2,204 research outputs found

    A B2B Team Formation Microservice for Collaborative Manufacturing in Industry 4.0

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    Sustainable Enterprise Design 4.0: Addressing Industry 4.0 Technologies from the Perspective of Sustainability

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    Abstract The introduction of Industry 4.0 and sustainability in production is currently on everyone's mind. However, companies face difficulties to address these trends in their long-term enterprise strategy and design. Industry 4.0 promises strategic advantages for companies in many respects, but there is a lack of instruments and concepts for integrating emerging technologies in an overall enterprise system design. Similarly, the multiple perspectives regarding economic, environmental and social sustainability provide a framework for thinking about a strategy for sustainable enterprise design. Based on the three principles presented in this paper for Sustainable Enterprise Design, this article aims to present an approach to better address sustainability as well as Industry 4.0 in terms of a long-term strategic, enterprise design that is sustainable. As a result, a list of needs, functional requirements as well as possible Industry 4.0 physical solutions is proposed to achieve a long-term sustainable enterprise design. The consequence of the perspective of an enterprise as a system that can be designed provides a rigorous approach that takes advantage of Industry 4.0 technologies and the multiple perspectives and candidate physical solutions that the research community offers

    Continuous maintenance and the future – Foundations and technological challenges

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    High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

    Assessing readiness for implementation of prognostics and health management in small and medium enterprises

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    Prognostics and Health Management (PHM) refers to using robust sensing, monitoring, and control to detect, assess, and track system health degradation and failure modes, allowing for enhanced management and operational decisions. The need for PHM within a manufacturing facility has increased due to a variety of reasons, such as the increasing complexity of manufacturing equipment. A lack of readiness for digital implementations is linked to failure. The literature highlights certain barriers and enablers that can signal whether a technology implementation will be successful, such as management and maintenance employees’ desire to change the existing process, an understanding and willingness to take risks with technology, and having employees with the right competencies and motivations. This thesis identifies barriers and enablers related a successful PHM implementation and develops an assessment tool to identify a company’s readiness level as well as recommendations for increasing the probability of success

    Industry 4.0 technologies for manufacturing sustainability: A systematic review and future research directions

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    Recent developments in manufacturing processes and automation have led to the new industrial revolution termed “Industry 4.0”. Industry 4.0 can be considered as a broad domain which includes: data management, manufacturing competitiveness, production processes and efficiency. The term Industry 4.0 includes a variety of key enabling technologies i.e., cyber physical systems, Internet of Things, artificial intelligence, big data analytics and digital twins which can be considered as the major contributors to automated and digital manufacturing environments. Sustainability can be considered as the core of business strategy which is highlighted in the United Nations (UN) Sustainability 2030 agenda and includes smart manufacturing, energy efficient buildings and low-impact industrialization. Industry 4.0 technologies help to achieve sustainability in business practices. However, very limited studies reported about the extensive reviews on these two research areas. This study uses a systematic literature review approach to find out the current research progress and future research potential of Industry 4.0 technologies to achieve manufacturing sustainability. The role and impact of different Industry 4.0 technologies for manufacturing sustainability is discussed in detail. The findings of this study provide new research scopes and future research directions in different research areas of Industry 4.0 which will be valuable for industry and academia in order to achieve manufacturing sustainability with Industry 4.0 technologies

    State of Industry 5.0—Analysis and Identification of Current Research Trends

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    The term Industry 4.0, coined to be the fourth industrial revolution, refers to a higher level of automation for operational productivity and efficiency by connecting virtual and physical worlds in an industry. With Industry 4.0 being unable to address and meet increased drive of personalization, the term Industry 5.0 was coined for addressing personalized manufacturing and empowering humans in manufacturing processes. The onset of the term Industry 5.0 is observed to have various views of how it is defined and what constitutes the reconciliation between humans and machines. This serves as the motivation of this paper in identifying and analyzing the various themes and research trends of what Industry 5.0 is using text mining tools and techniques. Toward this, the abstracts of 196 published papers based on the keyword “Industry 5.0” search in IEEE, science direct and MDPI data bases were extracted. Data cleaning and preprocessing were performed for further analysis to apply text mining techniques of key terms extraction and frequency analysis. Further topic mining i.e., unsupervised machine learning method was used for exploring the data. It is observed that the terms artificial intelligence (AI), big data, supply chain, digital transformation, machine learning, internet of things (IoT), are among the most often used and among several enablers that have been identified by researchers to drive Industry 5.0. Five major themes of Industry 5.0 addressing, supply chain evaluation and optimization, enterprise innovation and digitization, smart and sustainable manufacturing, transformation driven by IoT, AI, and Big Data, and Human-machine connectivity were classified among the published literature, highlighting the research themes that can be further explored. It is observed that the theme of Industry 5.0 as a gateway towards human machine connectivity and co-existence is gaining more interest among the research community in the recent years
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