Bioprinting is a complex process, highly dependent on bioink properties (materials and cells) and environmental conditions (mainly temperature, humidity and CO2 concentration) during the bioprinting process. To guarantee proper cellular viability and an accurate geometry, it is mandatory to control all these factors. Despite internal factors, such as printing pressures, temperatures or speeds, being well-controlled in actual bioprinters, there is a lack in the controlling of external parameters, such as room temperature or humidity. In this sense, the objective of this work is to control the temperature and humidity of a new, atmospheric enclosure system for bioprinting. The control has been carried out with a decoupled proportional integral derivative (PID) controller that was designed, simulated and experimentally tested in order to ensure the proper operation of all its components. Finally, the PID controller can stabilize the atmospheric enclosure system temperature in 311 s and the humidity in 65 s, with an average error of 1.89% and 1.30%, respectively. In this sense, the proposed atmospheric enclosure system can reach and maintain the proper temperature and humidity values during post-printing and provide a pre-incubation environment that promotes stability, integrity and cell viability of the 3D bioprinted structures.
Inferring room-level use of domestic space heating from room temperature and humidity measurements using a deep, dilated convolutional network
