European smart specialization for Ukrainian regional development: path from creation to implementation

The focus of the research is to develop recommendations of smart specialization (SS) for Ukrainian policymakers using European approaches. The authors revealed that the main SS projects are presented in such sectors as agri-food, industrial modernization and energy. More than 12 EU countries were the plot for conducted analysis of SS, as a result of which the level of activity of each country was determined. The creation of consortiums, including SMEs, associations, universities and other participants, disclosed the successful way of SS realization. The structure of SME’s innovative potential in Ukraine was identified underlining their main characteristic features like types of innovations and innovative activity, differentiation according to enterprise size, their regional distribution. The authors explored lack of innovations on regional and national level and significant territorial disparities, which could be eliminated through policy implementation of regional SS. The existing legislative norms for possibility of SS implementation in Ukraine were analyzed due to correspondence with the EU ones. The analysis provides the opportunity to consider them only as general framework documents without any action plans and sectoral prioritization at all. The weak points of these law documents are emphasized. As a result of research, the authors developed recommendations presented by direct action plan for Ukrainian policymakers, which include such activities as underlining key priorities (especially ICT applicability in every SS project) and their correspondence with the EU ones; eliminating regional imbalances by focusing on innovation development and reorientation of some regions according to SS priorities; respecting regional existing capacities; providing organizational mechanism for cooperation of stakeholders and financial mechanism for SS support through the EU structural funds

Characterising the agriculture 4.0 landscape - Emerging trends, challenges and opportunities

ReviewInvestment in technological research is imperative to stimulate the development of sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and sensor networks, robotics, artificial intelligence, big data, cloud computing, etc. foster the transition towards the Agriculture 4.0 era. This fourth revolution is currently seen as a possible solution for improving agricultural growth, ensuring the future needs of the global population in a fair, resilient and sustainable way. In this context, this article aims at characterising the current Agriculture 4.0 landscape. Emerging trends were compiled using a semi-automated process by analysing relevant scientific publications published in the past ten years. Subsequently, a literature review focusing these trends was conducted, with a particular emphasis on their applications in real environments. From the results of the study, some challenges are discussed, as well as opportunities for future research. Finally, a high-level cloud-based IoT architecture is presented, serving as foundation for designing future smart agricultural systems. It is expected that this work will positively impact the research around Agriculture 4.0 systems, providing a clear characterisation of the concept along with guidelines to assist the actors in a successful transition towards the digitalisation of the sectorinfo:eu-repo/semantics/publishedVersio

Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture

[EN] The term "Agri-Food 4.0" is an analogy to the term Industry 4.0; coming from the concept "agriculture 4.0". Since the origins of the industrial revolution, where the steam engines started the concept of Industry 1.0 and later the use of electricity upgraded the concept to Industry 2.0, the use of technologies generated a milestone in the industry revolution by addressing the Industry 3.0 concept. Hence, Industry 4.0, it is about including and integrating the latest developments based on digital technologies as well as the interoperability process across them. This allows enterprises to transmit real-time information in terms behaviour and performance. Therefore, the challenge is to maintain these complex networked structures efficiently linked and organised within the use of such technologies, especially to identify and satisfy supply chain stakeholders dynamic requirements. In this context, the agriculture domain is not an exception although it possesses some specialities depending from the domain. In fact, all agricultural machinery incorporates electronic controls and has entered to the digital age, enhancing their current performance. In addition, electronics, using sensors and drones, support the data collection of several agriculture key aspects, such as weather, geographical spatialization, animals and crops behaviours, as well as the entire farm life cycle. However, the use of the right methods and methodologies for enhancing agriculture supply chains performance is still a challenge, thus the concept of Industry 4.0 has evolved and adapted to agriculture 4.0 in order analyse the behaviours and performance in this specific domain. Thus, the question mark on how agriculture 4.0 support a better supply chain decision-making process, or how can help to save time to farmer to make effective decision based on objective data, remains open. Therefore, in this survey, a review of more than hundred papers on new technologies and the new available supply chains methods are analysed and contrasted to understand the future paths of the Agri-Food domain.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCARISE-2015.Lezoche, M.; Hernández, JE.; Alemany Díaz, MDM.; Panetto, H.; Kacprzyk, J. (2020). Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture. Computers in Industry. 117:1-15. https://doi.org/10.1016/j.compind.2020.103187S115117Ahumada, O., & Villalobos, J. R. (2009). Application of planning models in the agri-food supply chain: A review. 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ADAPTS: An Intelligent Sustainable Conceptual Framework for Engineering Projects

