As designing with recycled materials is becoming indispensable in the context of a circular economy, we argue that understanding how recycled plastics are perceived by stakeholders involved in the front end of the design process, is essential to achieve successful application in practice, beyond the current concept of surrogates according to industry. Based on existing frameworks, 34 experiential scales with semantic opposites were used to evaluate samples of three exemplary recycled plastics by two main industrial stakeholders: 30 material engineers and 30 designers. We describe four analyses: (i) defining experiential material characteristics, (ii) significant differences between the materials, (iii) level of agreement of respondents, and (iv) similarities and differences between designers and engineers. We conclude that the three materials have different perceptual profiles or identities that can initiate future idea generation for high-quality applications. The study illustrates the potential of this evaluation method. We propose that designers can facilitate the valorization and adoption of these undervalued recycled materials, first by industry and ultimately by consumers as well.

The current COVID-19 pandemic has resulted in an immense and unforeseen increase in demand for personal protective equipment (PPE) for healthcare workers worldwide. Amongst other products, respirator masks are crucial to protect the users against transmission of the virus. Decontamination and reuse of the existing stock could be a solution to the shortage of new respirators. Based upon existing studies, it was found that (I) a solid quality control method is essential to test product reuse, (II) in-depth evaluation of the different parts of the filtering facepiece respirator (FFR) should be considered, and (III) communication of the reuse cycle is essential to take track of the amount of reuse, as this is limited to ensure quality. The goal of this paper is two-fold. First, we identify the impact of decontamination on the different parts of the FFRs and how the quality control should be performed. Two different types of FFRs are analysed within this paper, resulting in the recommendation of combining quantitative respirator mask fit testing with a thorough sensory evaluation of decontaminated FFRs to qualify them for reuse. Secondly, the possibilities of communication of this reuse to the eventual user are mapped through in-depth reasoning.

As sports garments are stretchable, different sizing tables are used than for retail clothing. However, customers measuring themselves leads to errors and unsatisfaction, since these customized branded garments cannot be returned. Using fitting sets avoids this, but this is not always feasible, especially in an online retail environment. Therefore, this research aims to use descriptive measures—parameters that do not require manual measuring because they are readily known by heart by almost any customer—to predict users’ body measurements, which can, thus, be used by customers to determine the size of their sports garment from a sizing chart. To validate if these input measures are sufficient to predict the correct size, three prediction methods are used and compared with baseline manual measurements. The methods are: (i) clothing size predictions from shape models with descriptive measures as inputs, (ii) clothing size predictions from a regression analysis, and (iii) clothing size predictions from a shape model based on extensive 3D scanned measurements as input. The conclusion is that a regression algorithm with, as input variables, the straightforward demographics of age, gender, stature, and weight is more accurate than the algorithm with the same inputs but with a shape model behind it. Moreover, chest and hip circumferences have an intraclass correlation coefficient rating above 0.9 and are, thus, suited for online retail of stretchable garments, such as cycling clothes. As validated by end-users, the regression predictions are shown to agree with preferred garment sizes of the participants, within the natural variation of personal preferences.