Session: 02-05-01: IoT and Digital Twins

Paper Number: 162532

Thе Businеss Digitаl Twin: Unlоcking Industriаl Еnginееring and Rееnginееring Cараbilitiеs of thе Manufacturing Wоrkfоrcе 

Achieving industrial sustainability is a critical objective for nations worldwide, with a renewed emphasis on revitalizing the manufacturing sector through the development of smart factories. These advanced facilities form the backbone of modern industrial economies, relying not only on cutting-edge technologies but also on a skilled workforce capable of driving innovation and efficiency. To address this need, integrating theoretical knowledge with practical industrial applications is essential. This fusion equips professionals with the tools and expertise required to establish new manufacturing enterprises or enhance existing ones, thereby fueling economic revitalization and long-term sustainability.

This paper introduces the Business Digital Twin (BDT) software, a transformative tool developed in an industrial context, designed to unlock the full potential of the manufacturing workforce. The BDT serves dual purposes: it acts as a knowledge provider, offering insights and structured frameworks, and as a practical tool, enabling workers to manage, develop, and establish smart factories effectively. Its capabilities span three key dimensions:

Strategic: Facilitating high-level planning and decision-making to align factory operations with broader business goals.

Tactical: Supporting mid-level management of resources, processes, and technology integration.

Operational: Enhancing day-to-day activities through real-time monitoring and optimization.

The BDT achieves this by creating a digital replica of the factory environment, allowing users to simulate processes, test scenarios, and make data-driven decisions. This empowers the workforce to optimize resource allocation, streamline production, and adapt to market shifts, all while adhering to the principles of Industry 4.0 (automation, IoT, and data exchange) and Industry 5.0 (human-machine collaboration and sustainability).

Research Methodology

The research methodology centers on applying the BDT software to a practical case: planning and developing a new product while simultaneously designing the factory’s operational infrastructure. This holistic approach integrates critical enterprise systems, including:

Supplies: Managing raw materials and logistics.

Production: Overseeing manufacturing processes and workflows.

Sales: Aligning output with market demand.

Financing: Optimizing budget allocation and cost efficiency.

Technological Environment: Incorporating automation, IoT, and real-time data analytics.

By simulating these components, the BDT enables the creation of a fully functional smart factory capable of adapting to technological advancements and evolving economic conditions.

Core Framework: Business Model Ontology

At its foundation, the BDT is built upon the principles of Business Model Ontology (BMO), providing an intuitive, structured framework for understanding and simulating business models. This integration allows the workforce to move beyond routine operations, engaging in advanced industrial engineering (designing new systems) and reengineering (improving existing ones). Key features include:

Real-time scenario analysis: Testing potential outcomes before implementation.

Predictive insights: Anticipating challenges and opportunities.

Performance optimization: Enhancing efficiency across all factory levels.

Impact and Implications

The BDT enhances workforce capabilities by bridging the gap between theoretical expertise and practical execution. For new manufacturing enterprises, it provides a blueprint for establishing agile, efficient operations. For existing factories, it offers tools to revitalize processes, making them competitive in a rapidly evolving industrial landscape. By empowering professionals across strategic, tactical, and operational dimensions, the BDT fosters a workforce capable of driving industrial sustainability.

Conclusion

This research demonstrates that the Business Digital Twin software is a game-changer for the manufacturing sector. By unlocking the industrial engineering and reengineering capabilities of the workforce, it enables the creation and enhancement of smart factories that are efficient, adaptable, and aligned with global sustainability goals. Ultimately, the BDT not only revitalizes the manufacturing industry but also lays the foundation for economic growth and industrial success in the modern era.

Presenting Author: Stefan Stefanov Institute for Systemic Economic Engineering

Presenting Author Biography: Stefan Stefanov is the Executive Chairman of the Institute for Systemic Economic Engineering. He leads the development of strategic dissemination of Business Model Ontology dedicated to advancing the Digital Transformation of Economic Science. Stefan Stefanov has played a pivotal role in the evolution of the Business Model Ontology theory. With his extensive background, he was a key contributor to the pioneering development of the ontology, further solidifying his commitment to advancing the field of scientific management. His professional experience includes creating a new factory for high-tech machinery – hydraulic axial piston pumps and motors, as well as drastic improvements of existing factories by implementing the knowledge for BMO. Stefan Stefanov is a “Diplôme d'Ingénieur” from from Technical University, Sofia, Bulgaria and ECAM-EPMI, Paris, France.

Authors:

Stefan Stefanov Institute for Systemic Economic Engineering
Trifon Stefanov Institute for Systemic Economic Engineering
Dana Bachvarova Institute for Systemic Economic Engineering