Industry 4.0 paradigm: The viewpoint of the small and medium enterprises

International audienceThe pervasive diffusion of Information and Communication technologies (ICT) and automation technologies are the prerequisite for the preconized fourth industrial revolution: the Industry 4.0 (I4.0). Despite the economical efforts of several governments all over the world, still there are few companies, especially small and medium enterprises (SMEs), that adopt or intend to adopt in the near future I4.0 solutions. This work focus on key issues for implementing the I4.0 solutions in SMEs by using a specific case example as a test bench of an Italian small manufacturing company. Requirements and constraints derived from the field experience are generalised to provide a clear view of the profound potentialities and difficulties of the first industrial revolution announced instead of being historically recognised. A preliminary classification is then provided in view to start conceiving a library of Industry 4.0 formal patterns to identify the maturity of a SME for deploying Industry 4.0 concepts and technologies

Cyber-physical systems in food production chain

The article reviews the state-of-the-science in the field of cyber-physical systems (CPSs). CPSs are intelligent systems that include physical, biological and computational components using engineering networks. CPSs are able to integrate into production processes, improve the exchange of information between industrial equipment, qualitatively transform production chains, and effectively manage business and customers. This is possible due to the ability of CPSs to manage ongoing processes through automatic monitoring and controlling the entire production process and adjusting the production to meet customer preferences. A comprehensive review identified key technology trends underlying CPSs. These are artificial intelligence, machine learning, big data analytics, augmented reality, Internet of things, quantum computing, fog computing, 3D printing, modeling and simulators, automatic object identifiers (RFID tags). CPSs will help to improve the control and traceability of production operations: they can collect information about raw materials, temperature and technological conditions, the degree of food product readiness, thereby increasing the quality of food products. Based on the results, terms and definitions, and potential application of cyber-physical systems in general and their application in food systems in particular were identified and discussed with an emphasis on food production (including meat products).The article reviews the state-of-the-science in the field of cyber-physical systems (CPSs). CPSs are intelligent systems that include physical, biological and computational components using engineering networks. CPSs are able to integrate into production processes, improve the exchange of information between industrial equipment, qualitatively transform production chains, and effectively manage business and customers. This is possible due to the ability of CPSs to manage ongoing processes through automatic monitoring and controlling the entire production process and adjusting the production to meet customer preferences. A comprehensive review identified key technology trends underlying CPSs. These are artificial intelligence, machine learning, big data analytics, augmented reality, Internet of things, quantum computing, fog computing, 3D printing, modeling and simulators, automatic object identifiers (RFID tags). CPSs will help to improve the control and traceability of production operations: they can collect information about raw materials, temperature and technological conditions, the degree of food product readiness, thereby increasing the quality of food products. Based on the results, terms and definitions, and potential application of cyber-physical systems in general and their application in food systems in particular were identified and discussed with an emphasis on food production (including meat products)

Patenting in 4IR technologies and firm performance

We investigate whether firm performance is related to the accumulated stock of technological knowledge associated with the Fourth Industrial Revolution (4IR) and, if so, whether the firm’s history in 4IR technology development affects such a relationship. We exploit a rich longitudinal matched patent-firm data set on the population of large firms that filed 4IR patents at the European Patent Office (EPO) between 2009 and 2014, while reconstructing their patent stocks from 1985 onward. To identify 4IR patents, we use a novel twostep procedure proposed by EPO (2020, Patents and the Fourth Industrial Revolution: The Global Technology Trends Enabling the Data-Driven Economy, European Patent Office), based on Cooperative Patent Classification codes and on a full-text patent search. Our results show a positive and significant relationship between firms’ stocks of 4IR patents and labor and total factor productivity. We also find that firms with a long history in 4IR patent filings benefit more from the development of 4IR technological capabilities than later applicants. Conversely, we find that firm profitability is not significantly related to the stock of 4IR patents, which suggests that the returns from 4IR technological developments may be slow to be cashed in. Finally, we find that the positive relationship with productivity is stronger for 4IR-related wireless technology and for artificial intelligence, cognitive computing, and big data analytics

Enterprise platform systems management security threats and mitigation techniques

