Become an engineer specialized in digital transformation and apply your new knowledge in Blockchain, big data and artificial intelligence to your work" 

For years now, the digital sphere has begun to occupy all kinds of spaces that were previously reserved for analog activities. Digitalization has radically transformed many tasks. Engineering and industry have not been exempt from this revolution, and digitalization has also made a strong entry into these disciplines. 

Thus, concepts have become popular that will gradually gain more and more strength in today's society. Expressions such as blockchain, big data, artificial intelligence, augmented reality or the internet of things (IoT) are no longer as strange as they were a decade ago. These elements are here to stay and have already completely changed numerous professional fields. In the industrial field, these elements have brought about such a revolution that this area has already begun to be referred to as Industry 4.0. 

Industry 4.0 integrates traditional engineering knowledge with these new concepts. Thus, industrial management has had to adapt to the new reality, incorporating more current notions to an area of study that until now had been very solid. 

However, in order to become a true specialist in the field, an adequate learning process must be carried out to introduce these changes in the traditional industrial environment. For that reason, this Advanced Master’s Degree in Industrial Management and Digital Transformation is the degree that any engineer looking to boost his or her career should take. Its contents are focused on professional practice and have been drawn from the experience of great specialists who have been innovating in these areas for years, making this program the best educational degree that an ambitious engineer eager for new knowledge could achieve. 

Digital transformation is influencing all industrial processes today: specialize and become the most in-demand engineer in the profession" 

This Advanced master’s degree in Industrial Management and Digital Transformation contains the most complete and up-to-date scientific program on the market. The most important features include:  

• Practical cases presented by experts in industrial Engineering and Digital Transformation 
• The graphic, schematic, and eminently practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where the self-assessment process can be carried out to improve learning 
• Its special focus on innovative methodologies in digital transformation applied to industrial management
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection work
• Content that is accessible from any fixed or portable device with an Internet connection

Digital transformation is the present and the future: specialize and start applying this knowledge to your work" 

Its teaching staff includes professionals belonging to the field of industrial engineering and digital transformation, who bring their work experience to this program, as well as renowned specialists from leading companies and prestigious universities. 

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide an immersive training experience designed to train for real-life situations. 

This program is designed around Problem-Based Learning, whereby the student must try to solve the different professional practice situations that arise during the course. For this purpose, the professional will be assisted by an innovative interactive video system created by renowned and experienced experts.  

Industrial management has undergone a revolution. If you want to learn how to adapt to this change, enroll in this Advanced master’s degree"

Become an expert in Industrial Management and Digital Transformation and watch how quickly you achieve all your professional goals"

This Advanced master’s degree has been designed by the best experts in the field, who have first-hand knowledge of the latest developments in digital transformation, industrial management and engineering. Thus, the contents transmitted are drawn from the professional experience of great specialists who know what is needed in today's companies and how to meet the existing demand for professionals. For this reason, this degree is the answer for all those who want to learn what the labor market is currently looking for, thus becoming highly sought-after professionals. 

The best content for the most demanding professionals"

Module 1. Strategic Keys to Improve Competitiveness

1.1. Excellence in the Current Company

1.1.1. Adaptation to VUCA Environments
1.1.2. Satisfaction of Key Constituents (Stakeholders)
1.1.3. World Class Manufacturing
1.1.4. Measure of Excellence: Net Promoter Score

1.2. Business Strategy Design

1.2.1. General Strategy Definition Process 
1.2.2. Definition of the Current Situation Positioning Models 
1.2.3. Possible Strategic Movements 
1.2.4. Strategic Models of Action 
1.2.5. Functional and Organizational Strategies 
1.2.6. Environmental and Organizational Analysis SWOT Analysis for Decision-Making 

1.3. Strategy Deployment Balanced Scorecard 

1.3.1. Mission, Vision, Values and Principles 
1.3.2. Need for a Balanced Scorecard 
1.3.3. Perspectives to Be Used in the BSC 
1.3.4. Strategic Map 
1.3.5. Phase to Implement a Good BSC 
1.3.6. General Map of a BSC 

1.4. Process Management 

1.4.1. Process Description 
1.4.2. Types of Process Main Processes 
1.4.3. Process Prioritization 
1.4.4. Process Representation 
1.4.5. Measuring Processes for Improvement 
1.4.6. Process Map 
1.4.7. Process Reengineering 

1.5. Structural Typologies Agile Organizations. ERR 

1.5.1. Structural Typologies 
1.5.2. The Company Viewed as an Adaptable System 
1.5.3. The Horizontal Company 
1.5.4. Characteristics and Key Factors of Agile Organizations (ERR) 
1.5.5. Organizations of the Future: the TEAL Organization 

1.6. Design of Business Models 

1.6.1. Canvas Model for Business Model Design 
1.6.2. Lean Start Up Methodology in the Creation of New Businesses and Products 
1.6.3. The Blue Ocean Strategy 

1.7. Corporate Social Responsibility and Sustainability 

1.7.1. Corporate Social Responsibility (CSR): ISO Business School 26000 
1.7.2. Sustainable Development Goals SDGs 
1.7.3. The 2030 Agenda 

1.8. Customer Management 

1.8.1. The Need to Manage Customer Relationships 
1.8.2. Elements of Customer Management 
1.8.3. Technology and Customer Management. CRM 

