The digitalization of supply chains, especially within the realm of industrial production, represents a pivotal evolution in the way goods and services are delivered and managed. Central to the digitalization of supply chains is the deployment of AI and IoT. These technologies enable the collection and analysis of vast amounts of data across the supply chain. IoT devices offer real-time tracking and monitoring capabilities, providing granular visibility over each step of the supply chain. AI, including machine learning, evolutionary algorithms, fuzzy logic, and agent-based models, plays a crucial role in interpreting this data, facilitating more informed decision-making processes and optimizing operations.

The heart of digitalized supply chain management lies in the ability to gather and analyze data effectively. This course emphasizes the importance of advanced data analytics in understanding and optimizing supply chain processes. By analyzing data from customer-supplier chains and internal operations, businesses can streamline processes, reduce inefficiencies, and ultimately enhance the value delivered to customers.

One of the standout features of a digitalized supply chain is the capacity for real-time oversight. This capability ensures that all stakeholders have up-to-the-minute information on the status of goods, from production through to delivery. Such transparency not only enhances operational efficiency but also builds trust between consumers, suppliers, and manufacturers.

The course underscores the significance of integrating digital technologies throughout the entire supply chain network. This holistic approach ensures that every segment of the chain, from procurement of raw materials to the delivery of finished products, is optimized for efficiency and responsiveness. This integration is key in creating what are termed ‘connected factories,’ which are central to generating valuable data streams in primary processes.

Implementing a digitalized supply chain is not without its challenges. The course explores the complexities involved in designing, implementing, and managing digitalized supply chains. These include the substantial initial investment in technology, the need for skilled personnel to manage these systems, and the crucial aspect of cybersecurity in an increasingly connected and data-rich environment. A significant advantage of digitalized supply chains highlighted in the course is their potential for sustainability. Optimized routes and processes not only improve efficiency but also reduce environmental impact. The course explores how digitalized supply chains can be designed to be not just economically viable but also environmentally responsible.

Total Hours

This course unit covers 100 hours, from which 14 hours lectures, 14 hours lab work, and 72 hours individual study and work.

General Objective

The overarching objective of the Digitalization of Supply Chains course is to equip students with a holistic and in-depth understanding of both the challenges and the innovative solutions prevalent in managing modern supply chains, particularly those driven by specialized platforms and software applications in industrial production. The course aims to endow students with critical knowledge and skills in areas such as network architecture and data distribution, comprehensive threat analysis, and risk assessment. Furthermore, it emphasizes the development of competencies in devising and implementing strategies to mitigate risks in supply chains. A key component of the course is the exploration of Artificial Intelligence integration within supply chain management, highlighting its role in augmenting efficiency and minimizing human errors. This comprehensive educational approach is designed to prepare students to adeptly navigate and contribute to the evolving landscape of digitalized supply chain management.

Specific Objectives / Learning Outcomes

The specific objectives of the Digitalization of Supply Chains course are as follows:

  • Comprehend Key Concepts and Principles: Students will gain an in-depth understanding of the fundamental concepts and principles that govern industrial supply chains. This includes a focus on the architecture of distribution networks and the various modes of communication integral to effective supply chain management.
  • Analyze Threats and Perform Risk Assessments: The course will equip students with the analytical skills necessary to assess the threat landscape specific to industrial distribution networks. Students will learn to perform detailed risk assessments, identifying potential disruptors that could impact the efficiency and security of the supply chain.
  • Utilization of Tools and ERP Systems: Students will learn how to effectively use various tools and techniques, particularly dedicated Enterprise Resource Planning (ERP) systems, to streamline activities within distribution chains. This objective focuses on the practical application of technology to optimize supply chain processes.
  • Implement AI and IoT Technologies: A significant part of the course is dedicated to teaching students about the implementation and use of Artificial Intelligence in conjunction with Internet of Things (Industrial IoT) technologies. This includes the use of RFID smart labels, SMART scales, and scanners for efficient data acquisition processes within distribution chains.
  • Understand Emerging Trends and Future Directions: Finally, students will explore and gain knowledge about the emerging trends and potential future advancements in streamlining industrial supply chains. This objective aims to prepare students to be forward-thinking and adaptable to future developments in the field.

