7 resultados para Waste footwear industry

em Universidad de Alicante


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The use of 3D imaging techniques has been early adopted in the footwear industry. In particular, 3D imaging could be used to aid commerce and improve the quality and sales of shoes. Footwear customization is an added value aimed not only to improve product quality, but also consumer comfort. Moreover, customisation implies a new business model that avoids the competition of mass production coming from new manufacturers settled mainly in Asian countries. However, footwear customisation implies a significant effort at different levels. In manufacturing, rapid and virtual prototyping is required; indeed the prototype is intended to become the final product. The whole design procedure must be validated using exclusively virtual techniques to ensure the feasibility of this process, since physical prototypes should be avoided. With regard to commerce, it would be desirable for the consumer to choose any model of shoes from a large 3D database and be able to try them on looking at a magic mirror. This would probably reduce costs and increase sales, since shops would not require storing every shoe model and the process of trying several models on would be easier and faster for the consumer. In this paper, new advances in 3D techniques coming from experience in cinema, TV and games are successfully applied to footwear. Firstly, the characteristics of a high-quality stereoscopic vision system for footwear are presented. Secondly, a system for the interaction with virtual footwear models based on 3D gloves is detailed. Finally, an augmented reality system (magic mirror) is presented, which is implemented with low-cost computational elements that allow a hypothetical customer to check in real time the goodness of a given virtual footwear model from an aesthetical point of view.

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Customizing shoe manufacturing is one of the great challenges in the footwear industry. It is a production model change where design adopts not only the main role, but also the main bottleneck. It is therefore necessary to accelerate this process by improving the accuracy of current methods. Rapid prototyping techniques are based on the reuse of manufactured footwear lasts so that they can be modified with CAD systems leading rapidly to new shoe models. In this work, we present a shoe last fast reconstruction method that fits current design and manufacturing processes. The method is based on the scanning of shoe last obtaining sections and establishing a fixed number of landmarks onto those sections to reconstruct the shoe last 3D surface. Automated landmark extraction is accomplished through the use of the self-organizing network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates up to 12 times the surface reconstruction and filtering processes used by the current shoe last design software. The proposed method offers higher accuracy compared with methods with similar efficiency as voxel grid.

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The footwear industry is a traditional craft sector, where technological advances are difficult to implement owing to the complexity of the processes being carried out, and the level of precision demanded by most of them. The shoe last joining operation is one clear example, where two halves from different lasts are put together, following a specifically traditional process, to create a new one. Existing surface joining techniques analysed in this paper are not well adapted to shoe last design and production processes, which makes their implementation in the industry difficult. This paper presents an alternative surface joining technique, inspired by the traditional work of lastmakers. This way, lastmakers will be able to easily adapt to the new tool and make the most out of their know-how. The technique is based on the use of curve networks that are created on the surfaces to be joined, instead of using discrete data. Finally, a series of joining tests are presented, in which real lasts were successfully joined using a commercial last design software. The method has shown to be valid, efficient, and feasible within the sector.

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L’histoire de la United Shoe Machinery Company (USMC) montre que la réalité ne s’adapte pas toujours aux simplifications de la théorie. Comme le signale l’économie de la fonctionnalité, la stratégie de l’entreprise de vendre l’usage plutôt que la machine fournit plusieurs avantages importants, mais elle a également contribué au fait que les usines de chaussures subissent une véritable dépendance technologique de cette compagnie et au fait que l’USMC soit parvenue à une domination monopolistique du marché. D’autre part, en remettant en cause les rudiments généraux de la théorie économique néoclassique, cette position de monopole n’a pas empêché que l’entreprise ait un fonctionnement efficace et ait facilité la modernisation technologique de l’industrie de la chaussure, aux États-Unis et dans d’autres pays.

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Fashion is a complex social and cultural phenomenon with strong economic implications. Historical analysis reveals that the mechanisms of creating and spreading fashion have not remained constant, but have varied according to social structures, forms of producing and distributing apparel and social media, while the level of influence of fashion on society has increased in line with economic development. This special issue of Investigaciones de Historia Económica-Economic History Research is dedicated to fashion as an economic phenomenon in the contemporary period. The four articles which make it up show the plurality of the subject areas, sources and methodological approaches in the current research on this topic.

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The construction industry is characterised by fragmentation and suffers from lack of collaboration, often adopting adversarial working practices to achieve deliverables. For the UK Government and construction industry, BIM is a game changer aiming to rectify this fragmentation and promote collaboration. However it has become clear that there is an essential need to have better controls and definitions of both data deliverables and data classification. Traditional methods and techniques for collating and inputting data have shown to be time consuming and provide little to improve or add value to the overall task of improving deliverables. Hence arose the need in the industry to develop a Digital Plan of Work (DPoW) toolkit that would aid the decision making process, providing the required control over the project workflows and data deliverables, and enabling better collaboration through transparency of need and delivery. The specification for the existing Digital Plan of Work (DPoW) was to be, an industry standard method of describing geometric, requirements and data deliveries at key stages of the project cycle, with the addition of a structured and standardised information classification system. However surveys and interviews conducted within this research indicate that the current DPoW resembles a digitised version of the pre-existing plans of work and does not push towards the data enriched decision-making abilities that advancements in technology now offer. A Digital Framework is not simply the digitisation of current or historic standard methods and procedures, it is a new intelligent driven digital system that uses new tools, processes, procedures and work flows to eradicate waste and increase efficiency. In addition to reporting on conducted surveys above, this research paper will present a theoretical investigation into usage of Intelligent Decision Support Systems within a digital plan of work framework. Furthermore this paper will present findings on the suitability to utilise advancements in intelligent decision-making system frameworks and Artificial Intelligence for a UK BIM Framework. This should form the foundations of decision-making for projects implemented at BIM level 2. The gap identified in this paper is that the current digital toolkit does not incorporate the intelligent characteristics available in other industries through advancements in technology and collation of vast amounts of data that a digital plan of work framework could have access to and begin to develop, learn and adapt for decision-making through the live interaction of project stakeholders.

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On a global level the population growth and increase of the middle class lead to a growing demand on material resources. The built environment has an enormous impact on this scarcity. In addition, a surplus of construction and demolition waste is a common problem. The construction industry claims to recycle 95% of this waste but this is in fact mainly downcycling. Towards the circular economy, the quality of reuse becomes of increasing importance. Buildings are material warehouses that can contribute to this high quality reuse. However, several aspects to achieve this are unknown and a need for more insight into the potential for high quality reuse of building materials exists. Therefore an instrument has been developed that determines the circularity of construction waste in order to maximise high quality reuse. The instrument is based on three principles: ‘product and material flows in the end of life phase’, ‘future value of secondary materials and products’ and ‘the success of repetition in a new life cycle’. These principles are further divided into a number of criteria to which values and weighting factors are assigned. A degree of circularity can then be determined as a percentage. A case study for a typical 70s building is carried out. For concrete, the circularity is increased from 25% to 50% by mapping out the potential for high quality reuse. During the development of the instrument it was clarified that some criteria are difficult to measure. Accurate and reliable data are limited and assumptions had to be made. To increase the reliability of the instrument, experts have reviewed the instrument several times. In the long-term, the instrument can be used as a tool for quantitative research to reduce the amount of construction and demolition waste and contribute to the reduction of raw material scarcity.