A novel framework for storage assignment optimization inspired by finite element method.

Area of Science:

• Operations Management
• Industrial Engineering
• Manufacturing Systems

Background:

• Industry 4.0 necessitates fundamental changes in manufacturing and operations management.
• Traditional storage assignment methods are insufficient for modern, agile inventory systems.
• Automated Storage and Retrieval Systems (AS/RS) require advanced storage and layout solutions.

Purpose of the Study:

• To redefine the storage assignment and layout problem for enhanced agility in Industry 4.0 environments.
• To address the limitations of existing algorithms for storage assignment.
• To introduce a novel optimization technique for storage assignment.

Main Methods:

• A new definition for storage assignment and layout problems focusing on AS/RS agility.
• Development of the Storage Assignment Optimization/Finite Element Method (SAO/FEM) algorithm, inspired by mechanical engineering.
• Application of stress distribution analogy, Finite Element Method, and minimum total potential energy theory for optimization.

Main Results:

• The SAO/FEM algorithm provides a new model for storage assignment optimization.
• Numerical examples demonstrate the efficiency of SAO/FEM in terms of calculation time and solution quality.
• An application module for the SAO/FEM algorithm was developed and implemented for optimized storage positioning.

Conclusions:

• The SAO/FEM algorithm offers an effective solution for storage assignment optimization in Industry 4.0.
• The proposed method enhances storage mechanism agility and warehouse operational efficiency.
• The integration of mechanical engineering principles provides a novel framework for operations management challenges.