The tolerancing of products for manufacturing is usually performed at the end of the design process and the responsibility of the designer. Although components are commonly tolerated to ensure functionality, time-based influences, like wear, that occur during operation, are often neglected. This could result in small amounts of scrap after production, but high quantities of failure during operation. To overcome this issue, this paper presents an approach to perform a multi-objective optimization considering tolerances based on a wear simulation. Thereby, mean shifts serve as optimization variables, while the aim of the optimization is to generate an optimal ratio of scrap to failure. In addition, the optimization results are interpreted and further options for the designer are presented. Moreover, the approach is exemplary applied to a use case.

Mindset has been identified as an essential aspect of design and innovation, impacting both behaviours and performance. However, the concept of design mindset is elusive. Often design mindset is used indistinguishably from design behaviour, diminishing the complexity of the mechanisms and cognitive processes underlying design behaviour. As the initial step in researching these mechanisms, we operationalise the concept of design mindset and present the design mindset inventory (D-Mindset0) to measure it. The initial inventory centered around 16 agreement-to-value statements related to design practice. To analyse the inventory, we conducted an exploratory factor analysis based on 473 master students from different engineering disciplines participating in a course on innovation in engineering. The analysis revealed a four-factor structure with 11 final items. The four factors align with the concepts of ‘conversation with the situation,’ ‘iteration,’ ‘co-evolution of problem-solution,’ and ‘imagination.’

The transition towards circular economy means a radical systemic shift that requires re-design and innovation of business models. However, this radical systemic shift also creates high levels of uncertainty, which pose challenges to the circular business model innovation (CBMI) process. Using the transition towards circular plastics as a case context, this study aims to conceptualize different forms of uncertainty affecting CBMI, and to link them with approaches for managing these uncertainties. Based on interviews with incumbent manufacturing firms that have transitioned to circular plastics, or are in the process of doing so, we identified three domains of uncertainty: goal uncertainty, development uncertainty, and outcome uncertainty. We discuss the nature and sources of these uncertainties, and present different approaches chosen by manufacturers to manage these uncertainties in the context of their business. Our findings highlight the complex nature of uncertainty, and the importance of a nuanced consideration of uncertainty as a factor in the CBMI process. Moreover, our mapping of core uncertainties for CBMI and approaches to manage these uncertainties can guide practitioners in the innovation process.