This paper presents a conceptual framework for the optimization of environmental sustainability in engineering projects, both for products and industrial facilities or processes. The main objective of this work is to propose a conceptual framework to help researchers to approach optimization under the criteria of sustainability of engineering projects, making use of current Machine Learning techniques. For the development of this conceptual framework, a bibliographic search has been carried out on the Web of Science. From the selected documents and through a hermeneutic procedure the texts have been analyzed and the conceptual framework has been carried out. A graphic representation pyramid shape is shown to clearly define the variables of the proposed conceptual framework and their relationships. The conceptual framework consists of 5 dimensions; its acronym is ADAPTS. In the base are: (1) the Application to which it is intended, (2) the available DAta, (3) the APproach under which it is operated, and (4) the machine learning Tool used. At the top of the pyramid, (5) the necessary Sensing. A study case is proposed to show its applicability. This work is part of a broader line of research, in terms of optimization under sustainability criteria.Telefónica Chair “Intelligence in Networks” of the University of Seville (Spain

A concept for application of integrated digital technologies to enhance future smart agricultural systems

Future agricultural systems should increase productivity and sustainability of food production and supply. For this, integrated and efficient capture, management, sharing, and use of agricultural and environmental data from multiple sources is essential. However, there are challenges to understand and efficiently use different types of agricultural and environmental data from multiple sources, which differ in format and time interval. In this regard, the role of emerging technologies is considered to be significant for integrated data gathering, analyses and efficient use. In this study, a concept was developed to facilitate the full integration of digital technologies to enhance future smart and sustainable agricultural systems. The concept has been developed based on the results of a literature review and diverse experiences and expertise which enabled the identification of stat-of-the-art smart technologies, challenges and knowledge gaps. The features of the proposed solution include: data collection methodologies using smart digital tools; platforms for data handling and sharing; application of Artificial Intelligent for data integration and analysis; edge and cloud computing; application of Blockchain, decision support system; and a governance and data security system. The study identified the potential positive implications i.e. the implementation of the concept could increase data value, farm productivity, effectiveness in monitoring of farm operations and decision making, and provide innovative farm business models. The concept could contribute to an overall increase in the competitiveness, sustainability, and resilience of the agricultural sector as well as digital transformation in agriculture and rural areas. This study also provided future research direction in relation to the proposed concept. The results will benefit researchers, practitioners, developers of smart tools, and policy makers supporting the transition to smarter and more sustainable agriculture systems

