Introducing Industry 4.0

Technology always played an essential role in human history so much so we refer to past human societies using as defining factor the most advanced technology they mastered. Expressions such as stone or iron age are good examples of this trend. The rationale for depicting past human societies this way resides in the direct link between technology development, new capabilities acquisition, societies prosperity and human lifestyle.

A history of industrial revolutions.

In recent human history, the development of new technologies resulted on several occasions in an acceleration of our ability to produce goods, leading to the concept of industrial revolution. As shown in Figure 1, the first industrial revolution started at the end of the 18th century with the harnessing of steam power as an energy source for mechanisation development (Hermann et al., 2016). Around 1870 the invention of electricity, followed by that of internal combustion engines led to the second industrial revolution characterised by mass production of goods, supported by the implementation of assembly lines (i.e., Fordism) and new scientific management (i.e., Taylorism) (Hermann et al., 2016). A century later, electronics' progress led to computers and robots invention, allowing the automation of many industrial processes and giving birth to the third industrial revolution (Hermann et al., 2016).

Figure 1: An history of industrial revolutions, by (Gökalp et al., 2017).

Since the beginning of the 21st century, the progress made in information/communication technologies and computer science led to a fourth industrial revolution, also known as Industry 4.0 (Saucedo-Martínez et al., 2017). The concept of Industry 4.0 was first proposed in 2011 at the Hanover trade fair by a multidisciplinary group of representative seeking to enhance Germany’s manufacturing industry competitiveness (Hofmann and Rüsch, 2017). 

Industry 4.0: A definition attempt.

Since 2011, the concept of Industry 4.0 has been taken over by academics and practitioners alike. Today the concept does not exclusively apply to the industrial production of goods. Industry 4.0 can be implemented everywhere, where processes need to get more intelligent, including the service industry. Due to its constant evolution and the diversity of applications and practitioners involved in Industry 4.0, it has been challenging to build a consensual definition. Agostini, A et al., state that: “Industry 4.0 refers to the integration of physical objects, human actors, intelligent machines, production lines and processes across organisational boundaries, meant to form a system in which all processes are integrated and share information in a real-time frame (Agostini, 2019). Although many other definitions exist, they all tend to emphasise the reliance on automation systems, the necessity to connect the physical and virtual worlds through digitalisation and to change relationships and communication with stakeholders at all levels. These orientations are illustrated in the design principles of Industry 4.0, shown in Figure 2, and widely accepted by the Industry 4.0 community. 

Figure 2: Industry 4.0. design principles adapted from (Hermann et al., 2015).

Industry 4.0 enabling technologies.

As said earlier, past industrial revolutions relied on new technologies often one or a couple. However, the impact of past industrial revolutions on our societies at different level (i.e., demographic, scientific, economic), resulted in the exponential development of new technologies in various areas. Therefore, Industry 4.0 singularity resides in the extensive range of technologies involved and the synergies arising from their integration in producing goods and services. Figure 3 presents a non-exhaustive list of Industry 4.0 enabling technologies, which allows the implementation of the principles previously evoked. For instance, Internet of Things (IoT) devices (i.e., Internet-connected devices) of which Industrial Internet of Things (IIoT) devices are a subcategory, allows collaborators to communicate at a distance with each other's and with assembly lines assets in near real-time. Also, location detection technologies such as Radio Frequency Identification (RFID) tags changed how companies track items and manage warehouses. The rise of Additive Manufacturing, that is to say 3D-printing has considerably accelerated prototypes and spares manufacturing and testing, leading respectively to a reduction in time to market of new products and assembly line machines downtime. Finally, the ability to collect and store large amounts of data related to all aspects of a business through cloud computing, coupled with their exploitation by artificial intelligence algorithms, allows companies to improve their functioning continually. Thus, Industry 4.0 technologies implementation enable companies to adapt faster to their changing business environment (e.g., competition landscape, consumers taste evolution).

Figure 3: Industry 4.0 key enabling technologies from (Geissbauer et al., 2016).

Industry 4.0 related concepts.

