Vertical Farming Monitoring: How Does It Work and How Much Does It Cost?

Climate change, resource scarcity, and a growing world population are some of the problems facing traditional agriculture. For this reason, new cultivation systems are emerging, such as vertical farming. This is based on indoor cultivation, which is not affected by climatic conditions. However, vertical farming requires higher consumption of water and light, since in traditional agriculture those resources are free. Vertical cultivation requires the use of new technologies and sensors to reduce water and energy consumption and increase its efficiency. The sensorization of these systems makes it possible to monitor and evaluate their performance in real time. In addition, vertical farming faces economic uncertainty since its profitability has not been studied in depth. This article studies the most important variables when monitoring a vertical farming system and proposes the sensors to be used in the data acquisition system. In addition, this study presents a cost model for the installation of this type of system. This cost model is applied to a case study to evaluate the profitability of installing this type of infrastructure. The results obtained suggest that the investment made in VF installations could be profitable in a period of three to five years.

Cost Model Framework for Pieces Additively Manufactured in Fused Deposition Modeling for Low to Medium Batches.

The cost impact of implementing additive manufacturing (AM) in the fabrication process is nowadays an issue. The scope of this research is to establish a cost model framework that can predict the cost of a piece in a low to medium batch considering fused deposition modeling (FDM) printing parameters. Every enterprise wants to increase its internal capabilities for tools, prototypes, and the production of pieces for maintenance purposes. FDM is an AM technology increasingly used in aerospace, automotive, and many other sectors. The research methodology consists of developing a cost model based on the extrusion-type AM process for any given machine characteristics and comparing the cost per piece based on diverse lot sizes and raw materials. Two test cases were simulated to show the usefulness of the cost model, one with a conventional polymer material (acrylonitrile butadiene styrene) and another with a high-performance material (polyetheretherketone); materials with very different costs, machine technical requirements, and energy consumption. The framework could be used to predict the best machine size and material type that could be suitable for a certain situation. The strength of our approach lies in the energy cost calculus, which is dependent on machine capabilities and size.