Plastics industry 4.0 : potentials and applications in plastics technology /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Hopmann, Christian (Autor), Schmitz, Mauritius (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Munich : Carl Hanser Verlag, [2021]
Temas:
Plastics > Technological innovations.
Plastics industry and trade.
Mati�eres plastiques > Innovations.
Mati�eres plastiques > Industrie.
Plastics industry and trade
Plastics > Technological innovations
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Preface
  • About the Authors
  • Contents
  • 1 Introduction
  • 1.1 Potentials and Benefits of Industry 4.0
  • 1.2 Challenges for Successful Implementation of Industry 4.0
  • 2 Data Acquisition and Process Monitoring as Enabler for Industry 4.0
  • 2.1 The Necessity of Data Acquisition
  • 2.1.1 Quality Control in the 1990s
  • 2.1.2 Exemplary Fields of Application
  • 2.2 Gaining Insights into the Process
  • 2.2.1 Differentiation of Injection Molding Process Data
  • 2.2.2 Economic Evaluation of the Injection Molding Process Based on Measurable Values
  • 2.2.3 Process Data for Setup of a New Process
  • 2.2.4 Process Control
  • 2.2.4.1 Online Process Control
  • 2.2.4.2 Process Control Concepts
  • 2.3 Data Acquisition Methods
  • 2.3.1 Material Properties for Digital Engineering
  • 2.3.1.1 Thermal Properties of Plastic Melts
  • 2.3.1.2 pvT-Behavior
  • 2.3.1.3 Rheological Properties
  • 2.3.1.4 Mechanical Properties
  • 2.3.1.5 Applications of Data in Digital Engineering
  • 2.3.2 Data Acquisition and Process Monitoring Methods
  • 2.3.2.1 Temperature Measurement
  • 2.3.2.2 Pressure Measurement
  • 2.3.2.3 Electrical Pressure Measurement
  • 2.3.2.4 Position Measurement
  • 2.3.3 Humidity Measurement
  • 2.3.4 Part Measurement
  • 2.3.4.1 Part Measurement (Post-Mortem)
  • 2.3.4.2 Optical Measurement
  • 2.3.4.3 Tactile Measurement
  • 2.3.5 Combination of Tactile and Optical Measurements
  • 2.4 The Different Types of Quality Control
  • 2.4.1 Offline Quality Control
  • 2.4.2 Inline Quality Control
  • 2.4.3 Online Quality Control
  • 3 Cyber-Physical Systems
  • 3.1 Computer Integrated Manufacturing as Conceptual Foundation for Cyber-Physical Production Systems
  • 3.2 CPPS in Plastics Processing
  • 3.3 Communication Capability of CPPS Components in Injection Molding
  • 3.4 Planning and Realizing a CPPS in Plastics Processing.