Implementing industry 4.0 design principles through its enabling technologies led to the creation of new concepts illustrating the newly acquired capabilities. Thus, the idea of Smart Factory emerged describing "A flexible system that can self-optimise performance across a broader network, self-adapt to and learn from new conditions in real or near-real time, and autonomously run entire production processes." (Burke et al., 2017). 

Smart factories heavily rely on Cyber-Physical Systems (CPS), which are “Multidimensional and complex systems that integrate the cyber world and the dynamic physical world, providing real-time sensing, information feedback dynamic control of assets.”(Tao et al., 2019). Computing, communication, and control, known as the ''3C", are at the heart of CPS functioning. As shown in Figure 4, CPS allows the integration of the physical world (e.g., machine, robots) and the cyber world (e.g., IT infrastructure) through connected sensors and readers. The data produced by those sensors and readers are collected and analysed in the cyber world to generate results supporting decision making by shopfloor workers and executives alike. These decisions are then implemented through the cyber interface via connected actuators (Tao et al., 2019). CPS should not be mistaken with Digital Twins (DT), although both integrate the cyber and the dynamic physical world. Unlike CPS, DT focuses on the detailed virtual modelling of a physical asset in a one-to-one correspondence, while CPS emphasises the 3C capabilities in a one-to-many correspondence (Tao et al., 2019).

Figure 4: Cyber-Physical Systems (CPS) illustration by (Tao et al., 2019). 

Industry 4.0 also seeks further integration of stakeholders at all level of the value chain.  In the context of Industry 4.0, horizontal integration is concerned with the sharing of information throughout the value chain as well as with consumers, using an integrated information technology network (Saucedo-Martínez et al., 2017). On the other end, vertical integration in Industry 4.0's context, is concerned with integrating information technologies at various hierarchy levels at a given factory/stakeholder. In this regard, CPS can be view as vertical integration systems. Ultimately, the combination of vertical and horizontal integrations leads to end-to-end integration or digitalisation of the entire value chain. As best said by PwC Industry 4.0 experts: “While Industry 3.0 focused on the automation of single machines and processes, Industry 4.0 focuses on the end-to-end digitisation of all physical assets and integration into digital ecosystems with value chain partners. Generating, analysing and communicating data seamlessly underpins the gains promised by Industry 4.0, which networks a wide range of new technologies to create value.” (Geissbauer et al., 2016).

References

AGOSTINI, L. 2019. Organizational and managerial challenges in the path toward Industry 4.0. European Journal of Innovation Management, 22, 406-421.

BURKE, R., MUSSOMELI, A., LAAPER, S., HARTIGAN, M. & SNIDERMAN, B. 2017. The smart factory: Responsive, adaptive, connected manufacturing. Deloitte University Press.

GEISSBAUER, R., VEDSO, J. & SCHRAUF, S. 2016. Industry 4.0: Building the digital enterprise [Online]. https://www.pwc.com: Pwc. Available: https://www.pwc.com/gx/en/industries/industries-4.0/landing-page/industry-4.0-building-your-digital-enterprise-april-2016.pdf [Accessed 07th August 2019].

GÖKALP, E., ŞENER, U. & EREN, P. E. Development of an Assessment Model for Industry 4.0: Industry 4.0-MM. In: MAS, A., MESQUIDA, A., O'CONNOR, R. V., ROUT, T. & DORLING, A., eds. Software Process Improvement and Capability Determination, 2017// 2017 Cham. Springer International Publishing, 128-142.

HERMANN, M., PENTEK, T. & OTTO, B. 2015. Design Principles for Industrie 4.0 Scenarios: A Literature Review.

HERMANN, M., PENTEK, T. & OTTO, B. 2016. Design Principles for Industrie 4.0 Scenarios. IEEE.

HOFMANN, E. & RÜSCH, M. 2017. Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, 89, 23-34.

SAUCEDO-MARTÍNEZ, J. A., PÉREZ-LARA, M., MARMOLEJO-SAUCEDO, J. A., SALAIS-FIERRO, T. E. & VASANT, P. 2017. Industry 4.0 framework for management and operations: a review. Journal of Ambient Intelligence and Humanized Computing, 9, 789-801.

TAO, F., QI, Q., WANG, L. & NEE, A. Y. C. 2019. Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison. Engineering, 5, 653-661.