These specific objectives collectively aim to provide a comprehensive, practical, and forward-looking educational experience, preparing students to effectively manage and innovate in the field of industrial supply chain digitalization.

Professional Competencies

The Digitalization of Supply Chains course is structured to impart specific professional competences that are essential for students aspiring to excel in the field of industrial supply chain management. These competences are:

  • In-depth Knowledge of Industrial Supply Chain Management: A core professional competence developed through this course is a comprehensive understanding of industrial supply chain management. This encompasses grasping the fundamental concepts, techniques, and best practices associated with the operation of industrial supply chains. Students will delve into risk analysis, learning to assess potential disruptive factors, and understanding the policies and procedures applied in the effective management of supply chains. This knowledge base is critical for addressing the complexities and challenges inherent in modern industrial supply chain operations.

  • Mastery of Industrial Supply Network Architecture and Communication Channels: The course equips students with a thorough understanding of the architecture of industrial supply networks. This includes learning about the methodologies and technologies used for data transmission within these networks, especially through computer systems. A strong grasp of network architecture and communication channels is vital for ensuring seamless data flow and coordination across various segments of the supply chain.

  • Proficiency in Technologies and Tools to Streamline Supply Chains: A significant focus of the course is on educating students about the various technologies and tools that can be utilized to digitize and streamline industrial supply chain processes. This includes an in-depth exploration of how Artificial Intelligence (AI) can be integrated into supply chain operations to minimize human error and enhance efficiency. Students will gain hands-on experience with state-of-the-art tools and technologies, preparing them to implement these solutions in real-world scenarios effectively.

These professional competences ensure that students not only acquire theoretical knowledge but also develop practical skills essential for managing and improving industrial supply chains. This comprehensive skill set is pivotal in preparing them for a successful career in supply chain management, enabling them to contribute innovatively and effectively in a rapidly evolving industrial landscape.

Cross Competencies

The cross-competences developed through the Digitalization of Supply Chains course are integral to shaping well-rounded professionals equipped to handle the dynamic challenges of modern industrial supply chains. These competences include:

  • Critical Thinking: This course emphasizes the development of critical thinking skills, crucial for navigating the complexities of industrial supply chains. Students will engage in analyzing various supply chain models, identifying potential threats, and assessing disruptive factors. They will learn to formulate effective countermeasures to mitigate risks, requiring a deep understanding of the intricacies of supply chain dynamics and the ability to think critically about multifaceted problems.
  • Problem Solving: Problem-solving is a key competence in this course, focusing on optimizing activities within industrial distribution networks. Students will learn to apply theoretical knowledge to real-world scenarios, developing practical solutions to enhance efficiency and productivity in supply chains. This involves identifying bottlenecks, streamlining processes, and implementing technological solutions, all requiring adept problem-solving skills.
  • Communication: Effective communication is paramount in the management of supply chains, especially when addressing disruptions. The course will train students to communicate clearly and effectively, both in writing and verbally, to various stakeholders. This skill is essential for mitigating the effects of disruptive factors, ensuring coordinated efforts, and maintaining the smooth operation of supply chains in both internal and external organizational environments.
  • Collaboration: Collaboration is a critical skill in the context of supply chain management, and this course facilitates its development through team-based laboratory exercises and case studies. Students will learn to work collaboratively, coordinating with peers to successfully complete tasks. This teamwork not only enhances the learning experience but also simulates real-world scenarios where collaboration is key to achieving supply chain objectives.
  • Adaptability: In an ever-evolving field like supply chain management, adaptability is a crucial competence. The course prepares students to be flexible and responsive to changes in supply chain architecture and emerging technologies. Students will learn to embrace and adapt to new tools and methodologies, ensuring that they can contribute to making supply chains more efficient and resilient in the face of change.