1.9. Management in International Environments 

1.9.1. The Importance of the Internationalisation 
1.9.2. Diagnosis of Export Potential 
1.9.3. Elaboration of the Internationalisation Plan 
1.9.4. Implementation of the Internationalization Plan 
1.9.5. Export Assistance Tools 

1.10. Change Management 

1.10.1. The Dynamics of Change in Companies 
1.10.2. Obstacles to Change 
1.10.3. Factors of Adaptation to Change 
1.10.4. Kotter's Methodology for Change Management

Module 2. Project Management

2.1. The Project 

2.1.1. Fundamental Elements of the Project 
2.1.2. The Project Manager 
2.1.3. The Environment in Which Projects Operate 

2.2. Project Scope Management 

2.2.1. Scope Analysis 
2.2.2. Project Scope Planning 
2.2.3. Project Scope Control 

2.3. Schedule Management 

2.3.1. The Importance of the Planning 
2.3.2. Manage Project Planning Project Schedule
2.3.3. Trends in Time Management 

2.4. Cost Management 

2.4.1. Project Cost Analysis 
2.4.2. Financial Selection of Projects 
2.4.3. Project Cost Planning 
2.4.4. Project Cost Control 

2.5. Quality, Resources and Acquisitions 

2.5.1. Total Quality and Project Management 
2.5.2. Project Resources 
2.5.3. Acquisition The Contracting System 

2.6. Project Stakeholders and Their Communications 

2.6.1. The Importance of Stakeholders 
2.6.2. Project Stakeholder Management 
2.6.3. Project Communications 

2.7. Project Risk Management 

2.7.1. Fundamental Principles of Risk Management 
2.7.2. Management Processes for Project Risk Management 
2.7.3. Trends in Risk Management

2.8. Integrated Project Management 

2.8.1. Strategic Planning and Project Management 
2.8.2. Project Management Plan 
2.8.3. Execution and Control Processes 
2.8.4. Project Closure 

2.9. Agile Methodologies I: Scrum 

2.9.1. Agile and Scrum Principles 
2.9.2. The ScrumTeam 
2.9.3. Scrum Events 
2.9.4. Scrum Artefacts 

2.10. Agile Methodologies II: Kanban 

2.10.1. Kanban Principles 
2.10.2. Kanban and Scrumban 
2.10.3. Certifications

Module 3. Leadership and People Management

3.1. The Role of the Leader 

3.1.1. Leadership in Effective People Management 
3.1.2. Types of Decision-Making. Style in People Management 
3.1.3. The Leader Coach 
3.1.4. Self-directed Teams and Empowerment 

3.2. Team Motivation 

3.2.1. Needs and Expectations 
3.2.2. Effective Recognition 
3.2.3. How to Enhance Team Cohesion?

3.3. Communication and Conflict Resolution 

3.3.1. Intelligent Communication 
3.3.2. Constructive Conflict Management 
3.3.3. Conflict Resolution Strategies

3.4. Emotional Intelligence in People Management 

3.4.1. Emotion, Feeling and State of Mind 
3.4.2. Emotional Intelligence 
3.4.3. Ability Model (Mayer and Salovey): Identify, Use, Understand and Manage 
3.4.4. Emotional Intelligence and Personnel Selection 

3.5. Indicators in People Management 

3.5.1. Productivity 
3.5.2. Personnel Rotation 
3.5.3. Talent Retention Rate 
3.5.4. Staff Satisfaction Rate 
3.5.5. Average Time Vacancies Pending Filling 
3.5.6. Average Training Time 
3.5.7. Average Time to Reach Goals 
3.5.8. Absenteeism Levels 
3.5.9. Occupational Accidents 

3.6. Performance Evaluation 

3.6.1. Performance Evaluation Components and Cycle 
3.6.2. 360º Evaluation 
3.6.3. Performance Management: A Process and a System 
3.6.4. Management by Objectives 
3.6.5. Operation of the Performance Evaluation Process 

3.7. Training Plan 

3.7.1. Fundamental Principles 
3.7.2. Identification of Training Requirements 
3.7.3. Training Plan 
3.7.4. Training and Development Indicators 

3.8. Identification of Potential 

3.8.1. Potential 
3.8.2. Soft Skills as a Key High Potential Initiator 
3.8.3. Methodologies for Identifying Potential: Learning Agility Assessment (Lominger) and Growth Factors 

3.9. The Talent Map 

3.9.1. George Odiorne- 4 Boxes Matrix 
3.9.2. 9-Box Matrix 
3.9.3. Strategic Actions to Achieve Effective Talent Outcomes 

3.10. Talent Development Strategy and ROI 

3.10.1. 70-20-10 Learning Model for Soft Skills 
3.10.2. Career Paths and Succession 
3.10.3. Talent ROI

Module 4. Corporate Finance An Economic-Financial Approach

4.1. The Company in Our Environment 

4.1.1. Production Costs 
4.1.2. Companies in Competitive Markets 
4.1.3. Monopolistic Competition 

4.2. Analysis of Financial Statements I: The Balance 

4.2.1. The Assets CP and LP Resources 
4.2.2. Liabilities CP and LP Obligations 
4.2.3. Net Assets Shareholder Returns 

4.3. Analysis of Financial Statements II: the Income Statement 

4.3.1. The Structure of the Income Statement Income, Costs, Expenses and Profit or Loss 
4.3.2. Main Ratios to Analyze the Income Statement
4.3.3. Profitability Analysis 

