A stereo vision approach
    1. Abstract
    2. 1. Introduction
    3. 2. Disparity estimation algorithms
       1. 1.1. Probabilistic measure
       2. 1.2. Optimization and interpolation
    4. 3. Experimental outcomes
    5. 4. Conclusion
    6. 5. Acknowledgment
    7. References
90. Best practice development within a manufacturing enterprise collaboration framework
    1. Abstract
    2. Keywords
    3. 1. Introduction
    4. 2. Best practice
    5. 3. Best practice development and learning
    6. 4. ICT and collaborative manufacturing
    7. 5. Findings and discussion
    8. 6. Conclusion
    9. Acknowledgement
    10. Reference
91. Development of a Smart Supervisory Control System in a Sugar Mill Crystallisation Stage
    1. Abstract
    2. 1. Introduction
    3. 2. The Smart Supervisory Control Framework
       1. 2.1. Modular architecture
       2. 2.2. Standard layer
       3. 2.3. Discourse semantics
       4. 2.4. Meta-consequent
    4. 3. Predictive models
       1. 3.1. Crystallisation stage overview
       2. 3.2. Syrup rate prediction
       3. 3.3. Individual empirical vacuum pan models
       4. 3.4. Pan stage massecuite model
       5. 3.5. Stock tank models
    5. 4. Discussion and Conclusion
    6. Acknowledgements
    7. References
92. From simulation to VR based simulation and testing
    1. Abstract
    2. 1. Introduction
       1. 1.1. VR for broad consumption
       2. 1.2. Simulation
    3. 2. VR as simulation tool for design product testing
       1. 2.1. Beta testing
       2. 2.2. Simulation as a tool of hardware/software testing
       3. 2.3. What is missing from Virtual Reality simulation
    4. 3. Design product VR simulation and testing
    5. 4. Virtual Reality simulation implementation
       1. 4.1. Designing of the VR assembly simulation
       2. 4.2. Building behavior model of the VA simulation
       3. 4.3. Input and control peripheral devices
    6. 5. Conclusion
    7. References
93. Identifying defects on plywood using a minimum distance classifier and a neural network
    1. Abstract
    2. 1. Introduction
    3. 2. The minimum distance classifier (MDC)
       1. 2.1. Calculating the weights of the MDC
    4. 3. Neural network (NN)
       1. 3.1. Feedforward calculations
       2. 3.2. Error back-propagation claculations
    5. 4. Wood veneer inspection application
    6. 5. Training the classifiers
       1. 5.1. Training the wood veneer inspection minimum distance classifier (WVIMDC)
       2. 5.2. Training the wood veneer inspection neural network (WVINN)
    7. 6. Conclusion
    8. Acknowledgement
    9. References
94. Issues concerned with the spatial optimisation of shapes
    1. Abstract
    2. 1.0. Introduction
    3. 2.0. Problem Definition
    4. 3.0. Objective Function
    5. 4.0. Overlap between shapes
    6. 5.0. Optimisation method
    7. 6.0. Initial Configuration
    8. 7.0. Conclusion
    9. Acknowledgements
    10. Bibliography
95. Optimisation of nesting using Simulated Annealing
    1. Abstract
    2. 1.0. Introduction
    3. 2.0. The Markov chain length
    4. 3.0. The Cooling Schedule
    5. 4.0. The move set
    6. 5.0. The objective function
    7. 6.0. Conclusion
    8. Acknowledgements
    9. References
    10. Bibliography
96. Rapid Tooling Process Chain
    1. Abstract
    2. 1. Introduction
    3. 2. CAD construction
    4. 3. Data Preparation
    5. 4. DMLS Building Process
    6. 5. Finishing
    7. 6. Final Sintered Products
    8. 7. Conclusion
    9. 8. References
97. Reverse engineering and rapid prototyping for new orthotic devices
    1. Abstract
    2. 1. Introduction
       1. 1.1. Reverse engineering
       2. 1.2. Biomedical applications of reverse engineering
    3. 2. Methods
       1. 2.1. Data Acquisition
       2. 2.2. Pre-processing
       3. 2.3. Contours and surface fitting
       4. 2.4. CAD Model creation and data analysis
    4. 3. Results
       1. 3. I. New personalized elbow orthosis
          1. 3.1.1. Elbow CAD model based on laser scanning “in vivo”
          2. 3.1.2. Elbow CAD model based on laser scanning of a wax model.