Together, these cross-competences form the foundation of a comprehensive skill set that enables students to effectively manage and innovate within the field of supply chain digitalization, preparing them for a wide range of challenges and opportunities in their professional careers.

Alignment to Social and Economic Expectations

The Digitalization of Industrial Supply Chains course is meticulously designed to align with the evolving social and economic expectations in the global landscape. This alignment is evident in several key aspects:

  • Responding to Globalization Trends: In an era where globalization is intensifying, supply chains across all industrial sectors are undergoing rapid transformation. The course recognizes this dynamic environment and addresses the growing need for digitization and the integration of Artificial Intelligence (AI) in supply chain management. By staying abreast of global trends and the resultant shifts in supply chain architecture, the course ensures that its curriculum is relevant and forward-thinking.
  • Preparation for Efficient Supply Chain Management: The course equips students with vital knowledge and skills for the efficient management of industrial supply chains. This aspect is crucial in maintaining the continuity of production processes, enhancing productivity, and ensuring high-quality output. In a world where economic performance is closely tied to supply chain efficiency, the competencies developed through this course are directly aligned with economic expectations.
  • Focus on Quality and Error Reduction: Emphasizing the role of AI in minimizing human errors aligns with the societal expectation for safer, more reliable industrial operations. The course prepares students to implement technologies that not only streamline processes but also enhance the accuracy and reliability of these processes, thereby contributing to overall quality improvements in industrial outputs.
  • Meeting Social Expectations for Timely and Efficient Operations: The course acknowledges the societal demand for timely, efficient, and seamless industrial operations. By training students in the latest digitization techniques and technologies, it ensures that graduates are capable of contributing to supply chains that meet these social expectations, leading to the achievement of desired economic and societal outcomes.
  • Economic and Social Sustainability: Lastly, the course aligns with the growing societal and economic emphasis on sustainability. By teaching students how to optimize supply chain processes and implement sustainable practices, the course contributes to the broader goal of sustainable economic growth and responsible industrial practices.

Assessment Methods

Theoretical Lectures Component:

  • Quizzes: Regular in-class and online quizzes will assess students’ understanding of key concepts in supply chain digitalization, such as ERP systems, AI integration, and SMART technologies.
  • Written Assignments: Students will be required to submit assignments exploring and critically analyzing the application of digitalization technologies in industrial supply chains, focusing on problem-solving and practical application of theoretical knowledge.
  • Midterm and Final Exams: Comprehensive exams will evaluate students’ overall grasp of the course material. These exams will include multiple-choice, short answer, and essay questions, particularly focused on the digitalization of supply chains and its implications.

Practical Laboratory Component:

  • Lab Reports: Students must submit comprehensive lab reports documenting their experiments and projects in supply chain digitalization, focusing on methodology, results, and analytical insights.
  • Oral Presentations: Students will present their lab projects, assessed based on presentation skills, content clarity, and their ability to engage the audience, especially focusing on the solutions developed in supply chain digitalization.

Assessment Criteria

Lectures Component:

  • Knowledge and Understanding: Evaluating students’ comprehension and application of core concepts in supply chain digitalization.
  • Analytical and Problem-Solving Skills: Assessing the ability to analyze complex supply chain challenges and effectively apply digitalization solutions.
  • Communication Skills: Gauging proficiency in clearly and engagingly conveying concepts and solutions in supply chain digitalization.
  • Teamwork and Collaboration: Evaluating the ability to work effectively in teams, particularly in group projects involving supply chain digitalization.
  • Application of Technology: Assessing proficiency in using digitalization tools and understanding their application in supply chain management.

Laboratory Work Component:

  • Technical Skills: Evaluating competence in applying technical skills to develop practical digitalization solutions in supply chains.
  • Quality of Work: Assessing the ability to produce high-quality, innovative digitalization applications for supply chains.
  • Creativity and Innovation: Gauging capacity for creative thinking and innovation in developing supply chain digitalization solutions.
  • Attention to Detail: Evaluating thoroughness in documenting and executing supply chain digitalization projects.
  • Time Management: Assessing effectiveness in managing time to complete lab tasks and projects.

