The CDIO Syllabus 3.0 - An Updated Statement of Goals

The CDIO Initiative is going through a process of reconsidering and updating the CDIO approach for engineering education development. Previous work resulted in substantial updates of the twelve CDIO standards and the introduction of “optional” CDIO standards. This paper reports on a similar review and update of the CDIO Syllabus to version 3.0. It has been developed by a working group consisting of four sub-groups and iterated and refined guided by feedback from the whole CDIO community. There are mainly three external drivers that motivate the changes: sustainability, digitalization, and acceleration. There is also an internal driver in the form of lessons learned within the CDIO community, from using the Syllabus in curriculum and course development. Approximately 70 updates are proposed, amongst them three additions on the X.X level, namely 1.4 Knowledge of Social Sciences and Humanities, 3.1 Teamwork and Collaboration, and 5.3 Research

The CDIO Syllabus 3.0 - An Updated Statement of Goals

The CDIO Initiative is going through a process of reconsidering and updating the CDIO approach for engineering education development. Previous work resulted in substantial updates of the twelve CDIO standards and the introduction of “optional” CDIO standards. This paper reports on a similar review and update of the CDIO Syllabus to version 3.0. It has been developed by a working group consisting of four sub-groups and iterated and refined guided by feedback from the whole CDIO community. There are mainly three external drivers that motivate the changes: sustainability, digitalization, and acceleration. There is also an internal driver in the form of lessons learned within the CDIO community, from using the Syllabus in curriculum and course development. Approximately 70 updates are proposed, amongst them three additions on the X.X level, namely 1.4 Knowledge of Social Sciences and Humanities, 3.1 Teamwork and Collaboration, and 5.3 Research

Occupational Safety and Health 5.0—A Model for Multilevel Strategic Deployment Aligned with the Sustainable Development Goals of Agenda 2030

The concept of Industry 4.0 (I4.0) is evolving towards Industry 5.0 (I5.0), where the human factor is the central axis for the formation of smart cyber-physical socio-technical systems that are integrated into their physical and cultural host environment. This situation generates a new work ecosystem with a radical change in the methods, processes and development scenarios and, therefore, in the occupational risks to which safety science must respond. In this paper, a historical review of the evolution of work as a complex socio-technical system formalised through Vygostky’s theory of Activity and the contributions of safety science is carried out, for its projection in the analysis of the future of complex systems as an opportunity for safety research linked to the current labour context in transformation. Next, the Horizon 2020 strategies for Occupational Safety and Health (OSH) at the European level are analysed to extract the lessons learned and extrapolate them towards the proposed model, and subsequently the conceptual frameworks that are transforming work and Occupational Risk Prevention (ORP) in the transition to Industry 4.0 are identified and reviewed. Finally, a model is formulated that formalises the deployment of public policies and multi-level and multi-scale OSH 5.0 strategies within the framework of the Sustainable Development Goals (SDGs) of the United Nations (UN) for Horizon 2030

WAx: an integrated conceptual framework for the analysis of cyber-socio-technical systems

Modern work domains are constituted by an intertwined set of social and technical actors with different, often conflicting, functional purposes. These agents act jointly to ensure system's functioning under both expected and unexpected working conditions. Considering the increasing digitalization and automation of work processes, socio-technical systems are progressively including interconnected cyber technical artefacts, thus becoming cyber-socio-technical systems (CSTSs). Adopting a natural science perspective, this paper aims to explore knowledge creation and knowledge conversion within CSTSs, as rooted in an in-depth analysis of work practices and work contexts. The paper proposes a conceptual framework which unveils the relationships between different work representations, i.e. relying on Work-As-Imagined, Work-As-Done, Work-As-Disclosed, Work-As-Observed, intended as knowledge entities generated by different agents, i.e. sharp-end operators, blunt-end operators, and analysts. The recursive and fractal nature of the proposed WAx (Work-As-x) framework ensures its adaptability for different granularity levels of analysis, fostering the understanding, modeling, and analysis of work practices, while abandoning reductionist and over-simplistic approaches

Transdisciplinary AI Observatory -- Retrospective Analyses and Future-Oriented Contradistinctions

