This study aimed to verify the efficacy of a strategy for science learning acquisition based on contextual, metacognitive and sociocultural perspectives, strongly linked to the paradigm of conceptual change.The teaching model we adopted is based on co-operation for the realization of scientific experiences, and included direct observation, pair or group work, individual written reports and confrontation through discussion by the whole class.The experiment also aimed at verifying the efficacy of our learning strategy on the acquisition of skills such as debating, prediction, description, narrative structure and basic cognitive linguistic competence (the capacity to activate periphrastic, inferential, logical, critical, evaluative and aesthetic-poetic reasoning during the reading of a passage).Our sample consisted of 79 pupils, aged 7 to 10 years: the experimental group (18 boys and 22 girls) and the control group (19 boys and 20 girls).The result show that the children belonging to the experimental group, unlike those from the control group, were able to give reasons why the scientific phenomena they studied occurred and were better to explain these newly acquired concepts, producing spontaneously a large amount of metaphors and analogies, while they tried to understand, record and discuss what they had observed.
Over the last years, several technologies and control systems have been developed towards the decentralization of automation control architectures for cyber-physical production systems. Nevertheless, only few of these technologies are already in use. To support their adoption in brownfield production sites migration strategies and business case evaluations are necessary. This paper presents a migration approach and a business case evaluation methodology tailored to the migration of legacy automation systems towards the Industry 4.0 paradigm. The proposed approach aims to evaluate opportunities and mitigate the risks of migration from technical, operational, human and business perspectives. The methodology follows an iterative approach starting from the definition of the current situation of the factory and the identification of business goals aiming at evaluating a set of possible migration paths and selecting the optimal one according to a cost-benefit analysis. The paper concludes with an exemplary application of the methodology in a real industrial environment, developed within the FAR-EDGE European Project.
Industrial competitiveness today means shorter product lifecycles, increased product variety and shorter time-to-market. To face this challenge, the manufacturing industry is forced by different initiatives, namely Internet of Things, Industrie 4.0 and Cyber-Physical System to move from traditional control approaches towards intelligent manufacturing control systems that are dynamically adaptable to changing production environment and flexible to different processing tasks. For years several emergent intelligent approaches such as Multi-Agent Systems, Service-oriented Architecture, Plug-and-Produce systems and Cloud technologies have been developed in a variety of research fields. This paper reviews the state-of-the-art methodologies and technologies of flexible and reconfigurable manufacturing systems outlining the differences between them and arising benefits within the vision of the PERFoRM (Production harmonizEd Reconfiguration of Flexible Robots and Machinery) project. Current trends and challenges in industrial implementation of these methodologies are reported and research opportunities are described
In a global market characterized by strong competition and quickly changing boundary conditions, flexible and reconfigurable production systems can rapidly react to both endogenous and exogenous drivers. To this extent, it is necessary to define a new production system model, which can combine the most significant key business factors (KBFs), in order to meet the specified objectives and the relevant KPIs and to control the system. The model can be used within a cyber-physical system, to properly support the different functions and take the right decisions through simulation ICT tools. This research task is part of PERFoRM (Production harmonizEd Reconfiguration of Flexible Robots and Machinery), a European funded project, which aims at developing an innovative manufacturing system based on a new agile concept introducing the implementation of methods, methodologies and strategies for transforming existing production systems into plug-and-produce production ones based on Cyber-Physical Systems technologies. In particular, this paper aims at describing the relationships among the KBFs (Key Business Factors), namely the drivers of the production system, and the relevant KPIs. The model has been validated through an industrial use case, in order to gain important information about constraints and opportunities for improvement in other contexts.
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