Quantitative Performance Indicators

For Lectures:

  • Attendance and Participation: Minimum 80% attendance and active participation in class discussions required.
  • Homework and Quizzes: Completion of all assignments and quizzes with a minimum average score of 60%.
  • Midterm Exam: Minimum score of 50% required.

For Lab Works:

  • Lab Attendance and Participation: Full attendance and active participation in lab sessions required.
  • Lab Reports: Timely submission of all lab reports, each scoring a minimum of 60%.
  • Lab Assignments: Completion of all lab assignments with a minimum average score of 60%.
  • Lab Exams: Minimum score of 50% required on lab exams.

For Final Exam:

  • Comprehensive Understanding of Course Material: Minimum 70% of total questions correctly answered.
  • Demonstrating Understanding of Key Concepts: Minimum 50% score on multiple-choice and short-answer questions.
  • Analysis of Case Studies: Minimum 50% score on case study analysis questions.
  • Knowledge of Technologies, Tools, and Methodologies: Minimum 50% score on matching or labeling questions.
  • Application of Concepts to Practical Problems: Minimum 50% score on problem-solving questions.
  • Critical Evaluation of Digitization Impacts: Minimum 50% score on essay questions.
  • Evidence of Practical Application: Demonstrated through correctly answered application-based questions.
  • Display of Critical Thinking Skills: Evidenced by correct answers to analytical and synthesis questions.
  • Overall Exam Performance: Evaluated as a percentage of the total exam score, with a minimum passing mark of 50% or above.

This assessment framework ensures a comprehensive and balanced evaluation of both the theoretical knowledge and practical skills acquired in the course on Digitalization of Supply Chains.


Unit 1: Introduction to Supply Chains Field (2 hours)

  • Comprehensive overview of the supply chain field, including fundamental concepts and historical evolution.
  • Examination of key components and functions of modern supply chains in various industries.
  • Interactive discussion on the significance of efficient supply chain management in contemporary industrial operations.

Unit 2: Architecture and Communication Channels in Supply Chains (2 hours)

  • Detailed exploration of the architecture of supply chains, focusing on structural design and operational flow.
  • Analysis of various communication channels used in supply chains and their impact on efficiency and transparency.
  • Case studies on successful supply chain architecture and communication strategies in leading industries.

Unit 3: Identifying, Analyzing, and Countering Disruptive Factors in Industrial Supply Chains (2 hours)

  • Introduction to common disruptive factors in industrial supply chains and their potential impacts.
  • Techniques and methodologies for analyzing and identifying risks and vulnerabilities in supply chains.
  • Strategies and best practices for countering disruptions, including contingency planning and risk mitigation.

Unit 4: Use of Software Platforms Specific to Supply Chain Management (2 hours)

  • Overview of specialized software platforms used in supply chain management, including ERP systems.
  • Demonstration of key features and capabilities of various supply chain management software.
  • Practical session: Students engage in a simulated exercise using a supply chain management software platform.

Unit 5: Implementation of SMART Equipment in the Data Acquisition Process Needed in Supply Chain Management (2 hours)

  • Introduction to SMART equipment (e.g., IoT devices, RFID technology) and their roles in data acquisition.
  • Case studies demonstrating the integration and benefits of SMART equipment in supply chain management.
  • Hands-on workshop: Students participate in a practical exercise involving the setup and use of SMART data acquisition tools.

Unit 6: The Use of Artificial Intelligence in Essential Activities of Supply Chains (2 hours)

  • Exploration of AI applications in key areas of supply chain management, such as forecasting, optimization, and error reduction.
  • Discussion on the transformational impact of AI on supply chain efficiency and decision-making.
  • Group activity: Students analyze real-world scenarios where AI significantly improved supply chain operations.

