Abstract
Purpose: The purpose of this paper is to synthesize Industry 4.0’s on knowledge management process and practices, and to explore the improvements that will arise from it. It also provides an idea of how to use approaches for enhancing the knowledge management process in Industry 4.0. The main objective is to highlight the role of the technologies that support Industry 4.0 in facilitating the knowledge management process.
Design/methodology/approach: The aforementioned dynamic suggests that a thorough analysis of the existing literature on the topics related to the subject is needed to better understand what Industry 4.0 is for and how it can support the knowledge management system. Despite the analysis of the literature on Industry 4.0, this study develops an approach that presents the importance of this new industrial system, especially its technologies in the knowledge management process. It outlines the way in which Industry 4.0’s components are useful to overcome several stages of the process and improve the performance of the organization.
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Findings: Findings reveal that Industry 4.0 is an important factor in the growth of various organizational management processes. Industry 4.0’ components such as the Internet of Things (IoT), big data, cyber-physical systems (CPS), and Cloud computing play an important role in supporting the knowledge management process that contributes to the organization’s performance.
Research limitations/implications: How to manage the knowledge process is one of the important questions that pursue organizations to investigate possible ways. In this context, this paper deals with the relationship between Industry 4.0’s technologies and knowledge management. It provides an approach that covers the key technologies of this industry that can support managing knowledge in the organization. It contributes to the literature of Industry 4.0 and knowledge management by examining the role of its technologies in acquiring, creating, storing, sharing and protecting knowledge. Despite opening a new perspective for academics, this study also has limitations. As the main contribution is conceptual, further empirical studies are needed to analyze the impact of Industry 4.0 on knowledge management.
Originality/value: Business models are evolving along with the growing globalization and technological advancement, thus increasing the need for creative knowledge management. This paper highlights the current trend in knowledge management related to industry 4.0 and its technology. It focuses on the effect of this Industry and, subsequently connected technologies in the knowledge management process. This paper is one of the pioneering studies which examined the role of industry 4.0 in the process of knowledge management. It discusses the connection between industry 4.0’ technologies, mainly IoT, big data, cloud, and CPS and the knowledge management process. Therefore, this study contributed to the literature by providing valuable insights into knowledge management through Industry 4.0.
KEYWORDS: Industry 4.0, Knowledge management, IoT, big data, Technology.
Introduction
Nowadays, organizational management is widely linked to the innovative application of management techniques in knowledge processes and the organizational capacity to adapt to changing environments based on the rapid development of new technologies. Companies are facing complex structural changes and are increasingly based on knowledge which is a key driver of innovation. It is, therefore, necessary to implement strategies to support the knowledge management strategies. In addition, it is shown that the implementation of knowledge management strategies has a direct positive impact on the performance of the organization.
Therefore, the ability to manage information in today’s business landscape is becoming increasingly important. Knowledge management strategies can often be focused on new technologies and companies can adopt methods and use technologies to support knowledge management strategy and ensure dynamic and timely use of knowledge. Companies have to face challenges and embrace the opportunities offered by the new emerging technologies in order to remain competitive.
In the possible use of knowledge management, there is an apparent need for suitable and practical solutions to support innovation (Roblek et al, 2016). This is particularly evident in the fourth industrial revolution, known as Industry 4.0, which reflects the new manufacturing paradigm based on technology and which is heavily dependent on knowledge. In Industry 4.0, knowledge management that is strategically focused could prove to be a critical component in securing relevant knowledge to help foster innovation.
Industry 4.0 and the related digital transformation refer to the advent of new digital technologies, such as the Internet of Things (IoT), artificial intelligence, cloud computing, and Big Data, and involve a profound transformation of processes and activities, skills and business models. The emergence of these technologies generates a multiplicity of challenges for companies and particularly upsets the organizational ecosystem by the development of robotics and the arrival of smart and virtual factories.
In this context, we have seen an exponential increase in research developing methods and tools to address this challenge in the recent decade but still, the exchange of knowledge is crucial for practical technological application and implementation in the knowledge management field. To examine this issue, the present paper focuses on what kinds of creativity characteristics and related future innovation trajectories are important in forming knowledge management formal strategies and tools. Therefore, this paper aims to identify the technology flows and key elements of a successful technology roadmap that matches knowledge management formal strategies. Its contribution is, therefore, mainly conceptual.
This paper has been achieved as follows. Before discussing how Industry 4.0 can support the Knowledge management system, a brief overview of Industry 4.0 and the pillar of technological advancement that support it are presented in section 2. This section covers also a scientific contribution analysis related to Industry 4.0 with the focus on the technologies that support this new industrial system. Section 3 describes the process of managing knowledge and highlights its different stages. Section 4 outlines the adopted research approach and details the role of the components of Industry 4.0 in supporting the different stages of the knowledge management process. Section 5 discusses presents a brief discussion about the relationship between the different technologies of Industry 4.0 and how they fit together to improve the process of knowledge management in the organization. Section 6 summarizes the conclusions of the study and proposals for future research.
