In the current world scenario, which is experiencing the arrival of new technologies, Industry 4.0, increased mobility and a pandemic environment, the achievement of sustainability demands proactive solutions. One of these actions includes the design of sustainable products. Several authors have studied the scientific discipline of Life Cycle Engineering (LCE), which encompasses environmental, social and economic dimensions. However, current LCE models have gaps, such as the need to incorporate a more holistic view, uncertainty and integrated analysis. In this context, the aim of this paper is to present a model to evaluate the technology sustainability (TS) dimension. The methodology of the present work involves a literature review, the development of a model with qualitative and quantitative data, and application in a case study. A structure was developed to include market, technical, and technology-scaling perspectives. The computational model uses hybrid Bayesian networks, based on probabilistic theory, and incorporates uncertainty using sustainability indicators. The model includes quantitative and qualitative variables derived from experts’ opinions. The results of applying the model to a real research project on manhole covers indicate that this analytical tool can support decision-making, allowing a new dimension to be incorporated into LCE analysis. Finally, the model allows LCE analysis to be applied in a variety of circumstances, such as strategy development or the selection of more sustainable products, as well as the evaluation of competing products.

In this study, GMAW and CMT welding technologies were evaluated in terms of their technological lifecycles based on their patent datasets together with the S-curve concept, and the joints were evaluated in terms of their welding characteristics. To predict the future trends for both technologies, different models based on the time-series and growth-curve methods were tested. From a process point of view, the results showed better performance and stability for the CMT process based on the heat input to the base material and the frequency of the short circuits. The temperature distribution in the sample revealed that the GMAW process delivers higher values and, consequently, greater heat transfer. Regarding the technological lifecycle, the analyses revealed that the CMT welding process, despite being recent, is already in its mature phase. Moreover, the GMAW welding process is positioned in the growth phase on the S-curve, indicating a possibility of advancement. The main findings indicated that through mathematical modelling, it is possible to predict, in a precise way, the inflection points and the maturity phases of each technology and chart their trends with expert opinions. The new perspectives for analysing maturity levels and welding characteristics presented herein will be essential for a broaden decision-making market process.

This study presents a comparative life cycle assessment (LCA) of two manufacturing scenarios for a camera housing: Powder Bed Fusion (PBF) using polyamide 12 (PA-12) and Computer Numeric Control (CNC) machining using aluminum, for a cradle-to-gate boundary. The selected impact categories were cumulative energy demand (CED) and global warming potential (GWP). The key findings indicate that the PA-12 PBF part outperformed the aluminum CNC machining one in terms of environmental and energy performance, showing a significant reduction of approximately 90% in equivalent carbon emissions and 84% in cumulative energy demand. Sensitivity analyses revealed that the PBF process was highly sensitive to changes in the proportion of virgin/recycled material for the printing process, variations in the life cycle inventory (LCI) data sources for PA-12 powder production, and changes in the transportation system for imported materials, as is the case for the main input in the process (PA-12 powder). Sensitivity analysis also showed less impact for the PBF camera housing even considering a lifespan of one-fifth that of the aluminum for the impact categories considered. However, it should be noted that this analysis did not include considerations for the usage and end-of-life phases, which may have significant contributions to the overall environmental impact.