A general outline of a sustainable supply chain 4.0

[EN] This article presents a literature review to identify the current knowledge of supply chains 4.0 from the sustainability perspective. Reviewed papers were classified in terms of objectives, results, and sustainability approaches. Additionally, a critical discussion with the main results and recommendations for further research was carried out. Manufacturing supply chains have been contemplated but agri-food supply chains and chains related to diversified cropping systems have been also considered. In this way, 54 articles were identified and revised, and were classified according to the three main aspects of sustainability: economic, social, and environmental. The classification of articles indicated that more attention has been paid to the environmental aspect in the industry 4.0 (I4.0) context in the literature, while the social aspect has been paid less attention. Finally, reference frameworks were identified, along with the I4.0 models, algorithms, heuristics, metaheuristics, and technologies, which have enabled sustainability in supply chains.This research was supported by the European Commission Horizon 2020 project entitled 'Crop diversification and low-input farming cross Europe: From practitioners' engagement and ecosystems services to increased revenues and value chain organisation' (Diverfarming), grant agreement 728003; and the Spanish Ministry of Science, Innovation, and Universities project entitled 'Optimisation of zero-defects production technologies enabling supply chains 4.0 (CADS4.0)' (RTI2018-101344-B-I00).Cañas, H.; Mula, J.; Campuzano-Bolarín, F. (2020). A general outline of a sustainable supply chain 4.0. Sustainability. 12(19):1-17. https://doi.org/10.3390/su121979781171219Design Principles for Industrie 4.0 Scenarios https://ieeexplore.ieee.org/document/7427673Liao, Y., Deschamps, F., Loures, E. de F. R., & Ramos, L. F. P. (2017). Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), 3609-3629. doi:10.1080/00207543.2017.1308576Tseng, M.-L., Zhu, Q., Sarkis, J., & Chiu, A. S. F. (2018). Responsible consumption and production (RCP) in corporate decision-making models using soft computation. Industrial Management & Data Systems, 118(2), 322-329. doi:10.1108/imds-11-2017-0507Ghadimi, P., Wang, C., Lim, M. K., & Heavey, C. (2019). Intelligent sustainable supplier selection using multi-agent technology: Theory and application for Industry 4.0 supply chains. Computers & Industrial Engineering, 127, 588-600. doi:10.1016/j.cie.2018.10.050Wang, C., Ghadimi, P., Lim, M. K., & Tseng, M.-L. (2019). A literature review of sustainable consumption and production: A comparative analysis in developed and developing economies. Journal of Cleaner Production, 206, 741-754. doi:10.1016/j.jclepro.2018.09.172Exploring Linkages between Lean and Green Supply Chain and the Industry 4.0 https://link.springer.com/chapter/10.1007/978-3-319-59280-0_103Luthra, S., & Mangla, S. K. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117, 168-179. doi:10.1016/j.psep.2018.04.018Lin, K., Shyu, J., & Ding, K. (2017). A Cross-Strait Comparison of Innovation Policy under Industry 4.0 and Sustainability Development Transition. Sustainability, 9(5), 786. doi:10.3390/su9050786Man, J. C. de, & Strandhagen, J. O. (2017). An Industry 4.0 Research Agenda for Sustainable Business Models. Procedia CIRP, 63, 721-726. doi:10.1016/j.procir.2017.03.315KIEL, D., MÜLLER, J. M., ARNOLD, C., & VOIGT, K.-I. (2017). SUSTAINABLE INDUSTRIAL VALUE CREATION: BENEFITS AND CHALLENGES OF INDUSTRY 4.0. 