Personalization, production on-demand, and flexible manufacture facilities are growing within the European apparel sector, supported by national and regional public policy. These developments seem to embody a much waited “paradigm shift” in the fashion industry; a shift from global to local scale, from quantity to quality and from standard products to personalized services. Such values, however, are far from new, and scholars have already pointed out the similarities between emerging and pre-industrial systems of production and consumption. This article argues that in order to understand current developments in historical context, we should return to the process of industrialization of the apparel industry during the turn from the 19th to the 20th C, taking into account aspects of production as much as mediation and consumption. With this aim in mind, the article traces the rise of ready-made garments in the Netherlands and northwest Europe, and the associated decline in custom- and home-made garments in the region. Although available statistical data is insufficient to accurately map these phenomena, secondary sources suggest that both processes were not simultaneous and therefore there was not a straightforward substitution of custom- and home-made clothing by ready-mades. While availability and trade of mass-produced ready-mades was escalating since the early 19th C, it was not until mid 20th C that custom- and home-made clothing declined among the middle class. In this study, such a gap is explained by a steady increase in the amount of clothes acquired per person: an expanding culture of consumption during the period under consideration may have enabled these different systems to flourish all together. A parallelism of the findings above with current developments suggests that we should not regard emergent industrial formats as substitutionary of established ones, but as complementary. We may then reevaluate to what extent does the rise of the flexible factory enable a “revolution”, a shift from a problematic present to a contrasting and desirable future. This historical overview indicates that, on the contrary, emerging product-service-systems manufacturing personalized garments on-demand must be considered in relation to – and in coexistence with- traditional industrial models.
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Author supplied: In a production environment where different products are being made in parallel, the path planning for every product can be different. The model proposed in this paper is based on a production environment where the production machines are placed in a grid. A software entity, called product agent, is responsible for the manufacturing of a single product. The product agent will plan a path along the production machines needed for that specific product. In this paper, an optimization is proposed that will reduce the amount of transport between the production machines. The effect of two factors that influence the possibilities for reductions is shown in a simulation, using the proposed optimization scheme. These two factors are the redundancy of production steps in the grid and the
Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.
Artificial Intelligence (AI) wordt realiteit. Slimme ICT-producten die diensten op maat leveren accelereren de digitalisering van de maatschappij. De grote innovaties van de komende jaren –zelfrijdende auto’s, spraakgestuurde virtuele assistenten, autodiagnose systemen, robots die autonoom complexe taken uitvoeren – zijn datagedreven en hebben een AI-component. Dit gaat de rol van professionals in alle domeinen, gezondheidzorg, bouwsector, financiële dienstverlening, maakindustrie, journalistiek, rechtspraak, etc., raken. ICT is niet meer volgend en ondersteunend (een ‘enabling’ technologie), maar de motor die de transformatie van de samenleving in gang zet. Grote bedrijven, overheidsinstanties, het MKB, en de vele startups in de Brainport regio zijn innovatieve datagedreven scenario’s volop aan het verkennen. Dit wordt nog eens versterkt door de democratisering van AI; machine learning en deep learning algoritmes zijn beschikbaar zowel in open source software als in Cloud oplossingen en zijn daarmee toegankelijk voor iedereen. Data science wordt ‘applied’ en verschuift van een PhD specialisme naar een HBO-vaardigheid. Het stadium waarin veel bedrijven nu verkeren is te omschrijven als: “Help, mijn AI-pilot is succesvol. Wat nu?” Deze aanvraag richt zich op het succesvol implementeren van AI binnen de context van softwareontwikkeling. De onderzoeksvraag van dit voorstel is: “Hoe kunnen we state-of-the-art data science methoden en technieken waardevol en verantwoord toepassen ten behoeve van deze slimme lerende ICT-producten?” De postdoc gaat fungeren als een linking pin tussen alle onderzoeksprojecten en opdrachten waarbij studenten ICT-producten met AI (machine learning, deep learning) ontwikkelen voor opdrachtgevers uit de praktijk. Door mee te kijken en mee te denken met de studenten kan de postdoc overzicht en inzicht creëren over alle cases heen. Als er overzicht is kan er daarna ook gestuurd worden op de uit te voeren cases om verschillende deelaspecten samen met de studenten te onderzoeken. Deliverables zijn rapporten, guidelines en frameworks voor praktijk en onderwijs, peer-reviewed artikelen en kennisdelingsevents.
Sea Lettuce, Ulva spp. is a versatile and edible green seaweed. Ulva spp is high in protein, carbohydrates and lipids (respectively 7%-33%; 33%-62% and 1%-3% on dry weight base [1, 2]) but variation in these components is high. Ulva has the potential to produce up to 45 tons DM/ha/year but 15 tons DM/ha/year is more realistic.[3, 4] This makes Ulva a possible valuable resource for food and other applications. Sea Lettuce is either harvested wild or cultivated in onshore land based aquaculture systems. Ulva onshore aquaculture is at present implemented only on a few locations in Europe on commercial scale because of limited knowledge about Ulva biology and its optimal cultivation systems but also because of its unfamiliarity to businesses and consumers. The objective of this project is to improve Ulva onshore aquaculture by selecting Ulva seed material, optimizing growth and biomass production by applying ecophysiological strategies for nutrient, temperature, microbiome and light management, by optimizing pond systems eg. attached versus free floating production and eventually protoype product development for feed, food and cosmetics.
