Foamed components provide the industry with numerous advantages from production through to the life cycle of plastic components. However, especially against the backdrop of climate change, the demand for sustainability drastically increases. To keep up with these requirements, polymer-processing technologies have to be refined constantly. In this work, an automation approach for the reduction of back pressure during an injection foam molding process is presented. Our innovative yet simple methodology based on the compressibility of polymer-gas-mixtures was applied to detect an undissolved gas phase at insufficient back pressures. Iterative execution of linear regression analysis facilitated the determination of the least necessary pressure during production. The resulting optimized pressure conditions inside the barrel allowed for a resource-saving process. Increased plasticizing capacity, reduced torque, decreased cavity pressures and lower necessary pressures in the gas supply chain are examples. The components benefited from increased mechanical bending properties while simultaneously exhibiting lower densities. From an economic point of view, the largest advantages of optimized pressures are reduced wear and lower energy/power demand. This study provides a further step towards fully autonomous production and process optimization and combines ideas from industry 4.0 as well as sustainability.