Abstract
Sustainability and eco-efficiency have been researched in multiple scientific papers since the last years. However the literature is not so abundant when applying those concepts to industrial assembly processes. This paper presents an innovate methodology to optimize aerospace assembly processes. Authors propose the introduction of a new element, the eco-efficiency, along with the traditional criteria, cost and time, currently used for optimization. Using a large Aero-Structure as an industrial case of study, the methodology analyzes the eco-efficiency of an assembly process in connection with a Life Cycle Assessment (LCA) to compute the environmental impact. Results are shown in a dashboard along with the relevant Key Process Indicator (KPI) to help the engineers to select the best assembly process. © 2020, IFIP International Federation for Information Processing.

Abstract
A product development framework called LeanDfX has been conceived at INEGI, aiming at organizing the product design and development process benefitting from lean thinking and DfX paradigms. The design of the metallic structure for an automated guided vehicle (AGV) focusing on its static, dynamic and fatigue characteristics was a recent opportunity to enhance and further develop the framework through the consideration and integration into the process of several existing tools such as FMEA (failure mode and effect analysis), QFD (quality function deployment) or fuzzy logic. This paper describes the integration of those tools in the LeanDfX framework and an application to the design of an AGV structure. The methodology presented involves systematic consideration of a substantial number of design requirements and more detailed product specification characterization. Such a number might be seen as delaying the development process, but the present case study showed that the inverse was true, thanks to the structured systematic approach and timely elimination of less desirable alternatives.

Abstract
This study focuses on the characterization of the production process of a composite sandwich panel for an aircraft structure. Two curing alternatives were compared, namely hot-press and autoclave. A holistic assessment was conducted applying the Total Efficiency Framework, which combines both process efficiency and environmental performance analyses into a single index score to support manufacturing decision. The study provides inventory data, collected at laboratory scale regarding materials, energy consumption, and process operation for composite panel production, which are seldom available. This foreground data was used to quantify the process efficiency, based on lean design tool, and to estimate the potential environmental impacts, using Life Cycle Assessment methodology to determine the eco-efficiency of the production process. The results suggested that the autoclave curing outperforms the hot-press alternative in terms of efficiency, eco-efficiency, and environmental perfor-mance. Regarding the total efficiency index results for maximum productivity, the results show a difference of 12% between the two alternatives, indicating potential competitive advantages in an industrial setting.

Abstract
In recent years, the Twin-Transition reference model has gained notoriety as one of the key options for decarbonizing the economy while adopting more sustainable models leveraged by the Industry 4.0 paradigm. In this regard, one of the most relevant challenges is the integration of data-driven approaches with sustainability assessment approaches, since overcoming this challenge will foster more agile sustainable development. Without disregarding the effort of academics and practitioners in the development of sustainability assessment approaches, the authors consider the need for holistic frameworks that also encourage continuous improvement in sustainable development. The main objective of this research is to propose a holistic framework that supports companies to assess sustainability performance effectively and more easily, supported by digital capabilities and data-driven concepts, while integrating improvement procedures and methodologies. To achieve this objective, the research is based on the analysis of published approaches, with special emphasis on the data-driven concepts supporting sustainability assessment and Lean Thinking methods. From these results, we identified and extracted the metrics, scopes, boundaries, and kinds of output for decision-making. A new holistic framework is described, and we have included a guide with the steps necessary for its adoption in a given company, thus helping to enhance sustainability while using data availability and data-analytics tools.

Abstract
Humanity faces serious problems related to water supply, which will be aggravated by population growth. The water used in human activities must be treated to make it available again without posing risks to human health and the environment. In this context, Wastewater Treatment Plants (WWTPs) have gained importance. The treatment process in WWTPs is complex, consisting of several stages, which consume considerable amounts of resources, mainly electrical energy. Minimizing such energy consumption while satisfying quality and environmental requirements is essential, but it is a challenging task due to the complexity of the processes carried out in WWTPs. One form of evaluating the performance of WWTPs is through the well-known Key Performance Indicators (KPIs). The KPIs are numerical indicators of process performance, being a simple and common way to assess the efficiency and eco-efficiency of a process. By applying KPIs to WWTPs, techniques for monitoring, predicting, controlling, and optimizing the efficiency and eco-efficiency of WWTPs can be created or improved. However, the use of computational methodologies that use KPIs (KPIs-based methodologies) is still limited. This paper provides a literature review of the current state-of-the-art of KPI-based methodologies to monitor, control and optimize energy efficiency and eco-efficiency in WWTPs. In this paper, studies presented on 21 papers are identified, assessed and synthesized, 12 being related to monitoring and predicting problems, and 9 related to control and optimization problems. Future research directions relating to unresolved problems are also identified and discussed.

Abstract
Over the last years, the numerical simulation of integrated processes has become the major challenge in virtual try-out of sheet metal components, including trimming operations that may occur between forming steps. Detailed simulation of trimming processes is a challenging task, particularly when integrated with other forming operations such as deep drawing or hemming. A simplified approach can be adopted in which elements outside the trim surface are deleted from the finite element (FE) model adjusting the remaining to the surface. Following this approach, the state variables are mapped from the old FE mesh to the new trimmed mesh to continue the simulation. This paper addresses this simplified approach to the trimming process exploring a previously presented algorithm (Finite Elem Anal Des 42: 1053-1060, Baptista et al. 2006), which allows the treatment of hexahedral finite element meshes. Particularly, it focuses on the performance evaluation of the implemented strategies for correcting the FE mesh to the trimming surface, including the treatment of pentahedral-shaped elements. Different correction and treatment strategies are evaluated on different types of meshes, based on numerical simulation results of simple mechanical tests: uniaxial tensile test and simple bending test. Finally, two practical applications are given where the local effect of the trimming algorithm is highlighted. © 2013 Springer-Verlag London.