Unit 7: Future Trends in the Process for the Digitalization of Supply Chains (2 hours)

  • Presentation on emerging trends and future developments in the digitalization of supply chains.
  • Discussion on the potential impact of new technologies and methodologies on supply chain management.
  • Brainstorming session: Students explore and present ideas on future innovations in supply chain digitalization.
Lab Work

Lab 1: Analyzing the Particularities of the Supply Chain (2 hours)

  • Objective: To understand and identify the unique characteristics and challenges of different types of supply chains.
  • Activities: Students will analyze case studies of various supply chains, identifying their distinct features. This includes a focus on industries such as manufacturing, production of food, etc. Students will also discuss the implications of these particularities on supply chain management strategies.

Lab 2: Design/Modeling of Supply Chains (2 hours)

  • Objective: To gain skills in designing and modeling efficient supply chains using simulation software.
  • Activities: Students will use supply chain modeling tools to design supply chain networks. The session includes creating a supply chain model from scratch, simulating different scenarios, and analyzing the outcomes for efficiency and effectiveness.

Labs 3 & 4: Utilizing ERP-type Platforms for Supply Chain Digitalization and Planning (4 hours)

  • Objective: To learn how to use Enterprise Resource Planning (ERP) platforms for managing and planning supply chain activities.
  • Activities: This lab will involve hands-on training with an ERP software. Students will simulate the planning and management of supply activities, including procurement, inventory management, and logistics. They will also learn to interpret data and reports generated by the ERP system.

Labs 5 & 6: Using Smart Peripheral Equipment in Supply Activities (4 hours)

  • Objective: To understand and apply the use of smart technologies like RFID tags, scanners, and SMART weighing in supply chain activities.
  • Activities: Students will engage in practical exercises involving the setup and use of RFID tags, scanners, and SMART weighing scales. This includes tagging items, scanning, and weighing them, and analyzing how this data integrates into a supply chain management system.

Lab 7: Implementation of AI in Optimizing Supply Activities (2 hours)

  • Objective: To explore and implement AI-driven strategies for optimizing supply chain operations.
  • Activities: Students will work with AI tools and software to optimize different aspects of the supply chain. This may include demand forecasting, route optimization, and inventory management. The session will involve both theoretical understanding and practical implementation of AI algorithms.
Supporting Infrastructure

To support the course Digitalization of Supply Chains, a specific set of infrastructure is allocated. Here’s a detailed breakdown:

  • Computer Network:

    • A high-speed, reliable computer network is used for connecting all the digital tools and platforms.
    • Sufficient bandwidth to support ERP software, CAD systems, virtual reality applications, and any additional online resources or databases.
    • Network security measures, including firewalls and encryption, to protect sensitive data and ensure secure data transmission.
  • ERP Platform – Asis RIA and B-Org:

    • These specialized ERP platforms with dedicated servers to run effectively.
    • Workstations with the necessary specifications and software installed for students to access and utilize these ERP systems.
    • Training materials and documentation for both Asis RIA and B-Org to facilitate learning and practical application.
  • 3D Printers:

    • Several high-quality 3D printers capable of producing detailed models and prototypes.
    • A dedicated space for 3D printing activities, including proper ventilation and storage for materials like filaments and resins.
    • Software for designing 3D models and preparing them for printing.
  • CAD Systems with Virtual Reality Glasses:

    • Computers with powerful graphics capabilities and processing power to run advanced CAD software and virtual reality applications.
    • Virtual reality headsets and possibly other accessories (like hand controllers) for a fully immersive experience.
    • Software licenses for CAD programs that are compatible with virtual reality technology.
  • Systems for Neuromarketing:

    • Equipment for neuromarketing studies, such as EEG headsets, and biometric sensors.
    • Software for collecting and analyzing neuromarketing data.
    • A controlled environment for conducting neuromarketing experiments, ensuring accurate and reliable data collection.
  • General Infrastructure:

    • Adequate power supply and backup solutions to support all equipment and prevent data loss.
    • Comfortable, ergonomically designed workspaces to accommodate students and instructors.
    • High-quality audio-visual equipment for demonstrations and presentations.