5,537 research outputs found
Innovation ecosystems for industry 4.0 : a collaborative perspective for the provision of digital technologies and platforms
Industry 4.0 considers complex interrelated IoT-based technologies for the provision of digital solutions. This complexity demands a vast set of capabilities that are hard to be found in a single technology provider, especially in small and medium-sized enterprises (SMEs). Innovation ecosystems allow SMEs to integrate resources and cocreate Industry 4.0 solutions. This thesis investigates the role of collaboration for the development of technologies and solutions in the Industry 4.0 context. To this end, this thesis was organized into three papers, which objectives are: (i) to verify if collaboration through inbound Open Innovation activities with different actors in the supply chain positively moderates the relationship between Industry 4.0 technologies and their expected benefits; (ii) to identify how the characteristics of an innovation ecosystem focused on solutions for Industry 4.0 change at each evolutionary lifecycle stage using elements from social exchange theory; and (iii) to identify which technologies can be configured as platforms through boundary-spanning activities and how they operate collaboratively to develop solutions for Industry 4.0. As a result, this thesis proposes a model that explains the role of collaboration at different levels (supply chains, ecosystems, and platforms) for the development of solutions in the Industry 4.0 context. This research approach combines both qualitative (i.e., focus group, interviews, and case studies) and quantitative (i.e., survey research with multivariate data analysis) aspects. The main results obtained are: (i) we show how collaboration with different actors in the supply chain through Open Innovation strategy has both positive and negative impacts on three strategies associated with product development (cost reduction, focalization, and innovation); (ii) we define the main characteristics of innovation ecosystems focused on the provision of Industry 4.0 solutions, considering an evolutionary lifecycles perspective and a Social Exchange view (iii) we define which are the different technology platforms of the Industry 4.0 context at different operation levels using Boundary-Spanning view. As remarking conclusions, from an academic perspective, these results help to understand how collaboration for the development of new solutions in Industry 4.0 can be analyzed under different perspectives (Open Innovation, Social Exchange Theory, and Boundary-Spanning) and in different contexts of integration (supply chains, ecosystems, and platforms). From a practical perspective, the results help to enlighten a trending business topic by showing how the collaboration among technology providers for Industry 4.0 should be fostered and developed
Cyber-physical systems in manufacturing: Future trends and research priorities
In the last decades, the manufacturing ecosystem witnessed an unprecedented evolution of disruptive technologies forging new opportunities for manufacturing companies to cope the ever-growing market pressure. Moreover, the race to create value for the customers has been hindered by several issues that both small and large companies have been facing, such as shorter product life cycles, rapid time-to-market, product complexity, cost pressure, increased international competition, etc. In this scenario, ICT represent a crucial enabler for preserving competitiveness and fostering industry innovation. In particular, among these technologies, Cyber-Physical Systems (CPS) is growing an ever-high interest of industry stakeholders, researchers, practitioners and policy makers as they are considered the key technology that will transform manufacturing industry to the next generation. Indeed, CPS is a breakthrough research area for ICT in manufacturing and represents the cornerstone for achieving the EU2020 "smart everywhere" vision. At this early development phase, there is the urgent need to set the ground for future research streams, create a common understanding and consensus, define viable migration paths and support standards definition. This paper describes the identified research challenges and the future trends that will drive to the adoption of CPS in manufacturing. The main evidences on researches challenges expected for CPS in manufacturing are outlined by the authors that have been involved in the sCorPiuS project 'European Roadmap for Cyber- Physical Systems in Manufacturing', promoted by the European Commission to define a roadmap for future CPS in manufacturing adoption research agenda
Eco‐Holonic 4.0 Circular Business Model to Conceptualize Sustainable Value Chain Towards Digital Transition
The purpose of this paper is to conceptualize a circular business model based on an Eco-Holonic Architecture, through the integration of circular economy and holonic principles. A conceptual model is developed to manage the complexity of integrating circular economy principles, digital transformation, and tools and frameworks for sustainability into business models. The proposed architecture is multilevel and multiscale in order to achieve the instantiation of the sustainable value chain in any territory. The architecture promotes the incorporation of circular economy and holonic principles into new circular business models. This integrated perspective of business model can support the design and upgrade of the manufacturing companies in their respective industrial sectors. The conceptual model proposed is based on activity theory that considers the interactions between technical and social systems and allows the mitigation of the metabolic rift that exists between natural and social metabolism. This study contributes to the existing literature on circular economy, circular business models and activity theory by considering holonic paradigm concerns, which have not been explored yet. This research also offers a unique holonic architecture of circular business model by considering different levels, relationships, dynamism and contextualization (territory) aspects
Industry 4.0 and the future of manufacturing. Theoretical base and empirical analyses
A new industrial revolution \u2013 also called \u201cIndustry 4.0\u201d \u2013 is unfolding fueled by the introduction of broadly interconnected digital technologies, including the Internet of Things, cloud computing, artificial intelligence and additive manufacturing. Many industries are witnessing the entrance of new players integrating new technologies into disruptive business models; incumbents are also urged to rethink how they operate against trends that are expected to further accelerate in the current pandemic situation.
