231 research outputs found

    Background, Systematic Review, Challenges and Outlook

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    Publisher Copyright: © 2013 IEEE. This research is supported by the Digital Manufacturing and Design Training Network (DiManD) project funded by the European Union through the Marie Skłodowska-Curie Innovative Training Networks (H2020-MSCA-ITN-2018) under grant agreement no. 814078The concept of smart manufacturing has attracted huge attention in the last years as an answer to the increasing complexity, heterogeneity, and dynamism of manufacturing ecosystems. This vision embraces the notion of autonomous and self-organized elements, capable of self-management and self-decision-making under a context-aware and intelligent infrastructure. While dealing with dynamic and uncertain environments, these solutions are also contributing to generating social impact and introducing sustainability into the industrial equation thanks to the development of task-specific resources that can be easily adapted, re-used, and shared. A lot of research under the context of self-organization in smart manufacturing has been produced in the last decade considering different methodologies and developed under different contexts. Most of these works are still in the conceptual or experimental stage and have been developed under different application scenarios. Thus, it is necessary to evaluate their design principles and potentiate their results. The objective of this paper is threefold. First, to introduce the main ideas behind self-organization in smart manufacturing. Then, through a systematic literature review, describe the current status in terms of technological and implementation details, mechanisms used, and some of the potential future research directions. Finally, the presentation of an outlook that summarizes the main results of this work and their interrelation to facilitate the development of self-organized manufacturing solutions. By providing a holistic overview of the field, we expect that this work can be used by academics and practitioners as a guide to generate awareness of possible requirements, industrial challenges, and opportunities that future self-organizing solutions can have towards a smart manufacturing transition.publishersversionpublishe

    Circular Economy and Sustainable Development: A Systematic Literature Review

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    Circular Economy put forth as an alternative to traditional linear model of extract-use-dispose along with the concept of Sustainable Development encompassing economic, environmental, and social aspects have garnered tremendous impetus among academics, practitioners and policymakers alike. The UN Sustainable Development Goals embraced by the member nations in 2015 based on the preceding Millenium Development Goals have been placed as the targets to be achieved as a part of holistic human development. In this backdrop, this paper examines the intersection of sustainability and circular economy with a focus on the three aspects of sustainable development, first the economic aspect by examining the relationship between GDP and circular economy, second the social economic aspect within the interaction of Circular Economy with Sustainable development and third the environmental-economical aspect by examining circularity and sustainability in waste management and waste valorisation. This paper achieves its objective through a systematic literature review of 1748 journal articles collected from Web of Science and SCOPUS database following PRISMA standards, network analysis of keywords, and manual review of texts. Four Research Questions are formulated: RQ1: What are the major emergent topics in Circular Economy and Sustainable Development and how are they related? RQ2: What is the relationship among CE and GDP in the CE and Sustainability? RQ3: What are the relationships between CE and Sustainability? RQ4: What are different use cases of valorisation of waste as CE tool, and can valorisation be sustainable? RQ1 is answered by presenting hotspot of research on Circular Economy and Sustainable Development through keywords occurrence network analysis using VosViewer. This study identifies three clusters and seven thematic areas of research, along with 25 most used keywords. RQ2 is attended through review of the relationship between economic growth (Gross Domestic Product) and Circular Economy and proposes based on the review that CE is still at its infancy. The paper also discusses the appropriateness of using GDP as a measure of sustainable development. This paper addresses RQ3 by examining the relationship between Circular Economy and Sustainable Development through review of literatures. The indicators used to measure CE and SD are also discussed and summarised. This review finds that achieving SDGs require greater effort, and that the present status of achievement is a bleak picture. Further, the role of waste management and potentiality of waste valorisation to aid in circular economy and sustainable development is analysed to answer RQ4. Though there are ample potential, however the recycle rate is very minimal to quench the required level of circularity. While CE and SD are related, CE cannot be a universal panacea to global challenges like emissions reduction, energy consumption, climate change, gender equality, poverty, well-being, environmental protection etc. even though the impact of CE to achieve SD can be substantial. The paper recommends avenues for future research and presents the conclusion of the study

    Safe navigation and human-robot interaction in assistant robotic applications

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Multi-Agent Modelling of Industrial Cyber-Physical Systems for IEC 61499 Based Distributed Intelligent Automation

