Being at the interface of the geosphere, the biosphere, and the atmosphere makes the soil a particularly challenging object. Nevertheless, its importance in ecological and environmental domains should encourage researchers to make use of new technologies, like 3D printing, to improve their comprehension of soils. With 3D printing we can build up objects by adding materials layer-by-layer based on a three-dimensional model, producing almost any geometrically complex shape or feature in a wide range of materials. Here we present the major challenges and opportunities of 3D printing for its application into soil science. We show that despite the remarkable achievements in 3D printing development during the past few years, it is still under-used in the field of soil science. Besides the 3D printing technology uses considering the soil as a source of mineral raw materials, or as the basis for the development of technical infrastructure, new researches highlight the functioning of the soil itself as an ecological compartment. Indeed, one of the most important challenges for the application of 3D printing in this area is the accurate modeling and replication of the soil structure and composition. This would require 3D-printed objects to be made of biocompatible yet chemically and mechanically stable materials manufactured under controlled conditions, which can mimic the many interactions occurring at this scale. Having 3D-printed objects with strict and controlled composition and structure could help academics and researchers to conduct reproducible experiments and gain a better understanding of the parameters controlling soil ecology and functioning. This opens a new way to broader utilization of 3D printing in soil science in the near future.

This work proposes a systematic approach for the design of formulated products incorporating consumer assessment and heuristic knowledge. The methodology is divided into two main phases: Consumer assessment and product realization. In the first part, product attributes valued by consumers and their interactions are identified through usability tests performed on a reference product, and fuzzy integral analysis. In the second phase, alternative product formulations are generated using a mixed-integer optimization approach, which incorporates heuristic rules regarding the choice of ingredients and their amounts. The results from the consumer assessment phase are transformed into additional heuristics and incorporated into the design. Different alternative formulations are generated at a lab-scale, by using two commercial skin moisturizers as references. Those formulations that included additional heuristics are shown to be more similar to the references. As a result, the incorporation of consumer preferences significantly reduced the time and resources spent on the design process.