Master
2023/2024
Industry 4.0
Type:
Elective course (Science, Technology and Innovation Management and Policy)
Area of studies:
Management
Delivered by:
Department of Educational Programmes
When:
2 year, 2 module
Mode of studies:
offline
Open to:
students of all HSE University campuses
Instructors:
Thomas Thurner
Master’s programme:
Governance of Science, Technology and Innovation
Language:
English
ECTS credits:
3
Contact hours:
32
Course Syllabus
Abstract
The course consists of one module and is designed for master students of the National Research University Higher School of Economics (HSE). The course length is 114 academic hours in total of which 32 hours are class room hours for lectures and 82 hours are devoted to self study. This course provides an introduction to Industry 4.0. Industry 4.0 describes the combination of digital technologies with traditional industrial processes and covers the entire ‘intelligent‘ value chains from design and development, production, delivery, maintenance, and recycling. The term Industry 4.0 – also labelled the fourth industrial revolution – builds on three earlier technological shifts: steam power, electrification of production and assembly lines, and the integration of automation principles. This development has become possible due to advances in sensor technology and connectivity modules which enabled data gathering throughout industrial processes and the central conversion into decision-relevant information. These cconnected devices connect with the larger Internet of Things (IoT) and the resulting data is used and enhanced by machine learning algorithms. These set of technologies though are seen as central for competitiveness of entire nations, which is why these topics have benefitted greatly from policy initiatives. The German Industry 4.0 platform – mainly pushed by the national government and industry association – has become the name for the present development stage. Also, other national governments pursue similar High-Tech Strategy Action Plans. Besides the major upgrade of the technological infrastructure, the new production paradigm also requires a much more knowledge-intense skill-set of new managers. In turn, the benefit for manufacturers lies in a more efficient use of inputs, better product quality, more customization and logistics. The combining language that allows for these benefits to happen is real-time data production and analysis. The integration of data flows with the steering of of the fourth industrial revolution are termed Smart Factories. Digital platforms in the Cloud are the place that convert data into new business models.
Learning Objectives
- Industry 4.0 components such as: automation, data exchanges, cloud, cyber-physical systems, mobile, robots, Big Data, deep machine learning, IoT, distributed systems and agile methodology.
- Convergence between consumer and industrial applications, evolution of connectivity technologies and data processing.
- Study how technology applications in Industry 4.0 will change industrial production
- Study how Industry 4.0 contributes to competitive advantages from a management perspective
- Strategize how businesses in different industries can benefit from Industry 4.0, in line with their needs and opportunities
Expected Learning Outcomes
- Comprehend Business model innovation through Industry 4.0
- Comprehend IoT, cyber-physical systems, cloud computing and big data, smart factories and their role in Industry 4.0
- Understand drivers and enablers of Industry 4.0, including policy support
- Understand the nature of the fourth industrial revolution and theoretical concepts
- Understand the opportunities, and challenges brought through Industry 4.0
Course Contents
- Industry 4.0: Design Principles
- Building Blocks of Industry 4.0: Cyber Physical Systems 1
- Building Blocks of Industry 4.0: Cyber Physical Systems 2
- Industry 4.0 and Technologies 1
- Industry 4.0 and Technologies 2
- Data storage and data security
- Aligning Industry 4.0 and Strategies. Advanced Manufacturing Process Analysis
- Industry 4.0 and the national high technology strategies
Bibliography
Recommended Core Bibliography
- Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: a literature review. International Journal of Production Research, 57(15/16), 4719–4742. https://doi.org/10.1080/00207543.2017.1402140
- Dijkman, R. R., Sprenkels, B., Peeters, T. T., & Janssen, A. (2015). Business models for the internet of things. ISSN:0268-4012.
Recommended Additional Bibliography
- Jay Lee, Behrad Bagheri, & Hung-an Kao. (2014). Recent Advances and Trends of Cyber-Physical Systems and Big Data Analytics in Industrial. Https://Www.Researchgate.Net/Profile/Behrad_Bagheri/Publication/266375284_Recent_Advances_and_Trends_of_Cyber-Physical_Systems_and_Big_Data_Analytics_in_Industrial_Informatics/Links/542dc0100cf27e39fa948a7d.Pdf.