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    Traditional industrial automation systems developed under IEC 61131-3 in centralized architectures are statically programmed with determined procedures to perform predefined tasks in structured environments. Major challenges are that these systems designed under traditional engineering techniques and running on legacy automation platforms are unable to automatically discover alternative solutions, flexibly coordinate reconfigurable modules, and actively deploy corresponding functions, to quickly respond to frequent changes and intelligently adapt to evolving requirements in dynamic environments. The core objective of this research is to explore the design of multi-layer automation architectures to enable real-time adaptation at the device level and run-time intelligence throughout the whole system under a well-integrated modelling framework. Central to this goal is the research on the integration of multi-agent modelling and IEC 61499 function block modelling to form a new automation infrastructure for industrial cyber-physical systems. Multi-agent modelling uses autonomous and cooperative agents to achieve run-time intelligence in system design and module reconfiguration. IEC 61499 function block modelling applies object-oriented and event-driven function blocks to realize real-time adaption of automation logic and control algorithms. In this thesis, the design focuses on a two-layer self-manageable architecture modelling: a) the high-level cyber module designed as multi-agent computing model consisting of Monitoring Agent, Analysis Agent, Self-Learning Agent, Planning Agent, Execution Agent, and Knowledge Agent; and b) the low-level physical module designed as agent-embedded IEC 61499 function block model with Self-Manageable Service Execution Agent, Self-Configuration Agent, Self-Healing Agent, Self-Optimization Agent, and Self-Protection Agent. The design results in a new computing module for high-level multi-agent based automation architectures and a new design pattern for low-level function block modelled control solutions. The architecture modelling framework is demonstrated through various tests on the multi-agent simulation model developed in the agent modelling environment NetLogo and the experimental testbed designed on the Jetson Nano and Raspberry Pi platforms. The performance evaluation of regular execution time and adaptation time in two typical conditions for systems designed under three different architectures are also analyzed. The results demonstrate the ability of the proposed architecture to respond to major challenges in Industry 4.0

    Robots learn to behave: improving human-robot collaboration in flexible manufacturing applications

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Agent-based manufacturing — review and expert evaluation

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    The advent of smart manufacturing and the exposure to a new generation of technological enablers have revolutionized the way manufacturing process is carried out. Cyber-Physical Production Systems (CPPS) are introduced as main actors of this manufacturing shift. They are characterized for having high levels of communication, integration and computational capabilities that led them to a certain level of autonomy. Despite the high expectations and vision of CPPS, it still remains an exploratory topic. Multi-Agent Systems (MAS) have been widely used by software engineers to solve traditional computing problems, e.g., banking transactions. Because of their high levels of distribution and autonomous capabilities, MAS have been considered by the research community as a good solution to design and implement CPPS. This work first introduces a collection of requirements and characteristics of smart manufacturing. A comprehensive review of various research applications is presented to understand the current state of the art and the application of agent technology in manufacturing. Considering the smart manufacturing requirements and current research application, a SWOT analysis was formulated which identifies pros and cons of the implementation of agents in industry. The SWOT analysis was further validated by an industrial expert evaluation and the main findings and discussion of the results are presented

    A Design Science Research Approach to Architecting and Developing Information Systems for Collaborative Manufacturing : A Case for Human-Robot Collaboration