The overarching aim of the research presented in this doctoral dissertation is to investigate to what extent Industry 4.0 represents a fundamental challenge to existing paradigms and requires researchers to modify their theoretical frameworks to approach emerging issues. With this in mind, each chapter can be seen as a step forward in journey whereby some core issues come progressively into focus. The starting point is a conceptual work analyzing the phenomenon \u2013 \u201cIndustry 4.0\u201d and similar labels \u2013 and its underlying technological and non-technological components. As a second step \u2013 under the assumption of Industry 4.0 having paradigmatic properties comparable to previous industrial revolutions \u2013 potential new configurations of manufacturing value chains are investigated. Through a future-oriented expert study, eight scenarios are conceived identifying critical drivers to value chain configurations. Finally, one of these critical drivers \u2013 data sharing in inter-organizational relationships \uac\u2013 is investigated through the development of a multiple case study analysis in the automotive sector.
The contribution of this dissertation to the academic debate is at least twofold. On the one hand, the research highlights the cornerstones of the phenomenon to make sense of its overarching features and building elements. This contributes to lay solid theoretical foundations needed to advance the understanding in the field. On the other hand, my empirical investigations suggest that several barriers counterbalance the technological drivers for change, posing significant questions as for when and how the future of manufacturing will materialize. Overall, an approach focused on understanding how technologies influence the assumptions behind the current reasoning might lead at a synthesis between \u201cold\u201d and \u201cnew\u201d elements in the Industry 4.0 phenomenon
Digitising the Industry Internet of Things Connecting the Physical, Digital and VirtualWorlds
This book provides an overview of the current Internet of Things (IoT) landscape, ranging from the research, innovation and development priorities to enabling technologies in a global context. A successful deployment of IoT technologies requires integration on all layers, be it cognitive and semantic aspects, middleware components, services, edge devices/machines and infrastructures. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC - Internet of Things European Research Cluster from research to technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster and the IoT European Platform Initiative (IoT-EPI) and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in the next years. The IoT is bridging the physical world with virtual world and requires sound information processing capabilities for the "digital shadows" of these real things. The research and innovation in nanoelectronics, semiconductor, sensors/actuators, communication, analytics technologies, cyber-physical systems, software, swarm intelligent and deep learning systems are essential for the successful deployment of IoT applications. The emergence of IoT platforms with multiple functionalities enables rapid development and lower costs by offering standardised components that can be shared across multiple solutions in many industry verticals. The IoT applications will gradually move from vertical, single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organisations and people, being one of the essential paradigms of the digital economy. Many of those applications still have to be identified and involvement of end-users including the creative sector in this innovation is crucial. The IoT applications and deployments as integrated building blocks of the new digital economy are part of the accompanying IoT policy framework to address issues of horizontal nature and common interest (i.e. privacy, end-to-end security, user acceptance, societal, ethical aspects and legal issues) for providing trusted IoT solutions in a coordinated and consolidated manner across the IoT activities and pilots. In this, context IoT ecosystems offer solutions beyond a platform and solve important technical challenges in the different verticals and across verticals. These IoT technology ecosystems are instrumental for the deployment of large pilots and can easily be connected to or build upon the core IoT solutions for different applications in order to expand the system of use and allow new and even unanticipated IoT end uses. Technical topics discussed in the book include: • Introduction• Digitising industry and IoT as key enabler in the new era of Digital Economy• IoT Strategic Research and Innovation Agenda• IoT in the digital industrial context: Digital Single Market• Integration of heterogeneous systems and bridging the virtual, digital and physical worlds• Federated IoT platforms and interoperability• Evolution from intelligent devices to connected systems of systems by adding new layers of cognitive behaviour, artificial intelligence and user interfaces.• Innovation through IoT ecosystems• Trust-based IoT end-to-end security, privacy framework• User acceptance, societal, ethical aspects and legal issues• Internet of Things Application
A journey towards Industry 4.0 : the supporting role of socio-technical systems
