Design for end-of-life and design for disassembly are enabling design strategies for the implementation of business models based on the circular economy paradigm. The paper presents a method for calculating the effective disassembly sequence and time for industrial products. Five steps support designers in defining liaisons and related properties and precedence among components with the aim to calculate the best disassembly sequence and time. The effective disassembly time is computed considering the actual conditions of a product and its components (e.g. deformation, rust and wear) using corrective factors. This aspect represents the main contribution to the state of the art in the field of design for disassembly. The corrective factors are derived from a specific data mining process, based on the observation of real de-manufacturing activities. The proposed approach has been used for calculating the disassembly times of target components in a washing machine and in a coffee machine. The case studies highlight the method reliability of both: definition of time-effective disassembly sequences and assessment of effective disassembly times. In particular, a comparison of experimental tests shows a maximum deviation of −6% for the electric motor of the washing machine and −3% for the water pump of the coffee machine.

Recently, environmentally conscious design and extended producer responsibility have become key aspects for companies that need to develop products that are sustainable along their whole life cycle. Design for End of Life (EoL) is a strategy that aims to reduce landfill waste through the implementation of closed-loop product life cycles. It is important to consider disassembly and EoL scenario management as early as the design phase. For these reasons, this paper presents an approach to help designers in the evaluation and subsequent improvement in product EoL performance. The method is based on four innovative EoL indices that compare different EoL scenarios for each product component. In this way, the designer can modify the product structure or the liaisons to maximise the reuse and remanufacture of components as well as material recycling. The presented case studies confirm the validity of the approach in helping designers during the redesign phase of goods and products to reduce the quantity of materials and industrial wastes sent to landfill.

Higher Education Institutions (HEIs) have been incorporating sustainability into education and curricula, where recent research has focussed on sustainability competences, pedagogical approaches, and how to connect them, generally on a single HEI. The process of integrating sustainability into education based on curricula assessment has been explained using adoption of innovations; and has the potential to explain the process of developing competences through pedagogical approaches. The aim of this paper is to investigate this process at academic discipline level. An online survey was developed to investigate teaching sustainability competences in 13 HEIs, from which 678 responses from educators were obtained. The competences and pedagogical approaches from the responses were ranked, and then the connections between the competences and pedagogical approaches per discipline were analysed using a correlations‐based framework, from which three disciplines groups were created. The groups were categorised using diffusion of innovations theory, which indicated that some disciplines are more innovative than others in adopting sustainability competence‐based teaching. The results are used to propose two frameworks to better understand the adoption of sustainability competence‐based teaching: (a) the D‐RAPID framework; and (b) the Disciplinary Multi‐dimensional Sustainability Influence Change for Academia (D‐MuSICA) memework. The adoption of sustainability competence‐base education must expand from a single HEI perspective to a disciplinary collaborative one spanning many HEIs, where academic disciplines should learn from each other's insights and mistakes and provide students with more transdisciplinary skillsets to make societies more sustainable.

Green building design and architecture have become widespread tenets in the development of sustainable buildings. In this context, the use of sustainable materials and the awareness of resource/energy consumption are strategic aspects to consider for the improvement of building performances. This paper presents a new and structured approach to address uncertainty and sensitivity analysis in Life Cycle Assessment (LCA) to support the decision-making process in building renovation. This “probabilistic” approach to LCA allows for the obtaining of results expressed as ranges of environmental impacts and for alternative solutions, offering an idea of the meaning of input parameters’ uncertainties and their influence on the result. The approach includes (i) the assessment of inputs’ uncertainties (represented by Probability Density Functions—PDF); (ii) the data sampling; and (iii) the uncertainty propagation (Monte Carlo method). Variance decomposition techniques have been used to sample inputs’ PDFs and assess their impact on the LCA result distribution (sensitivity analysis). The methodology application is illustrated through a case study where three building retrofit measures were assessed. Results provide an insight about the uncertainties of LCA indicators in terms of climate change and nonrenewable energy. The input parameters related to the use phase are confirmed as the most influential in building LCA.