4.4. Treasury Management 

4.4.1. Collections and Payments Cash-Forecast 
4.4.2. Impact and Management of Treasury Deficits/Surplus Corrective Measures
4.4.3. Effect Flows Analysis  
4.4.4. Bad Debt Portfolio Management and Impact 

4.5. Sources of Financing to CP and LP 

4.5.1. CP Financing, Instruments 
4.5.2. LP Financing, Instruments 
4.5.3. Types of Interest and Their Structure 

4.6. Interaction between the Company and the Bank

4.6.1. The Financial System and the Banking Business 
4.6.2. Corporate Banking Products 
4.6.3. The Company Analyzed by the Bank 

4.7. Analytical or Cost Accounting 

4.7.1. Cost Types. Decisions Based on Costs 
4.7.2. Full Costing 
4.7.3. Direct Costing 
4.7.4. Cost Model by Center and by Activity 

4.8. Investment Analysis and Valuation 

4.8.1. The Company and the Investment. Decisions Scenarios and Situations
4.8.2. Investment Valuation 
4.8.3. Company Valuation 

4.9. Corporate Accounting 

4.9.1. Capital Increase and Reduction
4.9.2. Dissolution, Liquidation and Transformation of Companies 
4.9.3. Combination of Companies: Mergers and Acquisitions 

4.10. Foreign Trade Finance 

4.10.1. Foreign Markets: The Decision to Export 
4.10.2. The Foreign Exchange Market 
4.10.3. International Payment and Collection Methods 
4.10.4. Transportation, Incoterms and Insurance

Module 5. Design and Product Development

5.1. QFD in Product Design and Development (Quality Function Deployment) 

5.1.1. From the Voice of the Customer to Technical Requirements 
5.1.2. The House of Quality/Phases for its Development 
5.1.3. Advantages and Limitations 

5.2. Design Thinking 

5.2.1. Design, Need, Technology and Strategy 
5.2.2. Process Stages 
5.2.3. Used Tools and Techniques

5.3. Concurrent Engineering 

5.3.1. Concurrent Engineering Fundamentals 
5.3.2. Concurrent Engineering Methodologies 
5.3.3. Used Tools 

5.4. Program. Planning and Definition 

5.4.1. Requirements. Quality Management 
5.4.2. Development Phases Time Management 
5.4.3. Materials, Feasibility, Processes Cost Management 
5.4.4. Project Team Human Resource Management 
5.4.5. Information. Communication Management 
5.4.6. Risk Analysis Risk Management 

5.5. Product. Design (CAD) and Development 

5.5.1. Information Management/PLM/Product Life Cycle 
5.5.2. Product Failure Modes and Effects 
5.5.3. CAD Construction Reviews 
5.5.4. Product and Manufacturing Drawings 
5.5.5. Design Verification 

5.6. Prototypes. Development

5.6.1. Rapid Prototyping 
5.6.2. Control Plan 
5.6.3. Experiment Design 
5.6.4. Analysis of Measuring Systems 

5.7. Productive Process. Design and Development.  

5.7.1. Modes and Effects of Process Failure 
5.7.2. Design and Construction of Manufacturing Tooling 
5.7.3. Design and Construction of Checking Fixtures (Gauges) 
5.7.4. Adjustment Phases 
5.7.5. Production Start-Up 
5.7.6. Initial Process Evaluation 

5.8. Product and Process. Validation 

5.8.1. Evaluation of Measurement Systems 
5.8.2. Validation Tests 
5.8.3. Statistical Process Control (SPC) 
5.8.4. Product Certification  

5.9. Change Management. Improvement and Corrective Actions  

5.9.1. Types of change 
5.9.2. Variability Analysis, Improvement 
5.9.3. Lessons Learned and Proven Practices 
5.9.4. Process of Change  

5.10. Innovation and Technology Transfer 

5.10.1. Intellectual Property 
5.10.2. Innovation 
5.10.3. Technology Transfer

Module 6. Production Planning and Control

6.1. Phases of Production Planning 

6.1.1. Advanced Planning 
6.1.2. Sales Forecasting, Methods 
6.1.3. Takt-Time Definition 
6.1.4. Material Plan-MRP- Minimum Stock  
6.1.5. Personnel Plan 
6.1.6. Equipment Needs 

6.2. Production Plan (PDP) 

6.2.1. Factors to Consider 
6.2.2. Push Planning 
6.2.3. Pull Planning 
6.2.4. Mixed Systems 

6.3. Kanban 

6.3.1. Types of Kanban 
6.3.2. Kanban Uses 
6.3.3. Autonomous Planning: 2-Bin Kanban 

6.4. Production Control 

6.4.1. PDP Deviations and Reporting 
6.4.2. Production Performance Monitoring: OEE 
6.4.3. Total Capacity Tracking: TEEP 

6.5. Production Organization 

6.5.1. Production Team 
6.5.2. Process Engineering 
6.5.3. Maintenance 
6.5.4. Material Control 

6.6. Total Productive Maintenance (TPM) 

6.6.1. Corrective Maintenance 
6.6.2. Autonomous Maintenance 
6.6.3. Preventative Maintenance 
6.6.4. Predictive Maintenance 
6.6.5. Maintenance Efficiency Indicators MTBF - MTTR 

6.7. Plant Layout 

6.7.1. Conditioning Factors 
6.7.2. In-Line Production 
6.7.3. Production in Work Cells 
6.7.4. Applications 
6.7.5. SLP Methodology 