Companies seek to improve their competitiveness and productivity through innovation in processes, products, and equipment. This innovation can be achieved via technologies that bring greater quality, flexibility, efficiency, control, and monitoring to their production. In this sense, the concept of a more intelligent, automated, and digital industry gained interest and culminated in Industry 4.0. Many companies view this industry evolution as capable of delivering immediate improvements and lowering production costs. However, only crediting the technology with gains in productivity, quality, and flexibility has brought frustrations, complexity, and reduced production in company processes. This is due to, among other things, the way Industry 4.0 technologies are understood, implemented, communicated, and used. Literature and empirical studies have shown that companies still lack the technological, cultural, and process maturity necessaries to obtain substantial gains with Industry 4.0, especially small and medium-sized companies. Focusing on this technology implementation process, this thesis aims to investigate how the socio-technical theory can bring improvements and gains in relation to the environment in which technologies such as IoT, big data, analytics, collaborative robots, and 3D printing are implemented. For that, this thesis aims to identify how the socio-technical aspects impact the implementation of Industry 4.0 and its contribution to improving the results with its implementation. The results demonstrate that socio-technical aspects are associated with higher levels of Industry 4.0 implementation as they serve as the basis for technologies to operate in a more organized environment, with workers trained and engaged in their use and with a clear and delimited strategy. Strategic aspects are the most impacting aspects of Industry 4.0 implementation and should be considered fundamental for companies adopting its technologies. The qualitative results highlight such importance and demonstrate how companies have made such a transition both through Industry 4.0 ecosystems, as well as seeking capabilities and knowledge through suppliers, consultancies, associations, and startups. Still, the results showed the importance of collecting, storing, and having the ability to use data for continuous improvement. Well-established lean maturity and the definition of a strategic and technological roadmap that guides the technology implementation process were also essential for the company to focus on a broader context of technologies to the detriment of ad-hoc implementations. Finally, the results also showed that although aspects of strategic definition bring important gains for implementing Industry 4.0, improvements related to workers, such as engagement, qualification, and training, can also bring productivity improvements. In this way, this thesis brings theoretical and empirical gains to a field of growing interest for the industry that demands high investments, impacting not only workers but various organizational, social, and technical aspects of the company. The results discussed here provide empirical evidence of the importance of a socio-technical vision based on more organized processes, a well-defined strategy, and trained, engaged, and participative workers in the transition to Industry 4.0, in contrast to the technocentric vision generally adopted by companies.Empresas buscam melhorar sua competitividade e produtividade através de inovações em processos, produtos e equipamentos. Tais inovações podem ser feitas através de tecnologias que tragam maior qualidade, flexibilidade, eficiência, controle e monitoramento a sua produção. Nesse sentido, o conceito de uma indústria mais inteligente, automatizada e digital ganhou força e culminou no que se denomina de Indústria 4.0. Muitas empresas visualizam essa evolução da indústria como capaz de entregar melhorias imediatas e diminuir custos de produção. No entanto, creditar somente à tecnologia ganhos de produtividade, qualidade e flexibilidade tem trazido frustrações, diminuição na produção e complexidade aos processos das empresas. Isso se deve, entre outras coisas, à forma como as tecnologias da Indústria 4.0 são entendidas, implementadas, comunicadas e usadas. Estudos empíricos têm demonstrado que as empresas ainda não possuem maturidade tecnológica, cultural e de processos para obter ganhos substanciais com a Indústria 4.0. Com foco nesse processo de implementação de tecnologia, esta tese visa estudar como a abordagem sistêmica e holística proposta pela teoria socio-técnica pode trazer melhorias e ganhos em relação ao ambiente em que as tecnologias como IoT, big data, analytics, robôs colaborativos e impressão 3D são implementadas. Para isso, essa tese tem como objetivo geral identificar como os aspectos socio-técnicos impactam a implementação da Indústria 4.0 e sua contribuição para melhorar os resultados com a sua implementação. Os resultados demonstram que os aspectos socio-técnicos estão associados a níveis mais altos de Indústria 4.0 uma vez que servem de base para que as tecnologias possam operar em um ambiente preparado, com trabalhadores treinados e engajados em seu uso e com uma estratégia clara e delimitada. Os aspectos estratégicos são os que mais impactam no nível de adoção de Indústria 4.0 e são fundamentais para a adoção das tecnologias. Os resultados qualitativos ressaltam tal necessidade e demonstram como as empresas têm feito tal transição tanto através de treinamentos, parcerias com startups e organizações governamentais, assim como buscando capabilidades e conhecimento através de fornecedores, universidades e consultorias. Ainda, os resultados evidenciaram a importância de coletar, armazenaram e possuir capacidade de utilizar dados para melhorias contínuas. Maturidade lean bem estabelecida e a definição de um roadmap estratégico e tecnológico que guie o processo de implementação das tecnologias também foi demonstrado como essencial para que a empresa foque num contexto mais amplo de tecnologias em detrimento de implementações pontuais e usos ad hoc. Finalmente, os resultados também demonstraram que apesar de aspectos de definição estratégica trazerem ganhos importantes para a implementação de Indústria 4.0, melhorias relacionadas a trabalhadores, como engajamento, qualificação e treinamento também são capazes de trazer melhorias na produtividade. Dessa forma, essa tese traz ganhos teóricos para um campo crescente e de interesse da indústria e que demandam investimentos altos, impactando não somente os trabalhadores, mas diversos aspectos organizacionais, sociais e técnicos da empresa. Os resultados discutidos aqui trazem evidências empíricas da importância de uma visão socio-técnica pautada em processos mais organizados, estratégia bem definida e trabalhadores treinados, engajados e participativos na transição para a Indústria 4.0 em contraste a visão tecnocentrista geralmente adotada pelas empresas
