1,721,096 research outputs found
Design, development and test of a novel broach for long polypropylene tubes
No full textPolymers are frequently used for a variety of applications in industry. One relevant field is plastic tubing. As plastic tubes are manufactured from thermoplastic material through hot-extrusion their dimensional accuracy is only moderate. Wherever high accuracy on tube diameters and roundness are required, the conventional production techniques reach their limits and more complex technologies are needed. Known approaches from metal machining are deep hole drilling and internal broaching. However, machining processes with chip removal on polymeric materials are not so common. Therefore, the authors studied cutting operations of polypropylene experimentally. Based on their findings they designed and built an internal broach for the machining of polypropylene tubes. Finally, the authors tested their developed broaching tool in a relevant industrial environment. The tool not only fulfills the dimensional machining requirements but also solves the present chip evacuation problem in a unique way. It enables free cutting through the whole operation and creates continuous straight chips with no need for chip breakers. Consequently, the timely cleaning step, required in traditional broaching, can be eliminated, which reduces the lead time significantly. Furthermore, the set of materials allows dry broaching. Coolant is not necessary. This leads to less waste, a cleaner production line, and avoids damage through aggressive liquids. Lastly, their design ensures that no loss of dimension occurs when resharpening the tool
The Italian Resistance: historical junctures and new perspectives
Full text linkThis introduction to this special issue of Modern Italy explores how the emphasis on fascism in recent scholarship and public discourse risks its mythification and cultural rehabilitation, and urges a rebalancing of historiography to highlight the pivotal role of the Italian Resistance in shaping Italy's democratic identity. Marking the eightieth anniversary of Italy's liberation and the thirtieth anniversary of Modern Italy, the issue examines lesser-known aspects of the Resistance, such as marginal groups, gendered experiences and transnational perspectives. Contributions include studies on Roma Resistance fighters, the Catholic underground press, American soldiers of Italian descent, and women in the Liberal Party. The articles emphasise the liminality and creative potential of the Resistance as a transformative period that redefined political and cultural identities
Fast development cycle for the design of industrial grippers
No full textRecent trends, such as Supply Chain agility, just in time delivery, and mass customization of products, are pushing automated production processes in Industry 4.0 towards increasing flexibility. Although the entire set of devices is already on the market and can be selected according to the needs, the element that regularly has to be redesigned is the robotic end effector, mainly a gripper. Therefore, we established a Fast Development Cycle to accelerate the design and test process of new industrial grasping devices. The cycle consists of the three main steps: Build, Test, and Learn. The most fundamental aspect of the methodology is to decompose a gripper idea into its essential uncoupled constituents and convert it into a gripper pretotype that is solely oriented to validate its basic principles. This procedure ensures a quick initial building phase and allows to enter testing early. Test results are used to evaluate the initial idea, to enhance knowledge and to create the input for the next turn of the cycle. During each turn the design evolves further while reducing uncertainties. Contrary to traditional product development, this method enables to test the feasibility of a device in the earliest possible stage with the least possible amount of time and money. The single steps of the methodology are illustrated in this paper in detail based on real cases from industry. The successful development of industrial grippers from these real cases through the Fast Development Cycle demonstrates its applicability. Instead of optimizing complex systems, the methodology generates simple solutions with a high potential for cost savings in the design and production process of the devices themselves and during their operation in automated production processes in several industries. The methodology applies regardless of the underlying physical principles and encounters the use of TRLs as KPIs to measure technology maturity
Simple synthesis of the two enantiomeric forms of erythro-octane- 2,3-diol and 2-hydroxyoctan-3-one, proposed pheromones of Xylotrechus pyrrhoderus
No full textAssessing text-image patent datasets with text-based metrics for engineering design applications
No full textImages provide concise representations of design artifacts and emerge as the primary mode of communication among innovators, engineers, and designers. The advanced of Artificial Intelligence tools which integrates image and textual information can significantly support the Engineering Design process. In this paper we create 5 different datasets combining both images and text of patents and we develop a set of text-based metrics to assess the quality of text for multimodal applications. Finally, we discuss the challenges arising in the development of multimodal patent datasets
A simple and fast method for Named Entity context extraction from patents
No full textThe process of extracting relevant technical information from patents or technical literature is as valuable as it is challenging. It deals with highly relevant information extraction from a corpus of documents with particular structure, and a mix of technical and legal jargon. Patents are the wider free source of technical information where homogeneous entities can be found. From a technical perspective the approaches refer to Named Entity Recognition (NER) and make use of Machine Learning techniques for Natural Language Processing (NLP). However, due to the large amount of data, to the complexity of the lexicon, the peculiarity of the structure and the scarcity of the examples to be used to feed the machine learning system, new approaches should be studied. NER methods are increasing their performances in many contexts, but a gap still exists when dealing with technical documentation. The aim of this work is to create an automatic training sets for NER systems by exploiting the nature and structure of patents, an open and massive source of technical documentation. In particular, we focus on collecting the context where users of the invention appear within patents. We then measure to which extent we achieve our goal and discuss how much our method is generalizable to other entities and documents
How to Discover the Prerequisites in Education and Training Courses: A Data-driven Method to Design Learning Path
No full textThe new method, named Prerequisite Discovery, can redesign education and training courses with most in-demand competences in the labour market. The method, exploiting text mining
techniques and machine learning algorithms, identifies and predicts prerequisite relations to
support the design of syllabi and learning paths. The most in-demand competences for the
labour market are used for building learning paths based on domain specific textbooks,
towards a more effective and efficient learning experience. A general reference framework for
competences (ESCO) enables the applications in different industrial areas. A Case Study in
the Project Management field is presented and discussed
A DATA DRIVEN TOOL TO SUPPORT DESIGN TEAM COMPOSITION MEASURING SKILLS DIVERSITY
No full textTeam composition in Project Based Learning is the first task for the class and has a great impact on the learning experience. Anyway, little space is dedicated in literature about team composition, considering their personal inclinations towards design tasks. For these reasons we propose a tool that aims to map the design skills of students to optimise team composition. The tool is based on a questionnaire grounded in the design theory and aims at measuring the willingness of students at performing certain design tasks. The results of the questionnaires are analysed using Principal Component Analysis to normalise each students' answers to the whole class, and to show the distribution of students in the space of engineering design skills. We present the design process of the tool, and a first experimentation on two classes of master's degree students in Management Engineering and Data Science, testing the tool on a total of 72 students. The results are promising and demonstrate the robusteness of the questionnaire and of the analytical method. Also, we propose next steps for our research activity, calling for other researchers to test our method in different contexts. © The Author(s), 2023. Published by Cambridge University Press
Technical Sentiment Analysis. Measuring Advantages and Drawbacks of New Products Using Social Media
No full textThe paper contributes to the literature on sentiment analysis by introducing a new knowledge-based lexicon. The lexicon, based on fundamental research and systematic practice in Engineering Design, describes the Advantages or Drawbacks (Disadvantages) of products as an effect of the interaction between artifacts and users. The paper extracts data from Twitter that report consumer conversations after the launch of new products in the videogame industry. It compares the results of a traditional sentiment analysis with the results filtered using the lexicon. We observe a drop in the number of positive tweets but a sharp increase in the informativeness of consumers’ opinions. Comments filtered using the lexicon offer a much more useful basis for understanding customers and designing new products. The paper develops several areas of potential applicability of the methodology
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