The sustainability evaluation of engineering processes and structures is a multifaceted challenge requiring the integration of diverse and often conflicting criteria. To address this challenge, Multi-Criteria Decision-Making (MCDM) methods have emerged as effective tools. However, the selection of the most suitable MCDM approach for problems involving multiple criteria is critical to ensuring robust, reliable, and actionable outcomes. Equally significant is the choice of a proper normalization technique, which plays a pivotal role in determining the robustness and reliability of the results. This study investigates the impact of common MCDM tools on the decision-making process concerning diverse aspects of sustainability. It also examines how different normalization methods influence the final outcomes. Sustainability in this context is understood as a trade-off among five key dimensions: performance, environmental impact, economic impact, social impact, and circularity. The outcome of the MCDM process is represented by an aggregated metric, referred to as the Sustainability Index (SI). This index offers a comprehensive and robust framework for evaluating sustainability and facilitating decision-making when conflicting criteria are present. To assess the effects of implementing different MCDM and normalization choices on the sustainability assessment, a dataset from the aviation sector is employed. Specifically, a typical aircraft component is analyzed as a case study for holistic sustainability assessment, utilizing data that represent the various dimensions of sustainability mentioned above, for this component. Additionally, the study investigates the influence of initial data variations and weight variations within the MCDM process on the results. The results indicate that, overall, the different MCDM and normalization methods lead to similar outcomes when applied to the design alternatives. However, a deeper dive into the results reveals that the weighted sum method, when paired with min-max normalization, appears to be more appropriate, based on the use case involved for the present investigation, due to its robustness regarding small variations in the initial data and its sensitivity to large ones. This research underscores the critical importance of selecting appropriate MCDM tools and normalization methods to enhance transparency, robustness, reliability, and consistency of sustainability assessments within a holistic framework.

The current prevailing trend in design across key sectors prioritizes eco-design, emphasizing considerations of environmental aspects in the design process. The present work aims to take a significant leap forward by proposing a design process where sustainability serves as the primary driving force. In this context, sustainability is positioned as a fundamental component to be integrated into the initial stages of design, introducing innovative multidisciplinary criteria that redefine the design paradigm. Within this framework, sustainability is characterized using a comprehensive and quantifiable index encompassing technological, environmental, economic, and circular economy dimensions. To demonstrate the practical application of sustainability as the primary criterion in designing mechanical components, a parametrized finite element model of a composite plate is utilized, integrating both pristine and recycled fibers. Subsequently, a demonstrator derived from the aviation industry—specifically, a hat stiffener—is employed as a validation platform for the proposed methodology, ensuring alignment with the demonstrator’s specific requirements. Various representative trade-off scenarios are implemented to guide engineers’ decision-making during the conceptual design phase. Additionally, the robustness of the aforementioned methodology is thoroughly assessed concerning changes in the priority assigned to each sustainability criterion and its sensitivity to variations in the initial data. The significance of the proposed design methodology lies in its effectiveness in addressing the complex challenges presented by conflicting sustainability objectives. Furthermore, its adaptability positions it for potential application across various sectors, offering a transformative approach to sustainable engineering practices.

Integration of functional elements into fibre-reinforced host structures provides the possibility for in situ monitoring of the structural integrity of critical components. In this study, a vibration-based monitoring function has been developed that allows the structural integrity identification of critical components. For this purpose, signal analysis algorithms were developed to enable the estimation of damage-dependent modal damping. The analysed smart structure was a carbon fibre–reinforced epoxy composite plate with an integrated actuating/sensing system. The local material damping is a parameter especially sensitive to different failure modes of composites. In order to characterise the changes of this parameter resulting from impact events, dynamical mechanical analysis on intact and damaged specimens made of the composite material was conducted. Based on the dynamical mechanical analysis results, a finite element model of the structure was developed. Then, modal damping ratios for different sizes and locations of damaged regions were numerically determined, and a relation between modal damping and damage-dependent local damping was identified. The deterministic decision trees describing the reverse relationship between online-measured modal damping and damage condition were determined. That was accomplished through the application of information entropy-based data-mining algorithms to the numerically generated learning dataset obtained using the developed finite element model.