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Procedia Manufacturing, 21, 438-445. doi:10.1016/j.promfg.2018.02.142Müller, J. M., Kiel, D., & Voigt, K.-I. (2018). What Drives the Implementation of Industry 4.0? The Role of Opportunities and Challenges in the Context of Sustainability. Sustainability, 10(1), 247. doi:10.3390/su10010247Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, 117, 408-425. doi:10.1016/j.psep.2018.05.009Hidayatno, A., Destyanto, A. R., & Hulu, C. A. (2019). Industry 4.0 Technology Implementation Impact to Industrial Sustainable Energy in Indonesia: A Model Conceptualization. Energy Procedia, 156, 227-233. doi:10.1016/j.egypro.2018.11.133Sustainable Value Stream Mapping and Technologies of Industry 4.0 in Manufacturing Process Reconfiguration: A Case Study in an Apparel Company https://ieeexplore.ieee.org/document/8476750Kumar, R., Singh, S. P., & Lamba, K. (2018). Sustainable robust layout using Big Data approach: A key towards industry 4.0. Journal of Cleaner Production, 204, 643-659. doi:10.1016/j.jclepro.2018.08.327Wiśniewska-Sałek, A. (2018). Sustainable Development in Accordance With the Concept of Industry 4.0 on the Example of the Furniture Industry. MATEC Web of Conferences, 183, 04005. doi:10.1051/matecconf/201818304005Müller, J. M., & Voigt, K.-I. (2018). Sustainable Industrial Value Creation in SMEs: A Comparison between Industry 4.0 and Made in China 2025. International Journal of Precision Engineering and Manufacturing-Green Technology, 5(5), 659-670. doi:10.1007/s40684-018-0056-zTsai, W.-H., & Lu, Y.-H. (2018). A Framework of Production Planning and Control with Carbon Tax under Industry 4.0. Sustainability, 10(9), 3221. doi:10.3390/su10093221Birkel, H., Veile, J., Müller, J., Hartmann, E., & Voigt, K.-I. (2019). Development of a Risk Framework for Industry 4.0 in the Context of Sustainability for Established Manufacturers. Sustainability, 11(2), 384. doi:10.3390/su11020384Roda-Sanchez, L., Garrido-Hidalgo, C., Hortelano, D., Olivares, T., & Ruiz, M. C. (2018). OperaBLE: An IoT-Based Wearable to Improve Efficiency and Smart Worker Care Services in Industry 4.0. Journal of Sensors, 2018, 1-12. doi:10.1155/2018/6272793Ardanza, A., Moreno, A., Segura, Á., de la Cruz, M., & Aguinaga, D. (2019). Sustainable and flexible industrial human machine interfaces to support adaptable applications in the Industry 4.0 paradigm. International Journal of Production Research, 57(12), 4045-4059. doi:10.1080/00207543.2019.1572932Zambon, I., Cecchini, M., Egidi, G., Saporito, M. G., & Colantoni, A. (2019). Revolution 4.0: Industry vs. Agriculture in a Future Development for SMEs. Processes, 7(1), 36. doi:10.3390/pr7010036Belaud, J.-P., Prioux, N., Vialle, C., & Sablayrolles, C. (2019). Big data for agri-food 4.0: Application to sustainability management for by-products supply chain. Computers in Industry, 111, 41-50. doi:10.1016/j.compind.2019.06.006Trivelli, L., Apicella, A., Chiarello, F., Rana, R., Fantoni, G., & Tarabella, A. (2019). From precision agriculture to Industry 4.0. British Food Journal, 121(8), 1730-1743. doi:10.1108/bfj-11-2018-0747Miranda, J., Ponce, P., Molina, A., & Wright, P. (2019). Sensing, smart and sustainable technologies for Agri-Food 4.0. Computers in Industry, 108, 21-36. doi:10.1016/j.compind.2019.02.002Stock, T., Obenaus, M., Kunz, S., & Kohl, H. (2018). Industry 4.0 as enabler for a sustainable development: A qualitative assessment of its ecological and social potential. Process Safety and Environmental Protection, 118, 254-267. doi:10.1016/j.psep.2018.06.026Chaim, O., Muschard, B., Cazarini, E., & Rozenfeld, H. (2018). Insertion of sustainability performance indicators in an industry 4.0 virtual