          3. 3.1.3. Manufacturing of the Elbow Orthosis using Rapid Prototyping
       2. 3.2. New personalized ankle-foot orthosis
    5. 4. Conclusion
    6. Acknowledgements
    7. References
98. Towards rapid sheet metal forming
    1. Abstract
    2. 1. Introduction
    3. 2. Dieless forming of sheet metals
       1. 2.1. Mechanics of ISF
       2. 2.2. Equipment and software for ISF
       3. 2.3. Accuracy of incremental ISF
       4. 2.4. Economics of lSF
       5. 2.5. Research issues in ISF
    4. 3. Forming Of Sheetmetal using Reconfigura ble Tool
       1. 3.1. Mechanics of sheetmetal forming using reconfigurable tooling
       2. 3.2. Equipment for sheetmelal forming using reconfigurable tooling
       3. 3.5. CAD/CAM system for sheetmetal forming using reconfigurable tooling
       4. 3.6. Accuracy of sheetmetal forming using reconfigurable tooling
       5. 3.7. Economics and sustainability issues in sheetmelal forming using reconfigurable tooling
       6. 3.8. Research issues in sheetmetal forming using reconfigurable tooling
    5. 4. Conclusions
    6. Acknowledgement
    7. References
99. Agent-based multiple supplier tool management system
    1. Abstract
    2. 1. Introduction
    3. 2. Turbine blade manufacturing
    4. 3. Generic agent shell
    5. 4. Multi-agent tool management system
       1. 4.1. MATMS agent communication
       2. 4.2. MATMS functioning
    6. 5. Conclusions
    7. Acknowledgements
       1. References
100. A correlation between the friction coefficient and the roughness of rolls in a hot flat rolling
     1. Abstract
     2. 1. Introduction
     3. 2. Experimental tests
     4. 3. Experimental results
     5. 4. FEM analysis
     6. 5. Conclusion
     7. Acknowledgements
        1. References
101. Advanced Hybrid Mechatronic Materials for ultra precise and high performance machining systems design
     1. Abstract
     2. 1. Introduction
     3. 2. Requirements and possible solutions
        1. 2.1. Reduction of Vibration in a low frequency domain (0-50 Hz)
        2. 2.2. Reduction of Vibration in a high frequency domain (50-1000 Hz)
        3. 2.3. Reduction of structura! displacements due to thermal effects or elastic deformations
     4. 3. Passive solutions for the reduction of vibrations
     5. 4. Active solutions for the reduction of vibrations
        1. 4.1. Tuned Absorbers
        2. 4.2. Smart Platform
     6. 5. Solutions for thermal deformation problems
        1. 5.1. Fiber Bragg Gratings
        2. 5.2. Extrinsic Fabry Perot Interferometer Sensors
     7. 6. Conclusions
     8. Acknowledgements
        1. References
102. Advanced ultrasonic system for high performance composite laminate nondestructive evaluation
     1. Abstract
     2. 1. Introduction
     3. 2. Ultrasonic Nondestructive Evaluation System
     4. 2. Materials and experimental work
        1. 2.1. Materials
        2. 2.2. Mechanical testing
        3. 2.3. Ultrasonic testing
     5. 3. Results and discussion
        1. 3.1. Mechanical testing results
        2. 3.2. Ultrasonic non-destructive evaluation results
           1. 3.2.1. UT image generation
           2. 3.2.2. UT image analysis
     6. 4. Conclusions
     7. Acknowledgements
     8. References
103. Application of Artificial Neural Networks in the prediction of quality of wastewater treated by a biological plant
     1. Abstract
     2. 1. Introduction
     3. 2. The biological plant
     4. 3. Scope and ANN architectures
     5. 4. Results and discussion
     6. 5. Conclusions
     7. References
104. Chip form monitoring in turning based on neural network processing of cutting force sensor data
     1. Abstract
     2. 1. Introduction
     3. 2. Experimental procedures
     4. 3. Sensor signal analysis
     5. 4. Neural network data processing
     6. 5. Result and discussion
     7. 6. Conclusions
     8. Acknowledgements
     9. References
105. Critical aspects in the application of acoustic emission sensing techniques for robust and reliable tool condition monitoring
     1. Abstract
     2. 1. Introduction
     3. 2. Background
        1. 2.1. Friction and tool wear
        2. 2.2. Friction and acoustic emission
     4. 3. Problems and solutions
        1. 3.1. Definition of the cutting tests
        2. 3.2. Definition of the tool condition monitoring tests
     5. 4. Conclusions
     6. Acknowledgements
     7. References