In the last years, AI safety gained international recognition in the light of heterogeneous safety-critical and ethical issues that risk overshadowing the broad beneficial impacts of AI. In this context, the implementation of AI observatory endeavors represents one key research direction. This paper motivates the need for an inherently transdisciplinary AI observatory approach integrating diverse retrospective and counterfactual views. We delineate aims and limitations while providing hands-on-advice utilizing concrete practical examples. Distinguishing between unintentionally and intentionally triggered AI risks with diverse socio-psycho-technological impacts, we exemplify a retrospective descriptive analysis followed by a retrospective counterfactual risk analysis. Building on these AI observatory tools, we present near-term transdisciplinary guidelines for AI safety. As further contribution, we discuss differentiated and tailored long-term directions through the lens of two disparate modern AI safety paradigms. For simplicity, we refer to these two different paradigms with the terms artificial stupidity (AS) and eternal creativity (EC) respectively. While both AS and EC acknowledge the need for a hybrid cognitive-affective approach to AI safety and overlap with regard to many short-term considerations, they differ fundamentally in the nature of multiple envisaged long-term solution patterns. By compiling relevant underlying contradistinctions, we aim to provide future-oriented incentives for constructive dialectics in practical and theoretical AI safety research

Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing

This book focuses on recent developments in new industrial platforms, with Industry 4.0 on its way to becoming Industry 5.0. The book covers smart decision support systems for green and sustainable machining, microscale machining, cyber-physical production networks, and the optimization of assembly lines. The modern multiobjective algorithms and multicriteria decision-making methods are applied to various real-world industrial problems. The emerging problem of cybersecurity in advanced technologies is addressed as well

Digitalization for agriculture and rural development in Ukraine

The introduction of digital technologies in agricultural production is one of the most important elements of strategic development in the agricultural sector and rural areas in Ukraine. In agriculture, these new technologies can modernize the industry, promoting innovation in agribusiness and creating new opportunities for rural development. The introduction of digital technologies in agriculture ensures the accuracy of measurements, speed data collection and processing. Digitization in rural areas is an inevitable process that brings a number of economic, social and environmental benefits. The immediate aim of this paper is to assess the state of implementation of digital technologies in agriculture and to examine opportunities for rural development in Ukraine. Research methods: monographic, descriptive, analysis, synthesis, induction. The results indicate that only large agricultural enterprises in Ukraine are able to implement and use digital technologies. Thus, it is proposed to create an integrated digital portal for agricultural needs, combining solutions that optimize activities of agricultural enterprises: land bank management, production, crop monitoring, warehouse, procurement and supply, equipment and repairs, logistics, inventory and finished products. The article identifies technological and human barriers to introduction of digital technologies in rural areas of Ukraine. In addition it proposes strategies for development of digital literacy and skills among rural residents in Ukraine. The results of the research can have a significant impact on the development of agriculture in Ukraine, promoting digital technologies among other agricultural enterprises and ensuring the development in rural areas, attracting additional agricultural market participants and infrastructure that provide relevant information and digital services to rural residents

Industrial Revolution and Smart Farming: A Critical Analysis of Research Components in Industry 4.0

Purpose of the Research: The domains of Industry 4.0 and Smart Farming encompass the application of digitization, automation, and data-driven decision-making principles to revolutionize conventional sectors. The intersection of these two fields has numerous opportunities for industry, society, science, technology, and research. Relatively, this intersection is new, and still, many grey areas need to be identified. This research is a step toward identifying research areas and current trends. Methodology Followed: The present study examines prevailing research patterns and prospective research prospects within Industry 4.0 and Smart Farming. This is accomplished by utilizing the Latent Dirichlet Allocation (LDA) methodology applied to the data procured from the Scopus database. Results Obtained: By examining the available literature extensively, the researchers have successfully discovered and developed three separate research questions. The questions mentioned above were afterward examined with great attention to detail after using Latent Dirichlet Allocation (LDA) on the dataset. The paper highlights a notable finding on the lack of existing scholarly research in the examined combined field. The existing database consists of a restricted collection of 51 scholarly papers. Nevertheless, the forthcoming terrain harbors immense possibilities for exploration and offers a plethora of prospects for additional investigation and cerebral evaluation. The originality of the research: Based on a thorough examination of existing literature, it has been established that there is a lack of research specifically focusing on the convergence of Industry 4.0 and Smart Farming. However, notable progress has been achieved in the field of seclusion. To date, the provided dataset has not been subjected to analysis using the Latent Dirichlet Allocation (LDA) technique by any researcher. Practical Implications: This study examines the Industrial Revolution's and Smart Farming's practical effects, focusing on Industry 4.0 research. The proposed method could help agricultural practitioners implement Industry 4.0 technology. It could additionally counsel technology developers on innovation and ease technology transfer. Research on regulatory frameworks, incentive programs, and resource conservation may help policymakers and government agencies