learning environment. Procedia Manufacturing, 21, 446-453. doi:10.1016/j.promfg.2018.02.143Smart Factories in Industry 4.0: A Review of the Concept and of Energy Management Approached in Production Based on the Internet of Things Paradigm https://ieeexplore.ieee.org/document/7058728Bonilla, S., Silva, H., Terra da Silva, M., Franco Gonçalves, R., & Sacomano, J. (2018). Industry 4.0 and Sustainability Implications: A Scenario-Based Analysis of the Impacts and Challenges. Sustainability, 10(10), 3740. doi:10.3390/su10103740De Sousa Jabbour, A. B. L., Jabbour, C. J. C., Foropon, C., & Godinho Filho, M. (2018). When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors. 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Sustainability, 10(12), 4511. doi:10.3390/su10124511IoT Solution for Energy Optimization in Industry 4.0: Issues of a Real-life Implementation https://ieeexplore.ieee.org/document/8534537Towards a System-of-Systems for Improved Road Construction Efficiency Using Lean and Industry 4.0 https://ieeexplore.ieee.org/document/8428698HERNANDEZ LUNA, M., ROBLEDO FAVA, R., FERNANDEZ DE CORDOBA CASTELLA, P., PAREDES, A., MICHINEL ALVAREZ, H., & ZARAGOZA FERNANDEZ, S. (2018). USE OF STATISTICAL CORRELATION FOR ENERGY MANAGEMENT IN OFFICE PREMISES ADOPTING TECHNIQUES OF THE INDUSTRY 4.0. DYNA, 93(1), 602-607. doi:10.6036/8844Energy Management in Industry 4.0 Ecosystem: A Review on Possibilities and Concerns https://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2018/097.pdfWang, X. V., & Wang, L. (2018). Digital twin-based WEEE recycling, recovery and remanufacturing in the background of Industry 4.0. International Journal of Production Research, 57(12), 3892-3902. doi:10.1080/00207543.2018.1497819Tsai, W.-H. (2018). Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques. Energies, 11(8), 2072. doi:10.3390/en11082072Sherazi, H. H. R., Imran, M. A., Boggia, G., & Grieco, L. A. (2018). Energy Harvesting in LoRaWAN: A Cost Analysis for the Industry 4.0. IEEE Communications Letters, 22(11), 2358-2361. doi:10.1109/lcomm.2018.2869404Tsai, W.-H., Chu, P.-Y., & Lee, H.-L. (2019). Green Activity-Based Costing Production Planning and Scenario Analysis for the Aluminum-Alloy Wheel Industry under Industry 4.0. Sustainability, 11(3), 756. doi:10.3390/su11030756Analysis of the Variables That Affect the Intention to Adopt Precision Agriculture for Smart Water Management in Agriculture 4.0 Context https://ieeexplore.ieee.org/document/8766384Franciosi, C., Iung, B., Miranda, S., & Riemma, S. (2018). Maintenance for Sustainability in the Industry 4.0 context: a Scoping Literature Review. IFAC-PapersOnLine, 51(11), 903-908. doi:10.1016/j.ifacol.2018.08.459DE LAS HERAS GARCIA DE VINUESA, A., AGUAYO GONZALEZ, F., & CORDOBA ROLDAN, A. (2018). PROPOSAL OF A FRAMEWORK FOR THE EVALUATION OF THE SUSTAINABILITY OF PRODUCTS FROM THE PARADIGM OF THE CIRCULAR ECONOMY BASED ON INDUSTRY 4.0 (1ST PART). DYNA, 93(1), 360-364. doi:10.6036/8631DE LAS HERAS GARCIA DE VINUESA, A., AGUAYO GONZALEZ, F., & CORDOBA ROLDAN, A. (2018). PROPOSAL OF A FRAMEWORK FOR THE EVALUATION OF THE SUSTAINABILITY OF PRODUCT SUSTAINABILITY FROM THE PARADIGM OF THE CIRCULAR ECONOMY BASED ON INDUSTRY 4.0. (Part 2). DYNA, 93(1), 488-496. doi:10.6036/8718Nascimento, D. L. M., Alencastro, V., Quelhas, O. L. G., Caiado, R. G. G., Garza-Reyes, J. A., Rocha-Lona, L., & Tortorella, G. (2019). Exploring Industry 4.0 technologies to enable circular economy practices in a manufacturing context. 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Enhancing the sustainability performance of Agri-Food Supply Chains by implementing Industry 4.0