106. Design, CFD Simulation and Testing of Special-Purpose Nozzles for Powder Coating Guns
     1. Abstract
     2. 1. Introduction
     3. 2. Evaluation of the efficiency of the basic powder coating gun nozzle
     4. 3. Creation of Virtual Prototype Powder Coating Nozzle and CFD Validation
        1. 3.1. CAD Design of Virtual Prototype Nozzle
        2. 3.2. CFD Validation of Virtual Prototype Nozzle
           1. 3.2.1. Simulation of Inlet Nozzle Pressure
           2. 3.2.2. CFD Simulation of Spray Patterns Using Virtual Prototype Nozzle
     5. 4. Rapid Prototyping of New Nozzle Designs
     6. 5. Nozzles Testing and Evaluation
     7. 6. Conclusions
     8. Acknowledgement
     9. References
107. Development of an artificial neural network for defects prediction in metal forming
     1. Abstract
     2. 1. Introduction
     3. 2. The artificial neural network approach
     4. 3. Network morphology
     5. 4. Number of hidden layers and neurons
     6. 5. The training process
     7. 6. Input vectors and data structures
     8. 6. Analysis of the results
     9. 7. Conclusions
     10. References
108. FEM analysis of advanced high strength steel car body drawing process
     1. Abstract
     2. 1. Introduction
     3. 2. Material requirements for sheet metal drawing
        1. 2.1. Safety requirements
        2. 2.2. Durability requirements
           1. 2.2.1. Corrosion
           2. 2.2.2. Fatigue
        3. 2.3. Environmental requirements
        4. 2.4. AHSS disadvantages
     4. 3. FEM analysis of sheet metal drawing processes
        1. 3.1. Finite element methods (FEM)
           1. 3.1.1. FEM codes
           2. 3.1.2. FEM approaches (one-step vs. incremental)The FEM numerical computation typology for
           3. 3.1.3. Elements in sheet metal drawing simulation
        2. 3.2. AutoForm FEM code
     5. 4. Test case with AutoForm Incremental code
     6. 6. Conclusions
     7. Acknowledgements
     8. References
109. Flexible tool management strategy for optimum tool inventory control
     1. Abstract
     2. 1. Introduction
     3. 2. CBN grinding wheel tool management
     4. 3. Tool inventory control
        1. 3.1. Flexible Tool Management Strategy
        2. 3.2. Novel FTMS Approach
        3. 3.3. Test Case Applications
     5. 4. Conclusions and further developments
     6. Acknowledgements
     7. References
110. Neural network material modelling for machining FEM simulation
     1. Abstract
     2. 1. Introduction
     3. 2. NN processing procedures
        1. 2.1. Stress-strain curves for NN training set formation
        2. 2.2. Neural network processing
           1. 2.2.1. NN configuration: 3-5-1
           2. 2.2.2. NN configuration: 4-5-1
           3. 2.2.3. NN configuration: 6-5-1
           4. 2.2.4. NN configuration: 7-5-1
     4. 3. Material modelling input into the FEM code
     5. 4. Conclusions
     6. Acknowledgement
     7. References
111. Open controller enabled by an advanced real-time network
     1. Abstract
     2. 1. Introduction
     3. 2. Objectives
     4. 3. Phases of the project
        1. 3.1. Analysis of Communication Systems, Platforms and Tools
        2. 3.2. Design, implementation and validation of a Distributed Control System Real-time Framework (DCRF)
           1. 3.2.1. Implementation of the DCRF
           2. 3.2.2. Configuration system
        3. 3.3. Design, implementation and validation of Motion Control base and extension components for an open numerical control system
        4. 3.4. Current and future activities
     5. Acknowledgements
     6. References
112. Prediction of machining errors on the geometric accuracy of a milled guide
     1. Abstract
     2. 1. Introduction
     3. 2. Form Shaping Function
     4. 3. Error Matrix
     5. 4. Modelling swept envelopes of cutting tools
     6. 5. Application at the case of a milted guide
     7. 6. Future developments
     8. Acknowledgements
     9. Reference
113. Reconstruction of 3-D Relief Surfaces from 2-D Images
     1. Abstract
     2. 1. Introduction
     3. 2. The illumination model
     4. 3. Transforming a 2-D image into a digital image
     5. 4. Extraction of the grey levels from the image
     6. 5. Applications of the proposed approach to reverse engineering process
        1. 1. Reverse engineering design of a paperclip
        2. 2. Recreation of 3-D relief surface from a 2-D visual image
     7. 6. Conclusions
     8. Acknowledgements
     9. References