Developers and technologists of enterprise systems such as servers, storage and networking products must constantly anticipate new cybersecurity threats and evolving security requirements. These requirements are typically sourced from marketing, customer expectations, manufacturing and evolving government standards. Much ongoing major research focus has been on securing the main enterprise system purpose functionality, operating system, network and storage. There appears, however, to be far less research and a growing number of reports of vulnerabilities in the area of enterprise systems management hardware and software subsystems. Many recent examples are within types of subsystems such as baseboard management controllers (BMCs), which are intricate embedded subsystems, independent of the host server system functionality. A BMC is typically comprised of a specialized system-on-a-chip, RAM, non-volatile storage, and sensors, and runs an embedded LINUX Operating System. The BMC’s primary roles are always increasing in scope including managing system inventory, system operational health, thermal and power control, event logging, remote console access, provisioning, performance monitoring, software updates and failure prediction and remediation. To compromise or create a denial of service of such subsystems has an increasing impact on equipment manufacturers and large and small enterprises. This report’s primary objective is to research real-world and theoretical hardware and software cyber-attack vectors on enterprise product platforms, inclusive of BMCs, BIOS and other embedded systems within such products. For each presented attack vector, best practices and suggestions for effective avoidance and mitigation are explored. Domains of particular interest are physical access security, hardware manipulation and secure boot protections against software image manipulation, BIOS recovery and secure field debug techniques.Electrical and Computer Engineerin

The ecological system of innovation: A new architectural framework for a functional evidence-based platform for science and innovation policy

Models on innovation, for the most part, do not include a comprehensive and end-to-end view. Most innovation policy attention seems to be focused on the capacity to innovate and on input factors such as R&D investment, scientific institutions, human resources and capital. Such inputs frequently serve as proxies for innovativeness and are correlated with intermediate outputs such as patent counts and outcomes such as GDP per capita. While this kind of analysis is generally indicative of innovative behaviour, it is less useful in terms of discriminating causality and what drives successful strategy or public policy interventions. This situation has led to the developing of new frameworks for the innovation system led by National Science and Technology Policy Centres across the globe. These new models of innovation are variously referred to as the National Innovation Ecosystem. There is, however, a fundamental question that needs to be answered: what elements should an innovation policy include, and how should such policies be implemented? This paper attempts to answer this question.Innovation; Delphi Method; Balanced Scorecard; Quadruple Helix Theory; Analytic Hierarchy Process; Ecological System of Innovation, Framework, Systems Dynamics

A Systematic Mapping Study on Modeling for Industry 4.0

Industry 4.0 is a vision of interconnected manufacturing in which smart, interconnected production systems optimize the complete value-added chain to reduce cost and time-to-market. At the core of Industry 4.0 is the smart factory of the future, whose successful deployment requires solving challenges from many domains. Model-based systems engineering (MBSE) is a key enabler for such complex systems of systems as can be seen by the increased number of related publications in key conferences and journals. This paper aims to characterize the state of the art of MBSE for the smart factory hrough a systematic mapping study on this topic. Adopting a detailed search strategy, 1466 papers were initially identified. Of these, 222 papers were selected and categorized using a particular classification scheme. Hence we present the concerns addressed by modeling community for Industry 4.0, how these are investigated, where these are published, and by whom. The resulting research landscape can help to understand, guide, and compare research in this field. In particular, this paper identifies the Industry 4.0 challenges addressed by the modeling community, but also the challenges that seems to be less investigated.Le concept d’Industrie 4.0 correspond à une nouvelle façon d’organiser les moyens de production : l’objectif est la mise en place d’usines dites « intelligentes » (« smart factories ») capables d’une plus grande adaptabilité dans la production et d’une allocation plus efficace des ressources, ouvrant ainsi la voie à une nouvelle révolution industrielle. Ses bases technologiques sont l'Internet des objets et les systèmes cyber-physiques. L'ingénierie systèmes dirigée par les modèles (MBSE Model based System Engineering) est une technologie essentielle pour de tel systèmes complexes en témoigne l'augmentation du nombre de publications dans les conférences et les revues clés du domaine. Cet article vise à caractériser l'état de l'art du MBSE pour l'Industrie 4.0 grâce à une étude sur la cartographie systématique du domaine. En adoptant une stratégie de recherche détaillée reproductible, 1466 documents ont été initialement identifiés. De ce nombre, 222 documents ont été sélectionnés et classés selon un schéma de classification particulier. Par cette étude, nous présentons les préoccupations abordées par la communauté de modélisation pour l'Industrie 4.0, comment elles sont étudiées, où celles-ci sont publiées et par qui. Le paysage de recherche qui en résulte peut aider à comprendre, guider et comparer la recherche dans ce domaine. En particulier, ce document identifie les défis spécifiques de notre communauté scientifique, mais aussi les défis qui semblent être moins étudiés

