Applications of Artificial Intelligence Techniques in Industry 4.0

1. Front Matter

   Pages i-xii

   PDF

2. Introduction

   • Aydin Azizi

   Pages 1-6

3. Modern Manufacturing

   • Aydin Azizi

   Pages 7-17

4. RFID Network Planning

   • Aydin Azizi

   Pages 19-25

5. Hybrid Artificial Intelligence Optimization Technique

   • Aydin Azizi

   Pages 27-47

6. Implementation

   • Aydin Azizi

   Pages 49-61

This book is to presents and evaluates a way of modelling and optimizing nonlinear RFID Network Planning (RNP) problems using artificial intelligence techniques. It uses Artificial Neural Network models (ANN) to bind together the computational artificial intelligence algorithm with knowledge representation an efficient artificial intelligence paradigm to model and optimize RFID networks.

This effort leads to proposing a novel artificial intelligence algorithm which has been named hybrid artificial intelligence optimization technique to perform optimization of RNP as a hard learning problem. This hybrid optimization technique consists of two different optimization phases. First phase is optimizing RNP by Redundant Antenna Elimination (RAE) algorithm and the second phase which completes RNP optimization process is Ring Probabilistic Logic Neural Networks (RPLNN).

The hybrid paradigm is explored using a flexible manufacturing system (FMS) and the results are compared with well-known evolutionary optimization technique namely Genetic Algorithm (GA) to demonstrate the feasibility of the proposed architecture successfully.

• Flexible Manufacturing Systems
• Inventory Management
• RFID Network Planning
• RFID Antenna
• Artificial Neural Network ANN
• Redundant Antenna Elimination RAE
• Ring Probabilistic Logic Neural Networks RPLNN
• Hybrid Artificial Intelligence Algorithm
• Genetic Algorithm
• Engineering Economics

• Department of Engineering, German University of Technology in Oman, Muscat, Oman

  Aydin Azizi

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