  • 4 Models and Artificial Intelligence
  • 4.1 Model Quality
  • 4.2 Three Different Categories of Models
  • 4.2.1 Physical Models
  • 4.2.2 Knowledge-Based Systems
  • 4.2.3 Artificial Intelligence
  • 4.2.3.1 AI Modeling Methods
  • 4.2.3.2 Artificial Neural Networks (ANNs)
  • 4.2.3.3 AI Modeling Examples in the Plastics Industry
  • 5 Global Connectivity
  • 5.1 Data Availability
  • 5.2 Data Management
  • 5.3 IT Infrastructure
  • 5.3.1 Cloud Computing
  • 5.3.2 Edge Computing
  • 5.3.3 Hybrid System in Plastics Processing
  • 5.4 Machine and Data Interfaces
  • 5.4.1 Digital I/O
  • 5.4.2 Analog I/O
  • 5.4.3 Serial Interfaces
  • 5.5 Data Systems
  • 5.5.1 Introduction
  • 5.5.2 Need for Data Processing
  • 5.5.3 Development of Data Systems
  • 5.5.4 Enterprise Resource Planning
  • 5.5.5 Manufacturing Execution System
  • 5.5.6 ERP/MES in the Plastics Processing Industry
  • 5.5.7 Requirements for ERP/MES in the Context of Industry 4.0
  • 5.5.8 Developed Systems in Research
  • 5.5.9 Used Systems in the Industry
  • 5.5.9.1 SAP ERP
  • 5.5.9.2 FEKOR MES
  • 5.5.9.3 authenTIG
  • 6 Digital Engineering
  • 6.1 Introduction
  • 6.1.1 Digital Materials
  • 6.1.2 Material Modeling on the Nanoscopic Scale
  • 6.1.3 Material Modeling on the Microscopic and Mesoscopic Scale
  • 6.1.4 Material Models on the Macroscopic Scale
  • 6.1.4.1 Isotropic Linear-Elastic Behavior
  • 6.1.4.2 Orthotropic Linear-Elastic Behavior
  • 6.1.4.3 Hyperelastic Behavior
  • 6.1.4.4 Anisotropic Hyperelastic Behavior
  • 6.1.4.5 Plastic Material Models
  • 6.1.4.6 Viscoelasticity
  • 6.1.4.7 Damage Model for Dynamic Load
  • 6.2 Process Simulation
  • 6.2.1 Setting up Injection Molding Simulation
  • 6.2.2 Design and Optimization Using Injection Molding Simulation
  • 6.3 Result Analysis and Mapping
  • 6.3.1 Calculation of Mechanical Properties Based on Local Microstructure
  • 6.3.2 Weld Lines.
  • 6.3.3 Elastomers: Considering Crosslinking Level in Structural Simulation
  • 6.3.4 Thermoplastic Elastomers: Determination of Elastomer Particle Size
  • 6.4 Part Simulation
  • 6.5 Artificial Neural Networks in Virtual Process Development
  • 7 Complex Value Chain
  • 7.1 Introduction to Complex Value Chains
  • 7.2 Shop Floor Management
  • 7.2.1 Lean Management
  • 7.2.2 Key Figures for Plastics Processing
  • 7.2.3 Shop Floor Management in the Context of Industry 4.0
  • 7.2.4 Asset Identification
  • 7.2.4.1 Identification, Tracking, and Tracing of Assets
  • 7.2.4.2 Technical Solutions of Asset Identification
  • 7.2.4.3 Plastic-Related RFID Research Projects
  • 7.2.5 Warehouse Management
  • 7.2.6 Logistics 4.0
  • 7.2.7 Equipment Management
  • 7.3 Examples of Complex Value Chains in Plastics Processing
  • 7.3.1 Model-Based Setup of Injection Molding Processes
  • 7.3.2 Producing Multiple Variants in a Production Cell
  • 8 Assistant Systems
  • 8.1 Requirements and Functionalities Regarding Assistant Systems
  • 8.2 Simulation-Based Assistance for Process Setup
  • 8.3 Predictive Maintenance
  • 8.3.1 Maintenance Routines
  • 8.3.2 Predictive Maintenance in Injection Molding
  • 8.3.2.1 Predictive Maintenance for Injection Molding Machines
  • 8.3.2.2 Predictive Maintenance for Injection Molds
  • 8.4 Augmented Reality and Virtual Reality as Visual Support
  • 8.4.1 Definition and Demarcation of Terms
  • 8.4.2 State of the Art
  • 8.4.3 Industry 4.0 and Augmented Reality
  • 8.5 Commercially Available Tools
  • 8.5.1 Engel iQ Control Systems for Process Support in Injection Molding
  • 8.5.2 ARBURG Continuous Quality Control with the CQC System
  • 8.5.3 KraussMaffei Adaptive Process Control to Deal with Material Fluctuations
  • 8.5.4 Sumitomo Enhanced Machine Efficiency with ActivePlus
  • 8.5.5 Process Optimization with STASA QC
  • Index.

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