Industry 4.0 as policy-driven discourse to institutionalize innovation systems in manufacturing

Reischauer, Georg

doi:10.1016/j.techfore.2018.02.012

Cited by 305 publications

(199 citation statements)

References 39 publications

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“…This vision is of interest both for the industrial world (ex. EFFRA White paper 1 , PWC white paper 2 ) than the academic one (Reischauer, 2018)(Jardim-Goncalves et al, 2017. Indeed, next generation industry holds the promise of increased flexibility in manufacturing, along with mass customisation, better quality, improved productivity and servitisation (Zhong et al, 2017).…”

Section: Cpps-based (Discrete) Manufacturing Plant Controlmentioning

confidence: 99%

Challenges for the cyber-physical manufacturing enterprises of the future

Panetto

Iung

Ivanov

et al. 2019

Annual Reviews in Control

257

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This paper summarizes a vision of the challenges facing the so-called "Industry of the Future" as studied by the research community of the IFAC Coordinating Committee 5 on Manufacturing and Logistics Systems, which includes four Technical Committees (TC). Each TC brings its own vision and puts forward trends and issues important and relevant for future research. The analysis is performed on the enterprise-level topics with an interface too other relevant systems (e.g., supply chains). The vision developed might lead to the identification of new scientific control directions such as Industry 4.0 technology-enabled new production strategies that require highly customised supply network control, the creation of resilient enterprise to cope with risks, developments in management decision-support systems for the design, and scheduling and control of resilient and digital manufacturing networks, and collaborative control. Cobots, augmented reality and adaptable workstations are a few examples of how production and logistic systems are changing supporting the operator 4.0. Sustainable manufacturing techniques, such closed-loop supply chains, is another trend in this area. Due to increasing number of elements and systems, complex and heterogeneous enterprise systems need to be considered (e.g., for decision-making). These systems are heterogeneous and build by different stakeholders. To make use of these, an environment is needed that allows the integration of the systems forming a System-of-Systems (SoS). The changing environment requires models which adapt over time. Some of the adaptation is due to learning, other mechanisms include self-organisation by intelligent agents. In general, models and systems need to be modular and support modification and (self-)adaptation. An infrastructure is needed that supports loose coupling and evolving systems of systems. The vision of the overall contribution from the research community in manufacturing and logistics systems, over the next few years is to bring together researchers and practitioners presenting and discussing topics in modern manufacturing modelling, management and control in the emerging field of Industry 4.0-based resilient and innovative production SoS and supply networks.

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Section: Cpps-based (Discrete) Manufacturing Plant Controlmentioning

confidence: 99%

Challenges for the cyber-physical manufacturing enterprises of the future

Panetto

Iung

Ivanov

et al. 2019

Annual Reviews in Control

257

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“…According to G. Reischauer [10] "Industry 4.0" is the direction of the innovation course in industry which combines the institutionalization of the innovation system, business, science and politics". This clarification of identity adds to the understanding of the relationship between production and politics and the need for technological changes in production.…”

Section: Resultsmentioning

confidence: 99%

Digitalization as a Key Factor of Increasing Investment Attractiveness and Innovative Development of Industrial Enterprises

et al. 2019

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The relevance of the study is stipulated by the need to increase the in-vestment attractiveness of the real sector of the economy in the context of global changes associated with the new industrial revolution "Industry 4.0". In this regard, the article is aimed at identifying indicators that determine the innovative potential of industrial complex enterprises, identifying factors and criteria for the effective development of industrial enterprises based on the introduction of innovative and digital technologies and increasing the investment attractiveness of high-tech industries. The leading approach to the study of this problem is a systematic and comprehensive analysis of the reasons of technological lag of industrial enterprises and the factors restraining their effective development. As a result, the possibilities of the economy growth at the account of the tools of the industrial investment policy were proved. The materials of the article are of practical value for researchers and specialists involved in the problems of increasing the investment attractiveness and economic efficiency of industrial enterprises in conditions of economy digitalization. The materials of the article are of practical value for researchers and specialists involved in the problems of increasing the investment attractiveness and economic efficiency of industrial enterprises in conditions of digitalization of the economy.

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“…It is not possible to determine unequivocally whether this is due to geographical location. According to (Reischauer 2018), a different type of economy may be a possible result. While Germany (and for example Japan too) are prototypical examples for coordinated market economy, the UK (and for example USA) are paradigm examples for a liberal market economy.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…Due to the worldwide spread of digital technologies in the manufacturing industry, some authors (Reischauer 2018;Valenčík 2019) consider Industry 4.0 only an innovative process, a policy-driven innovation discourse in manufacturing industry that aims to institutionalize innovation systems that encompass business, academia, and politics. There are claims too, that Industry 4.0 is listed only as the first of eight core fields within this area ahead of smart services, smart data, and cloud computing (Reischauer 2018), and the authors point out, that most important proponents in the debate on Industry 4.0 are the German federal government and German federal ministries.…”

Section: Literature Review and Current State Of Knowledgementioning

confidence: 99%

Local Extremes of Selected Industry 4.0 Indicators in the European Space—Structure for Autonomous Systems

Botlíková

Botlík

2020

JRFM

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In the past, the social and economic impacts of industrial revolutions have been clearly identified. The current Fourth Industrial Revolution (Industry 4.0) is characterized by robotization, digitization, and automation. This will transform the production processes, but also the services or financial markets. Specific groups of people and activities may be replaced by new information technologies. Changes represent an extreme risk of economic instability and social change. The authors described available published sources and selected a group of indicators related to Industry 4.0. The indicators were divided into five groups and summarized by negative or positive impact. The indicators were analyzed by precedence analysis. Extremes in the geographical dislocation of factor values were found. Furthermore, spatial dependencies in the distribution of these extremes were found by calculating multiple (long) precedencies. European countries were classified according to individual groups of indicators. The results were compared with the real values of the indicators. The indicated extremes and their distribution will allow to predict changes in the behavior of the population given by changes in the socio-economic environment. The behavior of the population can be described by the behavior of autonomous systems on selected infrastructure. The paper presents research related to the creation of a multiagent model for the prediction of spatial changes in population distribution induced by Industry 4.0.

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Industry 4.0 as policy-driven discourse to institutionalize innovation systems in manufacturing

Cited by 305 publications

References 39 publications

Challenges for the cyber-physical manufacturing enterprises of the future

Challenges for the cyber-physical manufacturing enterprises of the future

Digitalization as a Key Factor of Increasing Investment Attractiveness and Innovative Development of Industrial Enterprises

Local Extremes of Selected Industry 4.0 Indicators in the European Space—Structure for Autonomous Systems

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