Towards I4.0: A comprehensive analysis of evolution from I3.0

Highlights

• Industry 3.0: Centralized, monolithic and complex Manufacturing Systems.

• Industry 4.0: Distributed, modular and collaborative Manufacturing Systems.

• Overambitious Marketing confuses Technological Infrastructure with Possibilities.

• The Infrastructure to Technological Possibilities is under construction yet.

• Technological Possibilities on I3.0 cannot take full advantage of I4.0 platform yet.

Abstract

Advances in Information Technology and Communications are leading to a paradigm shift in manufacturing automation systems. Based on the Internet of Things (IoT) and Smart Technologies, manufacturing industries are witnessing the fourth Industrial Revolution, coined as Industrie 4.0 (I4.0). Although many studies related to this subject were published, including several literature reviews, there is no consensual definition of I4.0. Consequently, there is not a clear understanding of the underlying enabling technologies required to implement it. That makes it more difficult for players to plan a migration strategy. This paper proposes a technological pathway infrastructure from Industry 3.0 (I3.0) to I4.0, based on the analysis of research and academic involvement in this transition process. A bibliometric study was directed to academic work, while field research addressed industry practitioners.

The purpose of field research is to understand the impact of the knowledge about the transition from I3.0 up to I4.0. The contribution of this study includes a construct showing the fundamental technology infrastructure to pave the way from I3.0 up to I4.0. Furthermore, it reveals the transition of manufacturing paradigm from I3.0 complex, centralized, monolithic architecture and physical Supply Chain to a modular, distributed, collaborative, and product-service-oriented I4.0 architecture.

Introduction

It is a consensual understanding that Manufacturing Automation Systems (MAS) are under a disrupting paradigm shift. This technological paradigm shift is considered the fourth industrial revolution and coined with the term Industrie 4.0 (Kagermann, Helbig, Hellinger, & Wahlster, 2013) in Germany. The main technology leading this change is the Internet of Things (IoT), enabling pervasive use of embedded computing and standardization of digital network communication, and the inclusion of Cyber-Physical Systems (CPS). This initiative envisions a fully connected collaborative manufacturing environment with automated data collection and processing. The same idea was shared by other countries, such as the United States, and denoted by Industrial Internet (Evans & Annunziata, 2012), or in China, under the term Intelligent Manufacturing (Zhou, 2018). Many other countries also envision the future scenario, depicting potential economic and social changes and opportunities (Ferreira and Serpa, 2018, Pathfinder Consortium, 2014) to innovate production. I4.0 is in the hype, and many researchers made attempts to define it (Hermann et al., 2015, Drath and Horch, 2014, Geissbauer et al., 2014 apud Plattform Industrie 4.0 (Plattform Industrie 4.0), 2014; Anderl, 2014, Schulz, 2015), but still, there is not a consensual understanding about a composed technology toward I4.0. Therefore, it does not exist a consensus on how to make a transition from the current stage to this new production model. Furthermore, Bidet-Mayer and Ciet (2016) states that there are different approaches to I4.0 outside Germany not universally accepted, and with slightly different definitions. German telecommunications association BITKOM reveals that there are more than 100 different definitions of I4.0 (Bidet-Mayer & Ciet, 2016). Piccarozzi, Aquilani, and Gatti (2018) also fail to identify a consensual definition of I4.0 and cites several different attempts to characterize and formulate definitions of I4.0 from a management perspective. The lack of consensus covers definitions and enabling technologies to support the transition I3.0-I4.0 (Xu, Xu, & Li, 2018).

The transition phase between the legacy I3.0 – concerned with the integrated production controlled by computers – to the I4.0 is embedded by great expectations, both from industry and from the academy. On the other hand, the full understanding of this transition is crucial to the evolution of concepts toward a full integration between society, production, and life – Society 5.0 (Ferreira and Serpa, 2018, Shiroishi et al., 2018) – as well as to the evolution of the market, which faces a demand for sustainability and service-orientation (Nof & Silva, 2018). Fig. 1 depicts our proposal to structure the transition from I3.0 to I4.0.

Fig. 1 divides the transition from I3.0 to I4.0 in two parallel axes: in the bottom, a basis supported by Computer Integrated Manufacturing (CIM), integrated with the supply chain. On top, the target I4.0 with the proper composition of new features. Each of these axis embrace activities that go from the foundation to vertical integration: from manufacturing plant to product marketing and design; and horizontal integration, from the manufacturing environment to supply chain and to market. Notice that in each parallel axis, different technological concepts are associated, as well as different technologies – which eventually have a match or evolutionary counterpart in the other axis. For example, the first evolution from CIM and manufacturing cell goes vertically to the concept of CPS and Service-Oriented Architecture (SOA) (Jammes and Smit, 2005, Nof and Silva, 2018, Zuehlke, 2010). In horizontal integration, concepts match a formal and distributed connection with Supply Chain sources and different market niches. In this construct, IIoT (Industrial Internet of Things) is a subset of IoT and is shown separated from IoT, once only IIoT is present in the Manufacturing infrastructure. However, other non-industrial IoTs – such as cellphones and other smart products – may also be part of I4.0 Manufacturing Infrastructure.

Efficiency, Flexibility, and Agility are the goals for the whole process as its benefits are claimed in the literature to fit in one or more of these three categories. For instance, Kagermann et al. (2013) list eight potential sub-goals for I4.0 platform which matches these main goals:

• Meeting individual customer requirements (Flexibility and Agility).

• Flexibility (Flexibility).

• Optimized decision-making (Efficiency).

• Resource productivity and efficiency (Efficiency and Agility).

• Creating value opportunities through new services (Flexibility).

• Responding to demographic change in the workplace (Agility and Flexibility).

• Work-Life-Balance (Flexibility and Efficiency).

• A high-wage economy that is still competitive (Efficiency).

We will return to the structure Fig. 1 later, but it is important to highlight the loose coupling between concepts in different axis, to suggest that a smooth transition should give some attention to these couplings, looking for a strategy to achieve concepts such as Big Data (Efficiency), Evolvable Production Systems (EPS) (Flexibility) and Virtualization (Agility).

Therefore, the structure in Fig. 1 is a guide toward a strategy of transition, which should be adjusted to a production system according to its position in the market and to its technological level and insertion in the global market. It is not a “guideline”, as will be shown. In the next section, we will present methods and data used to support the evolutionary analysis extracted from bibliometric data as well as expectations extracted from the market.