6.8. Just-In-Time (JIT) 

6.8.1. Description and Origins of JIT 
6.8.2. Objectives 
6.8.3. Application of JIT Product Sequencing

6.9. Theory of Constraints (TOC) 

6.9.1. Fundamental Principles 
6.9.2. The 5 Steps of TOC and Its Application 
6.9.3. Advantages and Disadvantages 

6.10. Quick Response Manufacturing (QRM) 

6.10.1. Description 
6.10.2. Key Points for Structuring 
6.10.3. QRM Implementation 

Module 7. Lean manufacturing

7.1. Lean Thinking 

7.1.1. Structure of the Lean System
7.1.2. Lean Principles 
7.1.3. Lean Versus Traditional Manufacturing Processes 

7.2. Waste in the Company 

7.2.1. Value Vs. Waste in Lean Environments 
7.2.2. Types of Waste (MUDAS) 
7.2.3. Lean Process of Thinking 

7.3. The 5 S 

7.3.1. 5S Principles and How They Can Help Improve Productivity 
7.3.2. The 5 S: Seiri, Seiton, Seiso, Seiketsu and Shitsuke 
7.3.3. Implementation of the 5 S in the Company 

7.4. Lean Diagnostic Tools. Vsm. Value Stream Maps 

7.4.1. Value Adding Activities (VA), Necessary Activities (NNVA) and Non-Value Adding Activities (NVA) 
7.4.2. The 7 Tools of Value Stream mapping(Value Stream Mapping) 
7.4.3. Process Activity Mapping 
7.4.4. Supply Chain Response Mapping 
7.4.5. The Production Variety Funnel 
7.4.6. Quality Filter Mapping 
7.4.7. Demand Amplification Mapping 
7.4.8. Decision Point Analysis 
7.4.9. Mapping of the Physical Structure 

7.5. Lean Operational Tools 

7.5.1. Smed 
7.5.2. Jidoka 
7.5.3. Pokayoke 
7.5.4. Batch Reduction 
7.5.5. Pous

7.6. Lean Tools for Production Monitoring, Planning and Control  

7.6.1. Visual Management 
7.6.2. Standardization 
7.6.3. Production Leveling (Heijunka) 
7.6.4. Cellular Manufacturing 

7.7. The KAIZEN Method for Continuous Improvement 

7.7.1. KAIZENPrinciples  
7.7.2. KAIZEN Methodologies Kaizen Blitz, Gemba Kaizen, Kaizen Teian 
7.7.3. Problem Solving Tools A3, Report,  
7.7.4. Main Obstacles to KAIZEN Implementation 

7.8. Roadmap for Lean Implementation 

7.8.1. General Aspects of Implementation 
7.8.2. Phases of Implementation 
7.8.3. Information Technologies in Lean Implementation
7.8.4. Success Factors in Lean Implementation 

7.9. KPIs for Measuring Lean Performance

7.9.1. OEE- Overall Equipment Efficiency 
7.9.2. TEEP- Total Effective Equipment Effectiveness Performance 
7.9.3. FTT- First-Time Quality 
7.9.4. DTD- Dock to Dock Time 
7.9.5. OTD- On-Time Delivery 
7.9.6. BTS- Manufacturing According to Program 
7.9.7. ITO- Inventory Turnover Rate 
7.9.8. VAR- Value Added Ratio 
7.9.9. PPMs- Parts Per Million Defects 
7.9.10. FR- Delivery Fulfillment Rate 
7.9.11. IFA-Accident Frequency Index 

7.10. The Human Dimension of Lean Staff Participation Systems 

7.10.1. The Lean Project Team Application of Teamwork 
7.10.2. Operator Versatility 
7.10.3. Improvement Groups 
7.10.4. Suggestion Programs 

Module 8. Quality Management

8.1. Total Quality 

8.1.1. Total Quality Management 
8.1.2. External and Internal Customer 
8.1.3. Quality Costs 
8.1.4. Continuous Improvement and the Deming Philosophy 

8.2. ISO 9001:15 Quality Management System 

8.2.1. The 7 Principles of ISO 9001:15 Quality Management 
8.2.2. The Process Approach 
8.2.3. ISO 9001:15 Requirements 
8.2.4. Stages and Recommendations for Implementation 
8.2.5. Deployment Objectives in a Hoshin-Kanri-type Model  
8.2.6. Certification Audit 

8.3. Integrated Management Systems  

8.3.1. Environmental Management System ISO Business School 14000 
8.3.2. Occupational Risk Management System: ISO Business School 45001 
8.3.3. Integration of Management Systems 

8.4. Excellence in Management: EFQM Model 

8.4.1. Principles and Fundamentals of EFQM Model 
8.4.2. New Criteria of the EFQM Model 
8.4.3. EFQM Diagnostic Tool: REDER Matrixes 

8.5. Quality Tools 

8.5.1. Basic Tools 
8.5.2. SPC Statistical Process Control 
8.5.3. Control Plan and Control Guidelines for Product Quality Management 

8.6. Advanced Tools and Troubleshooting Tools 

8.6.1. FMEA 
8.6.2. 8D Report 
8.6.3. The 5 Whys 
8.6.4. The 5W + 2H 
8.6.5. Benchmarking 

8.7. Continuous Improvement Methodology I: PDCA 

8.7.1. The PDCA Cycle and Its Stages 
8.7.2. Application of the PDCA Cycle to Lean Manufacturing Development 
8.7.3. Keys to Success of PDCA Projects 