Industry 4.0: Theoretical framework
Industry 4.0 in literature
In recent years, the term of Industry 4.0 has attracted very high-level attention. Google trends (see Figure 1) reveal that up to 2013 there was little searching interest even the concept introduced in 2011. There has been an increase in search interest in the period between 2016 and 2019, which has continued to increase.
By analyzing the number of the scientific publications indexed in Scopus database from 2013 to 2019, and containing the following keywords: Industry 4.0, 4th industrial revolution, Smart factory, Smart Industry, and Manufacturing 4.0; we can notice that more than 6000 publications were made as shown in the following Figure.
Figure 2 reflects the interest of the Industry 4.0 among the scientific community and shows that the number of scientific contributions of Industry 4.0 has been increasing since 2013. In addition, the results of this analysis show also that the publications were maximal in the field of Engineering (54.20%), Computer Sciences (37.85%), Business, Management and Accounting (13.25%), and Decision Sciences (11.73%). It is worth noting that Industry 4.0 has attracted less attention in other research areas such as Social Sciences, Mathematics, and Materials Science with 3.61%, 9.06%, and 8.13% respectively.
Despite its popularity, especially during these last years, a clear and commonly accepted definition of the term Industry 4.0 still seems difficult to pin down (Muller, et al, 2018). Many studies have tried to develop different definitions of what constitutes Industry 4.0 (Lu et al, 2016; Muhuri et al, 2019). Industry 4.0, which presents the next level of manufacturing, does not concern only industrial. It concerns also all the change using digital integration and intelligent engineering, where machines redefine themselves to more communicate and perform different operations.
Based on digital transformation, Industry 4.0 and the smart factory have served as the basis for many countries’ programs. The appendix illustrates the different visions of some countries that have embraced the Industry 4.0 in very ambitious programs. The Appendix indicates that most of the European countries’ program is closer to the German’s Industry 4.0 strategy. Similarly, other countries have also put forward the corresponding Industry 4.0 program.
Globally, Industry 4.0 can be viewed as the utilization of cyber-physical systems in the systems of industrial production (Flynn, 2017). It affects manufacturing because of its emphasis on making a smart environment. In this context, this new industrial system needs advanced manufacturing technologies including the Internet of things (IoT), cloud, big data, cyber-physical systems (CPS), etc. We have paid specific attention to these components, and we selected some relevant technology in the following section.
Industry 4.0’s technology
Industry 4.0 is related to (i) the technical perspective of CPS coordinated into manufacturing activities, and (ii) the IoT tools into the industrial process. Therefore, humans, machines, and resources are vertically connected, while organizations are connected horizontally over the value chain (Waibel et al. 2017). It aims to provide employees with more accurate and relevant information, empower them with smart technology, and give them greater responsibility and flexibility with a higher perspective on workplace autonomy while delegating repetitive and low-level decision-making to machines and systems.
In this context, different advent technologies that are related to the main features of Industry 4.0 (Cheng et al, 2016) mainly: (i) Interconnectivity, (ii) data, (iii) integration, and (iv) innovation, are used to perform Industry 4.0 elements.
It should be noticed that it is not an exhaustive list, but it serves as a guide to select technologies that are of particular importance to Industry 4.0. These technology groups bring together a variety of technologies, approaches, methods, and techniques, as shown in Table 1. Their judicious combination enables the implementation of the company’s digital strategy.
Table 1 – Industry 4.0’s technology groups and support resources
Technology
For Industry 4.0
Resources involved
IoT and connected object (Molano et al, 2018)
Connecting a huge variety of digital and physical resources.
Decentralizing real-time decision-making
RFID, Wireless Sensor Networks, etc.
Cloud computing (Kagermann et al, 2013)
Facilitate data-sharing systems.
Deploy the functionality related to production, process, monitoring, and control
Infrastructure as a service (IaaS), Software as a Service (SaaS), Platform as a Service (PaaS).
Cyber-physical systems (Kagermann et al, 2013)
Integrating sensors, software and communications components to monitor and act in real-time on the physical world.
Smart and connected communities, physical components, etc.
Big data and analytics (Sedkaoui, 2018)
Driving and supporting real-time the decision process based on the analysis of the available data generated from different sources.
High-performance computing, High-Performance Computing Cluster, Hadoop-YARN, etc.
Industrial integration and enterprise architecture (Pereira and Romero, 2017)
Digital information integration and interoperability of engineering across the value chain service-oriented architecture, Business process management, etc.
Artificial intelligence
Support the management of the production process machinery.
