Automation Pyramid as Constructor for a Complete Digital Twin, Case Study: A Didactic Manufacturing System

Area of Science:

• Industrial Engineering
• Manufacturing Systems
• Artificial Intelligence

Background:

• Industry 4.0 necessitates disruptive technologies for comprehensive factory improvement, moving beyond partial solutions.
• Digital Twins (DT) offer real-time virtual modeling for process monitoring and anomaly detection.
• The Automation Pyramid (AP) traditionally segments manufacturing processes from shop floor to decision-making levels.

Purpose of the Study:

• To propose a complete Digital Twin (DT) structure that encompasses all levels of the Automation Pyramid (AP).
• To leverage Artificial Intelligence (AI) for modeling each AP stage within the DT framework.
• To enable efficient information flow and control across all manufacturing stages.

Main Methods:

• Development of a virtual model for each level of the traditional AP.
• Integration of these models into a unified DT structure.
• Application of Artificial Intelligence (AI) to manage interconnections and information flow between AP levels within the DT.

Main Results:

• A novel DT structure is proposed, covering all Automation Pyramid stages.
• The model facilitates efficient information management and control across the entire manufacturing system.
• A case study demonstrates the DT concept's application to modular workstations within the AP framework.

Conclusions:

• The proposed comprehensive DT model, powered by AI, is a valuable tool for improving all levels of industrial processes.
• Integrating DT across the entire AP enhances overall factory competitiveness and operational efficiency.
• This approach addresses the limitations of partial DT implementations by providing a holistic solution.