8.8. Continuous Improvement Methodology II: Six-Sigma 

8.8.1. Six-Sigma Description 
8.8.2. Six-Sigma Principles 
8.8.3. Six-Sigma Project Selection 
8.8.4. Six-Sigma Project Stages DMAIC Methodology 
8.8.5. Six-Sigma Roles 
8.8.6. Six-Sigma and Lean Manufacturing 

8.9. Quality Suppliers. Audits. Testing and Laboratory 

8.9.1. Reception Quality Concerted Quality 
8.9.2. Internal Audits Management System 
8.9.3. Product and Process Audits 
8.9.4. Phases to Perform Audits 
8.9.5. Auditor Profile 
8.9.6. Testing, Laboratory and Metrology 

8.10. Organizational Aspects of Quality Management 

8.10.1. Management's Role in Quality Management 
8.10.2. Organization of the Quality Area and the Relationship with Other Areas 
8.10.3. Quality Circles 

Module 9. The Logistics Function, Key to Compete

9.1. Logistical Function of and the Supply Chain 

9.1.1. Logistics Is the Key to a Company's Success 
9.1.2. Logistics Challenges 
9.1.3. Key Activities to Logistics How to Obtain Logistic Function Value 
9.1.4. Types of Supply Chain 
9.1.5. Supply Chain Management 
9.1.6. Logistics Costs 

9.2. Logistics Optimization Strategies 

9.2.1. Cross-Docking Strategy 
9.2.2. Application of Agile Methodology to Logistics Management 
9.2.3. Outsourcing of Logistic Processes 
9.2.4. Picking or Efficient Order Picking 

9.3. Lean Logistics 

9.3.1. Lean Logistics in Supply Chain Management 
9.3.2. Analysis of Waste in the Logistics Chain 
9.3.3. Application of a Lean System in Supply Chain Management 

9.4. Warehouse Management and Automation 

9.4.1. The Role of Warehouses 
9.4.2. Warehouse Management 
9.4.3. Stocks Management 
9.4.4. Warehouse Typology 
9.4.5. Load Units 
9.4.6. Organization of a Warehouse 
9.4.7. Storage and Handling Elements 

9.5. Procurement Management 

9.5.1. The Role of Distribution as an Essential Part of Logistics. Internal Vs. External Logistics 
9.5.2. The Traditional Relationship with Suppliers 
9.5.3. The New Paradigm of Supplier Relationships 
9.5.4. How to Classify and Select New Suppliers? 
9.5.5. How to Develop Effective Procurement Management

9.6. Information Systems and Logistics Control 

9.6.1. Requirements of a Logistics Information and Control System 
9.6.2. 2 Types of Information Systems and Logistics Control 
9.6.3. Big Data Applications in Logistics Management 
9.6.4. The Importance of Data in Logistics Management 
9.6.5. The Balanced Scorecard Applied to Logistics Main Management and Control Indicators 

9.7. Reverse Logistics 

9.7.1. Keys to Reverse Logistics 
9.7.2. Reverse Vs. Direct Logistics Flows 
9.7.3. Operations within the Framework of Reverse Logistics 
9.7.4. How to Implement a Reverse Distribution Channel? 
9.7.5. Final Alternatives for Products in the Reverse Channel 
9.7.6. Costs of Reverse Logistics 

9.8. New Logistic Strategies 

9.8.1. Artificial Intelligence and Robotization 
9.8.2. Green Logistics and Sustainability 
9.8.3. Internet of Things Applied to Logistics 
9.8.4. The Digitized Warehouse 
9.8.5. E-businessand the New Distribution Models 
9.8.6. The Importance of Last Mile Logistics 

9.9. Retail Chain Benchmarking 

9.9.1. Commonalities of Successful Value Chains 
9.9.2. Inditex Group Value Chain Analysis 
9.9.3. Amazon Value Chain Analysis 

9.10. Pandemic Logistics 

9.10.1. General Scenario 
9.10.2. Critical Supply Chain Issues in a Pandemic Scenario 
9.10.3. Implications of Cold Chain Requirements on the Establishment of the Vaccine Supply Chain 
9.10.4. Types of Supply Chains for the Distribution of Vaccines

Module 10. Industry 4.0 and Business Intelligence The Digitized Company

10.1. Process Automation: RPA 

10.1.1. Automatable Administrative Processes 
10.1.2. Software Structure 
10.1.3. Examples of Application 

10.2. MES, SCADA, GMAO, SGA, MRPII Systems 

10.2.1. Product Control with MES Systems  
10.2.2. Engineering and Maintenance SCADA and GMAO 
10.2.3. Procurement and Logistics: SGA and MPRII 

10.3. Business Intelligence Software 

10.3.1. Fundamentals of BI 
10.3.2. Software Structure 
10.3.3. Application Possibilities 

10.4. ERP Software 

10.4.1. ERP Description 
10.4.2. Use Reach 
10.4.3. Leading ERPs in the Market 

10.5.  IoT and Business Intelligence 

10.5.1. IoT: the Connected World 
10.5.2. Data Sources 
10.5.3. Total Control through IoT + BI 
10.5.4. Blockchain 

10.6. Main BI Software in the Market 

10.6.1. PowerBI 
10.6.2. Qlik 
10.6.3. Tableau 
10.7. Microsoft POWER BI 
10.7.1. Features 
10.7.2. Examples of Application 
10.7.3. The Future of PowerBI 

