Smart Composite Mechanical Demanufacturing Processes

Recycling of Glass Fibers Reinforced Plastics (GFRP) can be preferentially performed through mechanical processes due to the low cost of virgin fibers. Because of the poorer mechanical properties after comminution, the most interesting solution to reuse this material is a cross-sectorial approach, in which particles obtained through shredding of products from one sector are used in another sector. To allow this, a fine control on the particles dimension is fundamental, together with the minimization of operational costs. In this chapter, after a deep analysis on the available size reduction technologies and a preliminary feasibility analysis on the products involved in Use-Case 1 of the FiberEUse project, a 2-step architecture to optimize these two characteristics is presented. The models for both steps are shown and the developed solutions is applied to the End-of-Life products, demonstrating the potential of this approach, leading to optimal dimension of the particle with operational costs lower than both virgin fibers and disposal costs

Characterization of fine metal particles using hyperspectral imaging in automatic WEEE recycling systems

Waste from electric and electronic equipment (WEEE) represents the fastest growing waste stream in EU. The large amount and the high variability of electric and electronic products introduced every year in the market make the WEEE recycling process a complex task, especially considering that mechanical processes currently used by recycling companies are not flexible enough. In this context, hyperspectral imaging systems (HSI) can represent an enabling technology able to improve the recycling rates and the quality of the output products. This study shows the preliminary results achieved using a HSI technology in a WEEE recycling pilot plant, for the characterization of fine metal particles derived from WEEE shredding

Characterization of fine metal particles derived from shredded WEEE using a hyperspectral image system: Preliminary results

Waste of electric and electronic equipment (WEEE) is the fastest-growing waste stream in Europe. The large amount of electric and electronic products introduced every year in the market makes WEEE disposal a relevant problem. On the other hand, the high abundance of key metals included in WEEE has increased the industrial interest in WEEE recycling. However, the high variability of materials used to produce electric and electronic equipment makes key metalsâ recovery a complex task: the separation process requires flexible systems, which are not currently implemented in recycling plants. In this context, hyperspectral sensors and imaging systems represent a suitable technology to improve WEEE recycling rates and the quality of the output products. This work introduces the preliminary tests using a hyperspectral system, integrated in an automatic WEEE recycling pilot plant, for the characterization of mixtures of fine particles derived from WEEE shredding. Several combinations of classification algorithms and techniques for signal enhancement of reflectance spectra were implemented and compared. The methodology introduced in this study has shown characterization accuracies greater than 95%

Disassembly of Large Composite-Rich Installations

Considering the demanufacturing of large infrastructures (as wind blades and aircrafts) rich in composite materials, the most impacting step in terms of costs is disassembly. Different routes could be followed for dismantling and transportation and several factors influence the final result (as the technology used, the logistic and the administrative issues). For this reason, it is fundamental to understand which solution has to be followed to reduce the impact of decommissioning on the overall recycling and reusing cost. This work, after the formalization of the different possible disassembly scenarios, proposes a Decision Support System (DSS) for disassembly of large composite-rich installations, that has been designed and implemented for the identification of the most promising disassembly strategy, according to the process costs minimization. The mathematical models constituting the core of this tool are detailed and the DSS is applied to disassembly of onshore wind blades, underling the importance of similar systems to optimize demanufacturing costs

Ore minerals textural characterization by hyperspectral imaging

The utilization of hyperspectral detection devices, for natural resources mapping/exploitation through remote sensing techniques, dates back to the early 1970s. From the first devices utilizing a one-dimensional profile spectrometer, HyperSpectral Imaging (HSI) devices have been developed. Thus, from specific-customized devices, originally developed by Governmental Agencies (e.g. NASA, specialized research labs, etc.), a lot of HSI based equipment are today available at commercial level. Parallel to this huge increase of hyperspectral systems development/manufacturing, addressed to airborne application, a strong increase also occurred in developing HSI based devices for "ground" utilization that is sensing units able to play inside a laboratory, a processing plant and/or in an open field. Thanks to this diffusion more and more applications have been developed and tested in this last years also in the materials sectors. Such an approach, when successful, is quite challenging being usually reliable, robust and characterised by lower costs if compared with those usually associated to commonly applied analytical off- and/or on-line analytical approaches. In this paper such an approach is presented with reference to ore minerals characterization. According to the different phases and stages of ore minerals and products characterization, and starting from the analyses of the detected hyperspectral firms, it is possible to derive useful information about mineral flow stream properties and their physical-chemical attributes. This last aspect can be utilized to define innovative process mineralogy strategies and to implement on-line procedures at processing level. The present study discusses the effects related to the adoption of different hardware configurations, the utilization of different logics to perform the analysis and the selection of different algorithms according to the different characterization, inspection and quality control actions to apply