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    Konseptointi- ja suunnitteluvaiheessa sekä valmistuksen, käytön ja kehitysprosessin aikana syntyy tietoa, jonka hyödyntämisessä on valtavaa potentiaalia liike-elämän ja tuotantoprosessien muuttamiseen. Neljännen teollisen vallankumouksen ytimessä oleva digitaalinen muutos tunnistaa tämän painottaen erityisesti tämän tiedon yhdistämistä toimintojen ja järjestelmien tukemiseksi läpi tuotteen elinkaareen, mitä kutsutaan digitaaliseksi säikeen kehykseksi (digital thread framework). Tämän väitöskirjan tavoitteena on kehittää ja käyttää yhtä tällaista viitekehystä ihmisen ja robotin yhteistoiminnan asiayhteydessä. Tämä kehys pyrkii vastaamaan merkittävään ongelmaan, joka liittyy mukautuvuuden ja joustavuuden abstrakteihin ominaisuuksiin. Nykyiset ihmisen ja robotin yhteistyöjärjestelmät (human-robot collaboration (HRC)) on rakennettu pääasiassa pysyviksi järjestelmiksi, jotka sivuuttavat ihmisten intuitiivisen toiminnan asettamalla heidän roolinsa yhteistyötehtävissä etukäteen määritellyiksi. Lisäksi järjestelmien kyky vaihtaa tuotteesta toiseen on rajoittunutta. Tämä on erityisen ongelmallista nykyisellä laajan tuotevalikoiman aikakaudella, joka johtuu asiakkaiden räätälöidyistä vaatimuksista. Tähän taustaan vastaten, tämä väitöskirja käyttää design science research methodology -menetelmää suunnitellakseen, kehittääkseen ja ottaakseen käyttöön kolme pääasiallista artefaktia ihmisen ja robotin yhteistyösolussa laboratorioympäristössä. Ensimmäinen on digitaalisen säikeen kehys (digital thread framework), joka integroi tuotesuunnitteluympäristön toimijaksi monitoimijajärjestelmään käyttäen uusimpia tietoon perustuvia suunnittelujärjestelmiä, mikä tarjoaa prosessin toimijoille pääsyn tuotesuunnittelumalleihin reaaliajassa. Toinen on lisätyn todellisuuden malli, joka tarjoaa rajapinnan kokoonpanotehtävässä yhteistyöhön osallistuvan ihmisoperaattorin ja edellä mainitun kehyksen välille. Kolmas on tukitietomalli, jota yhteistyötä tekevät toimijat käyttävät tietopohjanaan täyttääkseen yhteistyössä tapahtuvan kokoonpanon tavoitteet mukautuvasti. Näitä kehitettyjä artefakteja käytettiin kokonaisuutena tapaustutkimuksissa, jotka liittyivät aidon dieselmoottorin kokoonpanoon, ja joissa todennettiin niiden hyödyllisyys ja että ne lisäävät joustavuutta, jota varten kehys (framework) suunniteltiin. Rajauslaatikoiden näyttäminen skaalautuvana informaationa, joka hahmottaa alikokoonpanon osien geometriaa, demostroi kehitettyjen artefaktien käytettävyyttä yhteistyötä tekevien toimijoiden aikomuksia heijastavien laajennetun todellisuuden projektioiden tuottamiseksi. Yhteenvetona tämän väitöskirjan tuloksena syntyi lähestymistapa älykkään ja mukautuvan robotiikan toteuttamiseksi hyödyntäen tietovirtoja ja mallinnusta ihmisen ja robotin yhteistoiminnan kontekstissa. Teollisuuden raportoima älykkäästi mukautuvien HRC-järjestelmien puute taas toimi osaltaan motivaationa tähän väitöskirjassa tehtyyn työhön. Kun tulevaisuuden tuotteet ja tuotantojärjestelmät muuttuvat monimutkaisemmiksi, tietojärjestelmiltä odotetaan suurempaa vastuuta korvaamaan ihmisen työmuistin luontaiset rajat ja mahdollistamaan siirtyminen kohti ihmiskeskeistä valmistusta, joihin viitataan termeillä Operator 4.0 ja Industry 5.0. Näin ollen on odotettavissa, että tietojärjestelmien tutkimus, kuten tämä väitöskirja, voi auttaa ottamaan merkittäviä askeleita tähän suuntaan.Information generated from the conceptualization, design, manufacturing, and use of a product has immense potential in transforming both the business and manufacturing processes of the manufacturing enterprise. The digital transformation at the heart of the fourth industrial revolution has acknowledged this with a special emphasis on weaving a thread of this information to support functions and systems throughout the life cycle of the product with what is known as a digital thread framework. This dissertation aims to develop and use one such framework in the context of human-robot collaborative assembly. The overarching problem that the framework aims to solve can be attributed to the abstract qualities of adaptability and flexibility. The human-robot collaboration (HRC) systems of today are built predominantly as static systems and ignore the intuitive role of humans by having their roles in collaborative tasks pre-defined. Furthermore, their ability to switch between products during product changeovers is also limited. This is especially problematic in the current era of product variety, stemming from the customised requirements of customers. To this end, this dissertation employs the design science research methodology to design, develop, and deploy predominantly three artefacts in a human-robot work cell in a laboratory setting. The first is the digital thread framework that integrates the product design environment using state-of-the-art knowledge-based engineering systems, as an agent of a multi-agent system, which provide the collaborative human-robot agents with access to product design models at run time. The second is a constituent mixed-reality model that provides an interface for the foregoing framework for the human operator engaged in collaborative assembly. The third is a supporting information model that the agents use as their knowledge base to fulfil adaptively the goals of collaborative assembly. Together, these developed artefacts were employed in case studies involving a real diesel engine assembly during which they were observed to provide utility and support the cause of adaptability for which the framework was designed. The identification of bounding boxes as a scalable information construct, that approximates the part geometry of the sub-assembly components, demonstrates the utility of the developed artefacts for spatially augmenting them as projections as intentions of collaborating agents. In summary, this dissertation contributes with an approach towards realising intelligent and adaptive robotics within the realms of information flows and modelling in the context of human-robot collaboration. The lack of intelligently adaptable HRC systems reported by the industry in part motivated the work undertaken in this dissertation. As future products and production systems become more complex, information systems are expected to assume greater responsibility to compensate for the inherent limits of the human working memory and enable transition towards a human-centred manufacturing, the current likes of which are labelled as Operator 4.0 and Industry 5.0. Thus, the expectation is that information systems research, such as this dissertation, can help take significant strides forward in this direction
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