Module 11. Internet of Things (IoT)

11.1. Cyber-physical Systems (CPS) in the Industry 4.0 Vision

11.1.1. Internet of Things (IoT)
11.1.2. Components Involved in IoT
11.1.3. Cases and Applications of IoT

11.2. Internet of Things and Cyber-Physical Systems

11.2.1. Computing and Communication Capabilities to Physical Objects
11.2.2. Sensors, Data and Elements in Cyber-Physical Systems

11.3. Device Ecosystem

11.3.1. Typologies, Examples and Uses
11.3.2. Applications of the Different Devices

11.4. IoT Platforms and Their Architecture

11.4.1. IoT Market Typologies and Platforms
11.4.2. Operation of an IoT Platform

11.5. Digital Twins

11.5.1. Digital Twin
11.5.2. Uses and Applications the Digital Twin

11.6. Indoor & Outdoor Geolocation (Real Time Geospatial)

11.6.1. Indoor and Outdoor Geolocation Platforms
11.6.2. Implications and Challenges of Geolocation in an IoT Project

11.7. Security Intelligence Systems

11.7.1. Typologies and Platforms for Security Systems Implementation
11.7.2. Components and Architectures in Intelligent Safety Systems

11.8. IoT and IIoT Platform Security

11.8.1. Security Components in an IoT System
11.8.2. IoT Security Implementation Strategies

11.9. Wearables at Work

11.9.1. Types of Wearables in Industrial Environments
11.9.2. Lessons Learned and Challenges in Implementing Wearables in the Workplace

11.10. Implementing an API to Interact with a Platform

11.10.1. Types of APIs Involved in an IoT Platform
11.10.2. API Market
11.10.3. Strategies and Systems to Implement API Integrations

Module 12. Industry 4.0 Automation Systems

12.1. Industrial Automation

12.1.1. Automization
12.1.2. Architecture and Components
12.1.3. Safety

12.2. Industrial Robotics

12.2.1. Fundamentals of Industrial Robotics
12.2.2. Models and Impact on Industrial Processes

12.3. PLC Systems and Industrial Control

12.3.1. PLC Evolution and Status
12.3.2. Evolution of Programming Languages
12.3.3. Computer Integrated Automation CIM

12.4. Sensors and Actuators

12.4.1. Classification of Transducers
12.4.2. Types of Sensors
12.4.3. Standardization of Signals

12.5. Monitor and Manage

12.5.1. Types of Actuators
12.5.2. Feedback Control Systems

12.6. Industrial Connectivity

12.6.1. Standardized Fieldbuses
12.6.2. Connectivity

12.7. Proactive / Predictive Maintenance

12.7.1. Predictive Maintenance
12.7.2. Fault Identification and Analysis
12.7.3. Proactive Actions Based on Predictive Maintenance

12.8. Continuous Monitoring and Prescriptive Maintenance

12.8.1. Prescriptive Maintenance Concept in Industrial Environments
12.8.2. Selection and Exploitation of Data for Selfdiagnostics

12.9. Lean Manufacturing

12.9.1. Lean Manufacturing
12.9.2. Benefits Lean Implementation in Industrial Processes

12.10. Industrialized Processes in Industry 4.0. Use Case

12.10.1 Project Definition
12.10.2. Technological Selection
12.10.3. Connectivity
12.10.4. Data Exploitation

Module 13. Blockchain and Quantum Computing

13.1. Aspects of Decentralization

13.1.1. Market Size, Growth, Companies and Ecosystem
13.1.2. Blockchain Fundamentals

13.2. Background: Bitcoin, Ethereum, etc.

13.2.1. Popularity of Decentralized Systems
13.2.2. Evolution of Decentralized Systems

13.3. Blockchain Operation and Examples

13.3.1. Types of Blockcahin and Protocols
13.3.2. Wallets, Mining and More

13.4. Characteristics of Blockchain Networks

13.4.1. Functions and Properties of BlockChain Networks
13.4.2. Applications: Cryptocurrencies, Reliability, Chain of Custody, etc

13.5. Types of Blockchain

13.5.1. Public and Private Blockchains
13.5.2. Hard and Soft Forks

13.6. Smart Contracts

13.6.1. Inteligent Contracts and Their Potential
13.6.2. Smart Contract Applications

13.7. Industry Use Models

13.7.1. Blockchain Applications by Industry
13.7.2. Blockchain Success Stories by Industry

13.8. Security and Cryptography

13.8.1. Objectives of Cryptography
13.8.2. Digital Signatures and Hash Functions

13.9. Cryptocurrencies and Uses

13.9.1. Types of Cryptocurrencies Bitcoin, HyperLedger, Ethereum, Litecoin, etc
13.9.2. Current and Future Impact of Cryptocurrencies
13.9.3. Risks and Regulations

13.10. Quantum Computing

13.10.1. Definition and Keys
13.10.2. Uses of Quantum Computing

Module 14. Big Data and Artificial Intelligence

14.1. Fundamental Principles of Big Data

14.1.1. Big Data
14.1.2. Tools to Work With Big Data

14.2. Data Mining and Warehousing

14.2.1. Data Mining Cleaning and Standardization
14.2.2. Information Extraction, Machine Translation, Sentiment Analysis, etc
14.2.3. Types of Data Storage

