Since automotive manufacturers of original equipment require high quality level of gaskets, it is mandatory that the gasket manufactures achieve a stability of production runs with minimized defects (zero-defect) and scraps amount. Therefore, a suitable process control for rubber injection molding able to take into account process fluctuations has to be developed. From the point of view of sustainability, rubber waste doesn’t degrade and remains for a long period of time in the environment. Therefore, to increase the sustainability of rubber products, the first strategy is to reduce the generated waste. Reducing rubber waste during production involves not only material savings, but also energy savings. The principal aim of this thesis is to develop a method for process optimization with the purpose to reduce scraps amount, and to increase the sustainability of rubber products by recycling the waste materials as well. The existing approaches reported in the literature are manly focused both on the technology improvement of conventional laboratory instruments such as RPA and capillary rheometer, and also on the technology improvement of the injection molding machine, used as a laboratory rheometer (e.g. slit die rheometry). Although specific sensors were employed directly in the injection molding machine to provide an online monitoring of pressure and temperature, however these devices were too susceptible to handling, wear and fouling especially if installed to monitor continuously these signals in daily industrial operation. Therefore, this research activity aims to develop an integrated approach, merging laboratory data and process data, useful to improve the injection molding process control, and to reduce the defects and scraps amount during the manufacturing process of rubber parts by injection molding. The proposed method is based on a very fast online monitoring of the surface rubber temperature (shear heat-ing temperature, TSH) by an infrared thermal camera, pointed toward the rubber leaving the extruder barrel of the injection molding machine. This measured temperature led to the calculation of a technological parameter designated shear heating pa-rameter, ηSH, which also takes into account physical material properties (density and specific heat capacity) and process conditions (screw L/D ratio). Therefore, monitoring also ηSH allowed to get an added value in terms of quantitative and precise indication of the quality of molded part. Furthermore, log ηSH values of a production run, combined with ML values, give indication of the “real output” of the injection molding process by comparison of this data with a well-established roadmap, obtained from stable production runs of different rubber compounds and process con-ditions. Moreover, this integrated approach (operating roadmap), has the advantage of being fast and provides in-formation about the stability of the process, while it is running, well before completing the production run, by optimizing the injection molding process for rubbers where knowledge about thermal history is lacking. The integrated approach should be as general as possible, potentially applicable to any rubber compound pro-cessable by injection molding. It was therefore validated not only for industrial compounds, but also for two types of innovative compounds, characterized by a high level of sustainability: recycled rubbers coming from devulcanization process, such as fluorocarbon rubber (FKM) on one side, and acrylonitrile butadiene (NBR) rubber compounds containing electric arc furnace (EAF) slag (a by-product of steel industry) as reinforcing filler on the other side. Finally, the research activity is also focused on the possibility to use the shear heating temperature, TSH, in the setup of computer-aided engineering simulations (CAE) useful for mold design and injection molding process optimization.