Innovative hyperspectral imaging (HSI) based techniques applied to end-of-life concrete drill core characterization for optimal dismantling and materials recovery

The reduction of EOL concrete disposal in landfills, together with a lower exploitation of primary raw materials, generates a strong interest to develop, set-up and apply innovative technologies to maximize Construction and Demolition Waste (C&DW) conversion into useful secondary raw materials. Such a goal can be reached starting from a punctual in-situ efficient characterization of the objects to dismantle in order to develop demolition actions aimed to set up innovative mechanical-physical processes to recover the different materials and products to recycle. In this paper an innovative recycling-oriented characterization strategy based on HyperSpectral Imaging (HSI) is described in order to identify aggregates and mortar in drill core samples from end-of-life concrete. To reach this goal, concrete drill cores from a demolition site were systematically investigated by HSI in the short wave infrared field (1000-2500 nm). Results obtained by the adoption of the HSI approach showed as this technology can be successfully applied to analyze quality and characteristics of C& DW before dismantling and as final product to re-utilise after demolition-milling-classification actions. The proposed technique and the related recognition logics, through the spectral signature detection of finite physical domains (i.e. concrete slice and/or particle) of different nature and composition, allows; i) to develop characterization procedures able to quantitatively assess end-of-life concrete compositional/textural characteristics and ii) to set up innovative sorting strategies to qualify the different materials constituting drill core samples

Quality assessment of demolition waste using innovative sensing devices and architectures based on hyperspectral imaging

The recycling of end-of-life concrete into new concrete is one of the most interesting options for reducing worldwide natural resources use and emissions associated with the building materials sector. The possibility to realize a larger re-use of silica aggregates from old concrete, strongly contributes to reduce environmental impact (reduced exploitation of natural resources, reduction of CO2 emissions, airborne dust production, etc.).To reach this goal, innovative processing techniques, as well as innovative sensing units and architectures have to be developed. In this perspective an analytical approach, based on hyperspectral sensing techniques, is proposed, discussed and critically evaluated in order to perform an automatic quality control assessment, finalized to maintain a high standard of concrete demolition waste, from the earliest stage of recycling to the further processing stages, according to the detected in-situ demolition waste characteristics. The paper deals with the analysis and the evaluation of the problems related to the integration of this approach with state-of-the-art demolition and building processes and procedures

2D-fractal based approach for fine particulate characterization: An application to limestone fillers

A full target oriented fine and ultrafine particles systems characterization represents an hard task to reach. Such a difficulty is mainly linked to the problems arising when, starting from a full analysis of single particles properties (i.e. size, shape, surface characteristics and density) a correlation with their behaviour in bulk has to be established. In this paper an innovative approach is proposed in order to detect and quantify the overall attributes of fine and ultrafine particles resulting from different processes and characterized by different particle characteristics. The proposed approach is based on: a 2D-fractal analysis of fine and ultrafine particles population acquired as digital images. This approach allows to perform a full measurement and control of fine particles structure and texture by evaluating statistical fractal parameters on the base of the topological assessment of the particles on a flat surface. The work was developed with the aim to develop and implement a reliable and simple tool to use for particulate products characterization and recognition able to correlate the characteristics of fine particles detected by the proposed logics and those usually extracted by using classic methods

Microscopic Investigations of the Effect of Ultrafine Particles on Cement Paste Properties

The utilization of fine and ultrafine particles for concrete manufacturing has received considerable attention in recent years. Interest has been more and more addressed towards the utilization of fine and ultrafine particulates products of natural origin and/or resulting from waste and industrial by-products, in order to reduce cement consumption, also reducing the environmental impact linked to its production. In this paper materials coming from two natural pozzolanic deposits in Italy have been utilized. Pozzolanic materials have been milled below 25 μm and the resulting products utilized, in different recipes, for the preparation of different blended cements. It was found as the addition of pozzolanic fine fractions: i) does not increase cement compressive strength, ii) flowability characteristics of slumps result higher than the reference mortar sample and, finally, iii) blended mortars compressive strength is comparable with that of pozzolanic blended cement