Driving Manufacturing Systems for the Fourth Industrial Revolution

It has been a long way since the aroused of the Industry 4.0 and the companies' reality is not already align with this new concept. Industry 4.0 is ongoing slowly as it was expected that its maturity level should be higher. The companies´ managers should have a different approach to the adoption of the industry 4.0 enabling technologies on their manufacturing systems to create smart nets along all production process with the connection of elements on the manu-facturing system such as machines, employees, and systems. These smart nets can control and make autonomous decisions efficiently. Moreover, in the industry 4.0 environment, companies can predict problems and failures along all production process and react sooner regarding maintenance or production changes for instance. The industry 4.0 environment is a challenging area because changes the relation between humans and machines. In this way, the scope of this thesis is to contribute to companies adopting the industry 4.0 enabling technologies in their manufacturing systems to improve their competitiveness to face the incoming future. For this purpose, this thesis integrates a research line oriented to i) the understanding of the industry 4.0 concepts, and its enabling technologies to perform the vision of the smart factory, ii) the analysis of the industry 4.0 maturity level on a regional industrial sector and to understand how companies are facing the digital transformation challenges and its barriers, iii) to analyze in deep the industry 4.0 adoption in a company and understand how this company can reach higher maturity levels, and iv) the development of strategic scenarios to help companies on the digital transition, proposing risk mitigations plans and a methodology to develop stra-tegic scenarios. This thesis highlights several barriers to industry 4.0 adoption and also brings new ones to academic and practitioner discussion. The companies' perception related to these barriers Is also discussed in this thesis. The findings of this thesis are of significant interest to companies and managers as they can position themselves along this research line and take advantage of it using all phases of this thesis to perform a better knowledge of this industrial revolution, how to perform better industry 4.0 maturity levels and they can position themselves in the proposed strategic scenarios to take the necessary actions to better face this industrial revolution. In this way, it is proposed this research line for companies to accelerate their digital transformation.Já existe um longo percurso desde o aparecimento da indústria 4.0 e a realidade das empresas ainda não está alinhada com este novo conceito. A indústria 4.0 está em andamento lento, pois era esperado que o seu nível de maturidade fosse maior. Os gestores das empresas devem ter uma abordagem diferente na adoção das tecnologias facilitadoras da indústria 4.0 nos seus sistemas produtivos para criar redes inteligentes ao longo de todo o processo produtivo com a conexão de elementos do sistema produtivo como máquinas, operários e sistemas. Estas redes inteligentes podem controlar e tomar decisões autónomas com eficiência. Além disso, no ambiente da indústria 4.0, as empresas podem prever problemas e falhas ao longo de todo o processo produtivo e reagir mais cedo em relação a manutenções ou mudanças de produção, por exemplo. O ambiente da indústria 4.0 é uma área desafiadora devido às mudanças na relação entre humanos e máquinas. Desta forma, o objetivo desta tese é contribuir para que as empresas adotem as tecnologias facilitadoras das indústria 4.0 nos seus sistemas produtivos por forma a melhorar sua competitividade para enfrentar o futuro que se aproxima. Para isso, esta tese integra uma linha de investigação orientada para i) a compreensão dos conceitos da indústria 4.0, e suas tecnologias facilitadores para realizar a visão da fábrica inteligente, ii) a análise do nível de maturidade da indústria 4.0 num setor industrial regional e entender como as empresas estão enfrentando os desafios da transformação digital e suas barreiras, iii) analisar a fundo a adoção da indústria 4.0 numa empresa e entender como essa empresa pode atingir níveis mais elevados de maturidade, e iv) o desenvolvimento de cenários estratégicos para ajudar as empresas na transição digital, propondo planos de mitigação de riscos e uma metodologia para desenvolver cenários estratégicos. Esta tese destaca várias barreiras à adoção da indústria 4.0 e também traz novas barreiras para a discussão acadêmica e profissional. A perceção das empresas em relação a essas barreiras também é discutida nesta tese. As descobertas nesta tese são de grande interesse para empresas e gestores, pois podem-se posicionar ao longo desta linha de investigação e aproveitá-la utilizando todas as fases desta tese para obter um melhor conhecimento desta revolução industrial, como obter melhores níveis de maturidade da indústria 4.0 e possam posicionar-se nos cenários estratégicos propostos por forma a tomar as ações necessárias para melhorar o envolvimento nesta revolução industrial. Desta forma, propõe-se esta linha de investigação para que as empresas acelerem a sua transformação digital