14.3. Data Intake Applications

14.3.1. Principles of Data intake
14.3.2. Data Ingestion Technologies to Serve Business Needs

14.4. Viewing Data

14.4.1. The Importance of Data Visualization
14.4.2. Tools to Carry It Out Tableau, D3, matplotlib (Python), Shiny®

14.5. Machine Learning

14.5.1. Understanding Machine Learning
14.5.2. Supervised and Unsupervised Learning
14.5.3. Types of Algorithms

14.6. Neural Networks (Deep Learning)

14.6.1. Neural Network: Parts and Functionality
14.6.2. Types of Networks CNN, RNN
14.6.3. Applications of Neural Networks; Image Recognition and Natural Language Interpretation
14.6.4. Generative Text Networks: LSTM Structure and Content | 41

14.7. Natural Language Recognition

14.7.1. PLN (Processing Natural Language)
14.7.2. Advanced PLN Techniques: Word2vec, Doc2vec

14.8. Chatbots and Virtual Assistants

14.8.1. Types of Assistants: Voice and Text Assistants
14.8.2. Fundamental Parts for the Development of an Assistant: Intents, Entities and Dialog Flow
14.8.3. Integrations: Web, Slack, WhatsApp, Facebook
14.8.4. Assistance Development Tools: DialogFlow, Watson Assistant

14.9. Emotions, Creativity and Personality in IA

14.9.1. We Understand How Detect Emotions Using Algorithms
14.9.2. Creating a Personality: Language, Expressions and Content

14.10. Future of Artificial Intelligence
14.11. Reflections

Module 15. Virtual, Augmented and Mixed Reality

15.1. Market and Tendencies

15.1.1. Current Market Situation
15.1.2. Reports and Growth by Different Industries

15.2. Differences Between Virtual, Augmented and Mixed Reality

15.2.1. Differences Between Immersive Realities
15.2.2. Immersive Reality Typology

15.3. Virtual Reality Cases and Uses

15.3.1. Origin and Fundamentals of Virtual Reality
15.3.2. Cases Applied to Different Sectors and Industries

15.4. Augmented Reality Cases and Uses

15.4.1. Origin and Fundamentals of Augmented Reality
15.4.2. Cases Applied to Different Sectors and Industries

15.5. Mixed and Holographic Reality

15.5.1. Origin, History and Fundamentals of Mixed and Holographic Reality
15.5.2. Cases Applied to Different Sectors and Industries

15.6. 360º Photography and Video

15.6.1. Camera Typology
15.6.2. Uses of 360 Images
15.6.3. Creating a Virtual Space in 360 Degrees

15.7. Virtual World Creation

15.7.1. Platforms for the Creation of Virtual Environments
15.7.2. Strategies for the Creation of Virtual Environments

15.8. User Experience (UX)

15.8.1. Components in the User Experience
15.8.2. Tools for the Creation of User Experiences

15.9. Devices and Glasses for Immersive Technologies

15.9.1. Device Typology on the Market
15.9.2. Glasses and Wearables Functioning, Models and Uses
15.9.3. Smart Glasses Applications and Evolution

15.10. Future Immersive Technologies

15.10.1. Tendencies and Evolution
15.10.2. Challenges and Opportunities

Module 16. 4.0 Industry

16.1. Definitions of 4.0 Industry

16.1.1. Features

16.2. Benefits of the 4.0 Industry

16.2.1. Key Factors
16.2.2. Main Advantages

16.3. Industrial Revolutions and Vision of Future

16.3.1. Industrial Revolutions
16.3.2. Keys Factors in Each Revolution
16.3.3. Technological Principles a Basis for Possible New Revolutions

16.4. The Digital Transformation of the Industry

16.4.1. Characteristics of the Digitization of the Industry
16.4.2. Disruptive Technologies
16.4.3. Applications in the Industry

16.5. Forth Industrial Revolution Key Principles of Industry 4.0

16.5.1. Definitions
16.5.2. Key Principles and Applications

16.6. 4.0 Industry and Industrial Internet

16.6.1. Origin of IIoT
16.6.2. Operation
16.6.3. Steps to Follow for its Implementation
16.6.4. Benefits

16.7. Smart Factory Principles

16.7.1. Smart Factory
16.7.2. Elements That Define a Smart Factory
16.7.3. Steps to Deploy a Smart Factory

16.8. Status of the 4.0 Industry

16.8.1. Status of the 4.0 Industry in Different Sectors
16.8.2. Barriers to the Implementation of 4.0 Industry

16.9. Challenges and Risks

16.9.1. DAFO Analysis
16.9.2. Challenges

16.10. Role of Technological Capabilities and the Human Factor

16.10.1. Disruptive Technologies in Industry 4.0
16.10.2. The Importance of the Human Factor Key Factor

Module 17. Leading Industry 4.0

17.1. Leadership Abilities

17.1.1. Human Factor Leadership Factors
17.1.2. Leadership and Technology

17.2. Industry 4.0 and the Future of Production

17.2.1. Definitions
17.2.2. Production Systems
17.2.3. Future of Digital Production Systems

17.3. Effects of Industry 4.0

17.3.1. Effects and Challenges

17.4. Essential Technologies in Industry 4.0

17.4.1. Definition of Technologies
17.4.2. Characteristics of Technologies
17.4.3. Applications and Impacts

17.5. Digitization of Manufacturing

17.5.1. Definitions
17.5.2. Benefits of the Digitization of Fabrication
17.5.3. Digital Twin

17.6. Digital Capabilities in an Organization

17.6.1. Development Digital Capabilities
17.6.2. Understanding the Digital Ecosystem
17.6.3. Digital Vision of the Business

