The Digital Twin and Smart Manufacturing Technologies course in Madrid is designed to help professionals leverage advanced technologies like digital twins and IoT to optimize manufacturing operations.
From:
13-07-2026
Course Overview
Digital twin and smart manufacturing technologies are reshaping the industrial landscape by enabling real-time visibility, predictive analytics, and intelligent decision-making. These tools allow organizations to simulate operations, optimize performance, and improve resilience across production systems.
This course introduces participants to the principles of digital twin modeling, smart factory ecosystems, IoT integration, and advanced automation. Participants will explore how to apply these technologies to enhance efficiency, sustainability, and innovation in engineering and manufacturing operations.
At EuroQuest International Training, the program combines technical depth with strategic insights, ensuring participants gain actionable skills to lead digital transformation in manufacturing.
Key Benefits of Attending
Understand digital twin fundamentals and applications
Build smart factory strategies powered by IoT and AI
Optimize production processes with real-time data insights
Enhance predictive maintenance and operational reliability
Drive innovation and competitiveness in Industry 4.0
Why Attend
This course empowers professionals to lead digital transformation initiatives, integrating digital twin and smart manufacturing technologies to build sustainable and future-ready operations.
Course Methodology
Expert-led sessions on Industry 4.0 frameworks
Case studies of smart manufacturing adoption
Hands-on labs with digital twin simulations
Group projects on IoT and smart factory design
Scenario planning and digital transformation exercises
Course Objectives
By the end of this ten-day training course, participants will be able to:
Define digital twin concepts and smart manufacturing systems
Build and deploy digital twins for industrial assets
Integrate IoT, AI, and automation into manufacturing operations
Use predictive analytics for maintenance and optimization
Improve safety, compliance, and sustainability in factories
Evaluate Industry 4.0 technologies and adoption frameworks
Apply simulation tools for production and process improvement
Manage risks associated with digital transformation
Enhance workforce readiness for smart manufacturing
Design smart manufacturing strategies aligned with business goals
Communicate digital transformation benefits to stakeholders
Develop long-term roadmaps for Industry 4.0 maturity
Target Audience
Manufacturing and operations managers
Industrial automation and systems engineers
Digital transformation leaders
Maintenance and reliability professionals
Executives overseeing engineering and production
Target Competencies
Digital twin modeling and simulation
Smart factory design and implementation
IoT and AI integration in manufacturing
Predictive analytics and process optimization
Risk and compliance in Industry 4.0
Sustainable and efficient production management
Strategic digital leadership
Course Outline
Unit 1: Introduction to Digital Twin and Smart Manufacturing
Defining digital twin technology
Evolution of Industry 4.0 and smart factories
Benefits and challenges of adoption
Case studies of global leaders
Unit 2: Digital Twin Fundamentals
Modeling physical assets and processes
Real-time synchronization of physical and digital worlds
Tools and platforms for digital twin creation
Practical lab on digital twin simulation
Unit 3: Smart Manufacturing Ecosystems
Components of smart factories
IoT-enabled sensors and connectivity
Interoperability and system integration
Building connected manufacturing environments
Unit 4: IoT and Data Integration
Role of IoT in digital twin applications
Data collection, storage, and management
Real-time analytics for process monitoring
Security considerations in IoT systems
Unit 5: AI and Predictive Analytics in Manufacturing
Using AI for predictive maintenance
Data-driven decision-making frameworks
Machine learning for production optimization
Practical exercises on predictive analytics
Unit 6: Automation and Robotics in Smart Factories
Role of robotics in Industry 4.0
Human-robot collaboration in manufacturing
Automation for efficiency and quality improvement
Case studies of robotics adoption
Unit 7: Simulation and Process Optimization
Simulation techniques for process design
Workflow and production optimization
Scenario analysis and digital experimentation
Practical lab using simulation tools
Unit 8: Safety, Compliance, and Sustainability
Safety management in smart factories
Environmental compliance and monitoring
Sustainable production strategies
ESG integration in digital transformation
Unit 9: Risk and Cybersecurity in Digital Manufacturing
Identifying risks in Industry 4.0 systems
Cybersecurity challenges in digital twin applications
Building resilient digital ecosystems
Risk management frameworks
Unit 10: Workforce Transformation and Change Management
Upskilling for digital twin and smart manufacturing
Overcoming resistance to digital adoption
Building a culture of innovation
Communication strategies for transformation
Unit 11: Strategic Leadership in Digital Transformation
Aligning smart manufacturing with corporate strategy
Evaluating ROI of digital twin initiatives
Benchmarking against global best practices
Leadership skills for Industry 4.0
Unit 12: Capstone Smart Manufacturing Project
Group-based smart factory simulation
Designing a digital twin-enabled strategy
Presenting findings to stakeholders
Action roadmap for organizational adoption
Closing Call to Action
Join this ten-day training course to master digital twin and smart manufacturing technologies, enabling your organization to achieve operational excellence and Industry 4.0 leadership.
The Digital Twin and Smart Manufacturing Technologies Training Courses in Madrid provide professionals with an in-depth understanding of how advanced digital tools and intelligent systems can transform modern industrial operations. As organizations embrace digitalization to improve efficiency, enhance reliability, and accelerate innovation, digital twins and smart manufacturing technologies have become essential components of the next generation of engineering and production environments. These programs are designed for engineers, operations managers, digital transformation leaders, automation specialists, and technology strategists seeking to strengthen their expertise in industrial digitalization.
Participants explore the core principles of digital twin technology, including virtual modeling, real-time data integration, simulation, predictive analytics, and system optimization. The courses highlight how digital twins enable better decision-making by providing accurate, dynamic representations of physical assets, processes, and systems. Through case studies and hands-on exercises, attendees learn to build, apply, and evaluate digital twins to support predictive maintenance, operational planning, and performance improvement.
These smart manufacturing training programs in Madrid also examine Industry 4.0 technologies such as IoT-enabled systems, advanced automation, machine learning applications, and connected production environments. Participants gain insights into how these digital tools enhance supply chain visibility, process control, quality assurance, and production flexibility. The curriculum emphasizes the integration of digital platforms with traditional manufacturing operations, enabling organizations to modernize their systems and adopt data-driven, intelligent production models.
Attending these training courses in Madrid provides access to expert instructors and an international learning community with diverse industry perspectives. The city’s thriving technological and industrial ecosystem creates an ideal environment for exploring emerging digital solutions and future manufacturing trends. By completing this specialization, participants will be equipped to implement digital twin applications, optimize smart manufacturing systems, and support transformative digital initiatives that strengthen productivity, innovation, and competitiveness in the modern industrial landscape.