Despite the current boost in the use of electric vehicles to reduce the automotive sector’s footprint, combustion vehicles are and will be present in our cities in both the immediate and long term. In this sense, catalytic converters, which are exhaust gas post-treatment systems for vehicle emission control, are critical for complying with increasingly stringent environmental regulations. This work proposes a systematic review to identify the most relevant knowledge regarding the parameters (materials, geometries, and engine conditions), conditions (cold start, oxygen storage, and deactivation), and mathematical models to consider in the design of catalytic converters. The Scopus database contains 283 records related to this review’s objective. After applying the inclusion and exclusion criteria, 65 reports were retrieved for evaluation. A table was created to present the results and prepare this manuscript. The evaluation revealed that the following topics were active: the study of non-noble catalyst materials, as well as new substrate materials and geometries, for designing more compact and cost-effective catalytic converters; the development of strategies to improve conversion during cold starts; and the development of accurate and fast estimation models.

Incremental sheet forming (ISF) is gaining attention as a low cost prototyping and small batch production solution to obtain 3D components. In ISF, the forming force is key to define an adequate setup, avoiding damage and reducing wear, as well as to determine the energy consumption and the final shape of the part. Although there are several analytical, experimental and numerical approaches to estimate the axial forming force for metal sheets, further efforts must be done to extend the study to polymers. This work presents two procedures for predicting axial force in Single Point Incremental Forming (SPIF) of polymer sheets. Particularly, a numerical model based on the Finite Element Model (FEM), which considers a hyperelastic-plastic constitutive equation, and a simple semi-analytical model that extends the known specific energy concept used in machining. A set of experimental tests was used to validate the numerical model, and to determine the specific energy for two polymer sheets of polycarbonate (PC) and polyvinyl chloride (PVC). The approaches provide results in good agreement with additional real examples. Moreover, the numerical model is useful for accurately predicting temperature and thickness.

Build time is a key issue in additive manufacturing, but even nowadays, its accurate estimation is challenging. This work proposes a build time estimation method for fused filament fabrication (FFF) based on an average printing speed model. It captures the printer kinematics by fitting printing speed measurements for different interpolation segment lengths and changes of direction along the printing path. Unlike analytical approaches, printer users do not need to know the printer kinematics parameters such as maximum speed and acceleration or how the printer movement is programmed to obtain an accurate estimation. To build the proposed model, few measurements are needed. Two approaches are proposed: a fitting procedure via linear and power approximations, and a Coons patch. The procedure was applied to three desktop FFF printers, and different infill patterns and part shapes were tested. The proposed method provides a robust and accurate estimation with a maximum relative error below 8.5%.