17.7. Architecture Behind a Smart Factory

17.7.1. Areas and Functionalities
17.7.2. Connectivity and Security
17.7.3. Case Uses

17.8. Technology Markers in the Postcovid Era

17.8.1. Technological Challenges in the Postcovid Era
17.8.2. New Case Uses

17.9. The Era of Absolute Virtualization

17.9.1. Virtualisation
17.9.2. The New Era of Virtualization
17.9.3. Advantages

17.10. Current Situation in Digital Transformation Gartnet Hype

17.10.1. Gartnet Hype
17.10.2. Analysis of Technologies and Their Status
17.10.3. Data Exploitation

Module 18. Robotics, Drones and Augmented Workers

18.1. Robotics

18.1.1. Robotics, Societies and Cinema
18.1.2. Components and Parts of Robot

18.2. Robotics and Advanced Automation: Simulators, Cobots

18.2.1. Transfer of Learning
18.2.2. Cobots and Case Uses

18.3. RPA (Robotic Process Automatization)

18.3.1. Understanding RPA and its Functioning
18.3.2. RPA Platforms, Projects and Roles

18.4. Robot as a Service (RaaS)

18.4.1. Challenges and Opportunities for Implementing Raas Services and Robotics in Enterprises
18.4.2. Functioning of a Raas system

18.5. Drones and Automated Vehicles

18.5.1. Components and Functioning of Drones
18.5.2. Uses, Types and Applications of Drones
18.5.3. Evolution of Drones and Autonomous Vehicles

18.6. The Impact of 5G

18.6.1. Evolution of Communications and Implications
18.6.2. Uses of 5G Technology

18.7. Augmented Workers

18.7.1. Human-Machine Integration in Industrial Environments
18.7.2. Challenges in Worker-Robot Collaboration

18.8. Challenges in the Collaboration between Workers and Robots

18.8.1. Ethical Challenges in Robotics and Artificial Intelligence
18.8.2. Monitoring, Transparency and Traceability Methods

18.9. Prototyping, Components and Evolution

18.9.1. Prototyping Platforms
18.9.2. Phases to Make a Prototype

18.10. Future of Robotics

18.10.1. Trends in Robotization
18.10.2. New Types of Robots

Module 19. Industry 4.0 - Industry Services and Solutions (I)

19.1. Industry 4.0 and Business Strategies

19.1.1. Factors of Business Digitalization
19.1.2. Roadmap for Business Digitalization

19.2. Digitalization of Processes and the Value Chain

19.2.1. The Vale Chain
19.2.2. Key Steps in the Digitization of Processes

19.3. Sector Solutions Primary Sector

19.3.1. The Primary Economic Sector
19.3.2. Characteristics of Each Subsector

19.4. Digitization of the Primary Sector: Smart Farms

19.4.1. Main Characteristics
19.4.2. Keys Factors of Digitization

19.5. Digitization of the Primary Sector: Digital Agriculture and Intelligence

19.5.1. Main Characteristics
19.5.2. Keys Factors of Digitization

19.6. Sector Solutions Secondary Sector

19.6.1. The Secondary Economic Sector
19.6.2. Characteristics of Each Subsector

19.7. Digitization of the Secondary Sector: Smart Factory

19.7.1. Main Characteristics
19.7.2. Keys Factors of Digitization

19.8. Digitization of the Secondary Sector: Energy

19.8.1. Main Characteristics
19.8.2. Keys Factors of Digitization

19.9. Digitization of the Secondary Sector: Construction

19.9.1. Main Characteristics
19.9.2. Keys Factors of Digitization

19.10. Digitization of the Secondary Sector: Mining

19.10.1. Main Characteristics
19.10.2. Keys Factors of Digitization

Module 20. Industry 4.0 - Industry Services and Solutions (II)

20.1. Tertiary Sector Solutions

20.1.1. Tertiary Economic Sector
20.1.2. Characteristics of Each Subsector

20.2. Digitization of the Tertiary Sector: Transport

20.2.1. Main Characteristics
20.2.2. Keys Factors of Digitization

20.3. Digitization of the Tertiary Sector: e-Health

20.3.1. Main Characteristics
20.3.2. Keys Factors of Digitization

20.4. Digitization of the Tertiary Sector: Smart Hospitals

20.4.1. Main Characteristics
20.4.2. Keys Factors of Digitization

20.5. Digitization of the Tertiary Sector: Smart Cities

20.5.1. Main Characteristics
20.5.2. Keys Factors of Digitization

20.6. Digitization of the Tertiary Sector: Logistics

20.6.1. Main Characteristics
20.6.2. Keys Factors of Digitization

20.7. Digitization of the Tertiary Sector: Tourism

20.7.1. Main Characteristics
20.7.2. Keys Factors of Digitization

20.8. Digitization of the Tertiary Sector: Fintech

20.8.1. Main Characteristics
20.8.2. Keys Factors of Digitization

20.9. Digitization of the Tertiary Sector: Mobility

20.9.1. Main Characteristics
20.9.2. Keys Factors of Digitization

20.10. Future Technological Tendencies

20.10.1. New Technological Innovations
20.10.2. Application Trends

A highly academic program that will be fundamental for your professional development"