When products are no longer suitable for reuse, repair or refurbishment, they are discarded and recycled, often losing a lot of value (downcycling). Repurpose is a strategy that gives discarded products or obsolete parts a new, high-quality purpose, also known as upcycling. With Repurpose, the value added to the material in the shaping production process or during the use phase is not lost, as is the case with Recycling. For example, with Repurpose, the unique shape, color or composition of an object is preserved in a new product. Repurpose is therefore higher on the circularity ladder than Recycling.But how do you do that? Designing and producing from an existing product or part is challenging due to, among other things, variation in quality and limited or temporary availability. But it also offers opportunities because you can use unique properties or the origin of a product.During the DDW the AUAS showcases the results of the research project Repurpose Driven Design & Manufacturing, and informs and inspires the audience to apply Repurpose in their designs.
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A comparison between caring communities in Wedde (Groningen) and a rural community in Northwestern Germany. Motives, setbacks and changes for two small rural communities where citizens take charge of the care in their community
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The NDT methods currently used in aviation MRO are predominantly labour-intensive and time-consuming processes performed by human operators throughout the lifespan of an aircraft. These techniques are time-consuming, require perpetual training and are highly dependent on the operator's skills. Thus, there is a growing need for more efficient, automated, and accurate NDT tools that will be able to provide faster and less labour-intensive assessments. This study presents a novel, non-contact, automated NDT scanning system under development, which aims to reduce the inspection time significantly. The proposed technique uses a non-contact, Lamb wave-based approach. A further essential step during the process is to use an automated positioning system. Thickness mapping and defect detection in metal and composite structures have been performed. A local thickness map in the order of 1 mm has been obtained through a fast-scanning process with comparable resolution to conventional inspection techniques. Overall, it is currently concluded that the proposed NDT scanner is a promising tool that potentially can reduce the inspection time while also having the potential to automate the damage assessment resulting in more efficient MRO inspection processes.
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Currently, many novel innovative materials and manufacturing methods are developed in order to help businesses for improving their performance, developing new products, and also implement more sustainability into their current processes. For this purpose, additive manufacturing (AM) technology has been very successful in the fabrication of complex shape products, that cannot be manufactured by conventional approaches, and also using novel high-performance materials with more sustainable aspects. The application of bioplastics and biopolymers is growing fast in the 3D printing industry. Since they are good alternatives to petrochemical products that have negative impacts on environments, therefore, many research studies have been exploring and developing new biopolymers and 3D printing techniques for the fabrication of fully biobased products. In particular, 3D printing of smart biopolymers has attracted much attention due to the specific functionalities of the fabricated products. They have a unique ability to recover their original shape from a significant plastic deformation when a particular stimulus, like temperature, is applied. Therefore, the application of smart biopolymers in the 3D printing process gives an additional dimension (time) to this technology, called four-dimensional (4D) printing, and it highlights the promise for further development of 4D printing in the design and fabrication of smart structures and products. This performance in combination with specific complex designs, such as sandwich structures, allows the production of for example impact-resistant, stress-absorber panels, lightweight products for sporting goods, automotive, or many other applications. In this study, an experimental approach will be applied to fabricate a suitable biopolymer with a shape memory behavior and also investigate the impact of design and operational parameters on the functionality of 4D printed sandwich structures, especially, stress absorption rate and shape recovery behavior.
De veehouderij levert een bijdrage aan de emissie van methaan en ammoniak. Methaan is een broeikasgas en heeft een sterker opwarmingsimpact dan CO₂, terwijl ammoniak bijdraagt aan verzuring en fijnstofvorming. Overheden stellen steeds strengere milieuregels op voor de landbouw, zoals emissiereductiedoelstellingen en stikstofbeperkingen. Om de daadwerkelijke emissie in kaart te brengen is er behoefte aan schaalbare, accurate en robuuste sensoren, waarmee grootschalige monitoring mogelijk wordt. Hiermee kunnen ondernemers hun uitstoot inzichtelijk te maken en aantonen of ze voldoen aan regelgeving. Optische gassensoren zijn nauwkeurig en zeer geschikt voor het meten van lage concentraties. Echter, optische gassensoren die gebaseerd zijn op directe absorptiespectroscopietechnieken vereisen vaak krachtige laserbronnen, lange optische paden en een mechanisch stabiele gaskamer om nauwkeurige metingen uit te voeren. Hierdoor bevinden deze sensoren zich vooral in het wetenschappelijke domein, waar ze een nauwkeurigheid op het niveau van parts per billion (ppb) leveren, maar tegen een hoge kostprijs (5 - ¬30 kEuro per sensor). Door over te stappen naar meting op basis van faseverandering en dispersie, neemt de gevoeligheid met meerdere ordes van grootte toe. Dit vermindert de behoefte aan krachtige laserbronnen en lange optische paden. Hierdoor wordt miniaturisatie en daarmee kostenreductie van het optische systeem mogelijk, wat ook bijdraagt aan de stabiliteit en de produceerbaarheid. In dit project onderzoeken wij een optisch meetprincipe waarbij we aansluiten bij de toeleveringsketen van de data- en telecomsector, wat de potentie biedt voor schaalbare productie van deze sensor. Het beoogde resultaat is een prototype dat nauwkeurig en betaalbaar methaan of ammoniak concentraties kan meten in de veehouderij. De projectpartners dragen met hun expertise bij aan de realisatie van dit prototype: fotonica en spectroscopie in agri-food toepassingen (De Haagse Hogeschool), fotonische gas sensortechnologie en valorisatie (Spectrik), agri-food meet en adviesbureau gespecialiseerd in emissiemonitoring met een breed beroepspraktijk netwerk (Connecting Agri & Food).
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
