Control Engineering in Mechatronics: Industry 4.0 Adoption with Lean Six Sigma Framework

Preface
Contents
About the Editor
Agent-Based Control System for SMEs—Industry 4.0 Adoption with Lean Six Sigma Framework
1 Introduction
1.1 Background
1.2 Industry 4.0
1.3 Material Handling Systems in Intelligent Production Systems
1.4 Types of Control Systems
1.5 Lean Six Sigma Approach for Performance Evaluation and Improvement of the Manufacturing System
1.6 Overall Equipment Effectiveness (OEE)
1.7 Lead Time and Time Study in OEE and LSS
1.8 The Simulation for OEE and LSS
1.9 The Objective of the Research
2 Literature Review
2.1 Overview
2.2 Agent-Based Control Architecture for the Industry 4.0 Implementation
2.3 Agent-Based Control Architectures for Manufacturing System (Material Handling Systems Approach)
2.4 Importance of Manufacturing System Performance Evaluation
2.5 Lean Six Sigma Approach for Manufacturing System Performance Evaluation and Improvement
2.6 Time Study Techniques for Lean Six Sigma and Manufacturing System Performance Evaluation and Improvements
2.7 Overall Equipment Effectiveness for Lean Six Sigma and Manufacturing System Performance Evaluation and Improvements
2.8 Overall Equipment Effectiveness and Time Study Relationship
2.9 Computer-Based Simulation for Lean Six Sigma and Manufacturing System Performance Evaluation and Improvements
2.10 Literature Review Conclusion
3 Methodology
3.1 Overview
3.2 Design of the Agent-Based Control Architecture with Master-Slave Mechanism
3.3 Case Study System Description with the Agent-Based Control Architecture
3.4 System Description with the Agent-Based Control Architecture
3.5 Lean Six Sigma Strategies to Evaluate and Improve the Performance of the Target System After Agent-Based Control Architecture
4 Result and Discussion
4.1 Overview
4.2 Discrete Time Study Results for Each Phase of the System
4.3 Utilization Rate Report to Identify the Resources with More Idle Time
4.4 Simulation Result of the System by Arena
4.5 OEE Analysis Before Optimization
4.6 OEE Analysis After Optimization
5 Conclusion
Appendix A
References
Path Tracking Control of Bioflexible Probes Exposed to Uncertainties and Internal Tissues Disturbances with Unknown Upper Bonds Using Robust-Adaptive Sliding Mode Control
1 Introduction
2 Problem Formulation
3 Design of Robust-Adaptive Sliding Mode Controller
3.1 Fixed Upper Band and Unknown Disturbances
3.2 Upper Band of Unknown Functional Disturbances
4 Simulation Results
5 Conclusion
References
Applied Mechatronics: A Case Study on Mathematical Modelling and Experimental Analysis of the Second Life Batteries
1 Introduction
1.1 Application in Residential Buildings
1.2 Experimental Analysis
1.3 Modelling
2 Theoretical Analysis of the Second Life Batteries
2.1 Experimental Methodology
2.2 Mathematical Modelling
References
Embracing Digital Technologies in the Pharmaceutical Industry
1 Introduction
2 Internet of Things
2.1 The IoT Architecture
2.2 IoT Advantages and Disadvantages
3 Cloud-Based Technology
3.1 Advantages of Cloud Computing
3.2 Cloud Technology in Medicine
3.3 Cloud Technology in the Pharmaceutical Industry
4 Data Analytics
4.1 Big Data Analytics
4.2 Enhancing Data Analytical Capabilities in the Pharmaceutical Industry
5 Blockchain Technology
6 Telemedicine Innovation
7 Artificial Intelligence Applications
7.1 AI in the Pharmaceutical Sector
8 Wearable Medical Device Technology
9 Cyber-Physical Systems
10 Pharma 4.0
References
Mathematical Modeling and Hybrid Adaptive-Fuzzy Control of HIV/AIDS Infection
1 Introduction
2 Dynamic Modeling of HIV/AIDS Infection
3 Adaptive Control Design to the Immunodeficiency Virus Model
4 Using Adaptive-Fuzzy Control Method
5 Conclusion
References
Communication Networks Characteristics Impact on Cyber-Physical Systems
1 Introduction
2 Background
2.1 Cyber-Physical System
2.2 Data Transmission
3 Method
4 Results and Discussion
5 Conclusions
References