Neural networks, machine learning, Bayesian networks, etc.
Simulation
Simulate all production operations machines, products, and humans
Cybersecurity
Reliable and proven communication protocols can be used to control access to the machine control systems.
VPN, P2P, RFID, etc.
The implementation of elements from the range of alternatives illustrated in Table 1 may depend on the case, redefine the way of monitoring, controlling, optimizing or even making Industry 4.0 products, processes or services autonomous.
Today’s business environment is moving towards Industry 4.0, marked by the use of cyber-physical systems, smart factories and developments in services. The term Industry 4.0 suggests that the effort is focused on improving manufacturing processes. However, the increase in the presence of sensors and real-time exchanges also opens up new opportunities in the definition of communicating products. Indeed, the contributions of digital technology can be broken down along the two following axes:
- The process, Industry 4.0 promises a transformation of production methods, going from mass production to individualized production. Processes are more agile and reconfigurable to adjust to customer needs and thus maximize value creation. Production decisions are adapted in real-time with the appearance of autonomous machines and communication between machines and cyber-physical systems.
- Connected objects allow real-time data collection. This data can be analyzed in real-time and allow the system to adapt to its environment autonomously, or be used later for the development of new products or services. The availability of data and the possibilities of analysis bring opportunities for the development of new services (Sedkaoui, 2018).
Knowledge management: process and practices
The success of an organization depends widely on the quality of knowledge applied to its business processes. Therefore, the knowledge management process, as a part of the business processes, is essential for effective knowledge management. This process requires that personal knowledge be transformed into corporate knowledge that can be widely shared and applied appropriately across an organization.
The literature identifies a multitude of knowledge management processes and divides it into several stages:
- Creation, Storage/Retrieval, Transfer, Application (Alavi and Leidner, 2001)
- Discovery, Capture, Sharing, Application (Beccara-Fernandez et al, 2004)
- Acquisition, Conversion, Application, Protection (Mills et al, 2011)
- Acquisition, Sharing, Application, Storage (Lee et al, 2013)
It should be mentioned that there is no consensus to illustrate the classification and implementation of these processes. However, all these knowledge management processes contribute to the performance of knowledge management practices in the organization.
In this study, the authors explored the following knowledge management process: (i) acquisition, (ii) creation, (iii) storage, (iv) sharing, and (v) protection, in order to examine the impact of Industry 4.0 or more specifically its components. Where all these stages (see Table 2) contribute to the performance of knowledge management practices.
An organization needs to continually generate new knowledge, promote its sharing, and use knowledge in order to achieve a competitive advantage.
Table 2 – Knowledge management process
Stage
Definition
Acquisition
Defining applicable external knowledge, turning it into a form suitable for assimilation or internalization in the sense of an organization that can be applied to the creation of knowledge
Creation
Generating new knowledge by applying the knowledge acquired from outside and within the organization appropriately.
Storage
Collecting and recording of organizational knowledge available and knowledge acquired for future reference
Sharing
Mechanisms that allow safe transfer of knowledge within the organization.
Protection
Mechanisms of protecting an organization’s knowledge from illegal or inappropriate use.
The process of knowledge management allows an organization to acquire, store, use and protect knowledge to facilitate problem-solving, creating creative insights, and supporting the decision-making process.
The analysis of literature indicates generally accepted distinction in knowledge management between the two following strategic focus areas (Choi et al, 2008):
- Explicit oriented strategy: or the use of information and communication technologies (ICT) to manage knowledge across the organization.
- Tacit oriented strategy: Knowledge management is allowed using people-focused tools and techniques
A clear link can be seen in the literature between the strategic orientation and the form of shared knowledge. The first strategy is related to explicit knowledge that is data-driven, codifiable, and not connected to individuals. While the second strategy is linked to tacit knowledge, which refers to the person’s knowledge and cannot be codifiable. In practice, two main types of knowledge branch off entire strategic focuses.
The use of ICTs increases the organization's effectiveness and improves collaboration. In this context, the emphasis in the knowledge management process is on codification, storage, structured knowledge sharing, and internal organizational links (Sedkaoui, 2018). The improvement of collaboration can support innovation. Its main purpose is to share knowledge through informal connections that can be created, for example, through social networks or directly at meetings.
If we examine more deeply into modern business practices, we can notice that new organization’ trends show that the internet of things and connected objects, big data analytics, smart systems, etc. are increasingly being integrated into knowledge management processes.
The knowledge management process becomes more flexible and smart, thanks to the development of new technology (North et al, 2018). With the advent of IoT and the development of several devices, organizations can now gain an insight that has never been possible before. This technology facilitates the way in which knowledge is acquiring, creating, sharing, storing and protecting. It stimulated the development of integrated software platforms to optimize knowledge management strategies.
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