[EN] In order to enhance the sustainability in the supply chain, its members should define and pursue common objectives in the three dimensions of the sustainability (economic, environmental and social). The Agri-Food Supply Chain (AFSC) is a network of different members such as farmers (producers), processors and distributors (wholesales, retailers.), etc.. In order to achieve the performance objectives of the AFSC, Industry 4.0 technologies can be implemented. The aim of this paper is to present a classification of these technologies according to two criteria: objective to be achieved (environmental or social) specified in the main issues to be covered in each objective and member of the AFSC supply chain where it is implemented. In this work, we focus on technologies that deal with environmental and social sustainability because economic sustainability will depend on the specific characteristics of the business (a supply chain using a specific Industry 4.0 technology may be profitable while others do not).This work has been funded by the Project GV/2017/065 "Development of a decision support tool for the management and improvement of sustainability in supply chains" funded by the Regional Government of Valencia. Authors also acknowledge the Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems.Pérez Perales, D.; Verdecho Sáez, MJ.; Alarcón Valero, F. (2019). Enhancing the sustainability performance of Agri-Food Supply Chains by implementing Industry 4.0. 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Smart Agriculture Development and Its Contribution to the Sustainable Digital Transformation of the Agri-Food Sector

This study analyses the importance of the connection between the development of smart agriculture and sustainable digital transformation (DT) of the agri-food sector. The sustainability of DT depends on a number of complex components, especially information and communication technologies (ICT), and economic systems. The increase in the number of studies in this area indicates a complex nature as well as interdependencies. Over the last few decades of innovation, ICT, artificial intelligence (AI) and the Internet of Things (IoT) have significantly affected human activities in all aspects. This includes the rapidly changing and difficult-to-predict agricultural sector in the context of global development, indicating the need to address these challenges. The global trend of DT has included all sectors, opening space for the contribution of smart agriculture to sustainable DT, but also to find appropriate "tailor-made solutions" for every challenge we face

Precision Techniques and Agriculture 4.0 Technologies to Promote Sustainability in the Coffee Sector: State of the Art, Challenges and Future Trends

Precision Agriculture (PA) and Agriculture 4.0 (A4.0) have been widely discussed as a medium to address the challenges related to agricultural production. In this research, we present a Systematic Literature Review (SLR) supported by a Bibliometric Performance and Network Analysis (BPNA) of the use of A4.0 technologies and PA techniques in the coffee sector. To perform the SLR, 87 documents published since 2011 were extracted from the Scopus and Web of Science databases and processed through the Preferred Reporting Items for Systematic reviews and Meta-Analyzes (PRISMA) protocol. The BPNA was carried out to identify the strategic themes in the field of study. The results present 23 clusters with different levels of development and maturity. We also discovered and presented the thematic network structure of the most used A4.0 technologies in the coffee sector. Our findings shows that Internet of Things, Machine Learning and geostatistics are the most used technologies in the coffee sector, we also present the main challenges and trends related to technological adoption in coffee systems. We believe that the demonstrated results have the potential to be considered by researchers in future works and decision making related to the field of study

Study and Analysis of the Implementation of 4.0 Technologies in the Agri-Food Supply Chain: A State of the Art

Industry 4.0 is changing the industrial environment. Particularly, the emerging Industry 4.0 technologies can improve the agri-food supply chain throughout all its stages. This study aims to highlight the benefits of implementing Industry 4.0 in the agri-food supply chain. First, it presents how technologies enhance the agri-food supply chain development. Then, it identifies and highlights the most common challenges that Industry 4.0 implementation faces in agri-food’s environment. After that, it proposes key performance indicators to measure the advantages of this implementation. To achieve this, a systematic literature review was conducted. It combined conceptual and bibliometric analyses of 78 papers. As a result, the most suitable technologies were identified, e.g., Internet of Things, Big Data, blockchain and cyber physical systems. The most used indicators are proposed and the challenges of implementation were detected and classified in three groups, i.e., technical, educational and governmental. This paper highlights and exemplifies the benefits of implementing Industry 4.0 facing the lack of knowledge that exists nowadays. Moreover, it fulfils the gaps in literature, i.e., the lack of information about the implementation of technologies 4.0 or the description of the most relevant indicators for Industry 4.0 implementation.This research study received no external fundin