Enabling Cyber-Physical Systems for Industry 4.0 operations: A Service Science Perspective
Based on the Internet of Things (IoT) and Smart
Technologies, manufacturing industries are witnessing the fourth
Industrial Revolution, the Industry 4.0 (I4.0), and digital
transformation is a keystone in this change. Cyber-Physical
Systems (CPS) are strategic in thoroughly digitalizing companies,
and I4.0 operations depend on CPS efficiency. Digital plants are
held by digital technologies that provide excellent tools for
improving product security and supply chain security but requires
structured information management to maintain the CPS in its
highest level of efficiency. These systems are overly complex and
hard to handle when several CPS need to be combined as in a
large factory, where several machines must work together to
achieve a common goal. This research addresses these issues, and
we propose an information management framework of industrial
CPS that, towards the industrial efficiency, affords an increase in
value for all stakeholders. The framework structures the
information through the introduction of two innovative value
co-creation concepts: (i) Fingerprint (FP-I4.0), a virtual vehicle
that can carry two types of structured information and (ii)
Cockpit4.0, an interaction entity between the various service
systems, applied from cradle-to-cradle. Validated through the
Service Science Theory, we conclude that the proposed empirical
framework may boost up CPS efficiency and, from it, I4.0
operations will be more effectiveinfo:eu-repo/semantics/publishedVersio
Building the Hyperconnected Society- Internet of Things Research and Innovation Value Chains, Ecosystems and Markets
This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade
Digitising the Industry Internet of Things Connecting the Physical, Digital and VirtualWorlds
This book provides an overview of the current Internet of Things (IoT) landscape, ranging from the research, innovation and development priorities to enabling technologies in a global context. A successful deployment of IoT technologies requires integration on all layers, be it cognitive and semantic aspects, middleware components, services, edge devices/machines and infrastructures. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC - Internet of Things European Research Cluster from research to technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster and the IoT European Platform Initiative (IoT-EPI) and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in the next years. The IoT is bridging the physical world with virtual world and requires sound information processing capabilities for the "digital shadows" of these real things. The research and innovation in nanoelectronics, semiconductor, sensors/actuators, communication, analytics technologies, cyber-physical systems, software, swarm intelligent and deep learning systems are essential for the successful deployment of IoT applications. The emergence of IoT platforms with multiple functionalities enables rapid development and lower costs by offering standardised components that can be shared across multiple solutions in many industry verticals. The IoT applications will gradually move from vertical, single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organisations and people, being one of the essential paradigms of the digital economy. Many of those applications still have to be identified and involvement of end-users including the creative sector in this innovation is crucial. The IoT applications and deployments as integrated building blocks of the new digital economy are part of the accompanying IoT policy framework to address issues of horizontal nature and common interest (i.e. privacy, end-to-end security, user acceptance, societal, ethical aspects and legal issues) for providing trusted IoT solutions in a coordinated and consolidated manner across the IoT activities and pilots. In this, context IoT ecosystems offer solutions beyond a platform and solve important technical challenges in the different verticals and across verticals. These IoT technology ecosystems are instrumental for the deployment of large pilots and can easily be connected to or build upon the core IoT solutions for different applications in order to expand the system of use and allow new and even unanticipated IoT end uses. Technical topics discussed in the book include: • Introduction• Digitising industry and IoT as key enabler in the new era of Digital Economy• IoT Strategic Research and Innovation Agenda• IoT in the digital industrial context: Digital Single Market• Integration of heterogeneous systems and bridging the virtual, digital and physical worlds• Federated IoT platforms and interoperability• Evolution from intelligent devices to connected systems of systems by adding new layers of cognitive behaviour, artificial intelligence and user interfaces.• Innovation through IoT ecosystems• Trust-based IoT end-to-end security, privacy framework• User acceptance, societal, ethical aspects and legal issues• Internet of Things Application
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
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