The integration of sustainability into highly uncertain technology development is key to support manufacturing companies to reduce their environmental impacts. The use of future scenarios to support decision-making in early design for sustainability is promising, but there is a lack of systematic guidelines on how to build them. Through literature review and empirical research scenario-building guidelines were designed. The guidelines are step-by-step activities to be performed in workshops. Results suggest the guidelines were successful in building consistent, plausible, and useful scenarios.

In the field of individualized medical implants for bone replacesment, additive manufacturing offers far-reaching advantages for bridging bone defects and supporting the production of natural form and function. The article uses the example of a large, customized cranial implant to show the challenges of manufacturing with osteoinductive bone cements. The process is shown, starting with planning and design, through to functional integration using adapted manufacturing strategies to create defined porosity.

Trade-offs involving multiple criteria that cannot be satisfied at the same time are ubiquitous in engineering design activities. Navigating trade-off decisions can be challenging, especially when it comes to sustainability-related decisions in early-stage projects. Through a systematic literature review, we unravel the challenges related to sustainability trade-offs in technology development, concept design, and other front-end of innovation activities. The challenges, which were evaluated by experts from industry and academia, range from technical and organisational to psychological aspects.

Scenario planning is often used in design practice to foster futures thinking, reduce uncertainties and improve decision-making. Scenarios are especially relevant for innovation activities in manufacturing companies, such as technology development, a particularly uncertain process where many trade-offs occur. This study is, to the authors knowledge, the first to empirically measure the effect of scenarios in decision-making quality, in the context of technology development. In a quasi-experiment, engineers from a manufacturing company and university students were independently asked to analyse a trade-off situation between environmental and financial aspects of a technology concept, with and without scenarios. The quality of decision-making quality for control and experiment groups was measured through a standardized questionnaire. The results show that scenarios had a positive impact in 6 of the 7 quality decision-making practices (QMDP), although the effect size is small. The results suggest that both expert and novice designers may benefit from using scenario planning when performing early-stage design activities by having awareness of the decision context, a more structured decision process, and clearer decision criteria.

Digital Twins and Product-Service Systems are just two of the recent trends in product development. While many presented approaches seem promising, their implementation often face challenges. This is especially true if existing approaches are transferred onto new applications. Diving into these topics this paper presents the basics but also challenges as well as synergies emerging between them. The objective is set, to move from specialised applications to broader approaches that can provide benefit to a range of applications and ease the entrance, particularly, for smaller enterprises.

To ensure optimal resource allocation in technology demonstration projects, the evaluation of demonstrators of various maturity, scale, and nature has to be carried out. Most of the existing approaches focus on risk assessment or projected financial return; the need for a tool supporting multi-facet projects evaluation has been identified. This paper presents R2L framework based on three major criteria, defined in detail: Leap Potential, Learning, and Risk. The framework was applied to a real flight-test demonstrator project during workshops in a major aerospace company.

Universities struggle to commercialise scientific research. However, designers can help scientists bridge the research-market gap in different ways. Although the value design can bring to science is understood, how design outputs deliver value to scientific research remains unexplored. Our paper reports findings from a designer-scientist collaboration developing a graphene-based water desalination technology. By reflecting on this case study, we found that design outputs serve different purposes in developing technology and assist in progressing technology maturation efficiently.

A novel application of Best Worst Method (BWM) enables one to incorporate the complexity of specific sub-criteria of technological development to assess its maturity with the pre-established Technology Readiness Level (TRL) framework. It utilizes the concept of Multi-Criteria Decision Making (MCDM) methods to determine the cardinality of endpoint quantitative processes. The model is used to determine the maturity of Class II Ventilators and to detect the consistency aspects for their selection.

Introducing irrigation to smallholder farms in Sub-Saharan Africa (SSA) can increase food security, improve nutrition, and reduce poverty. To explore the possibility of using drip irrigation on smallholder farms in SSA, we introduce a feasibility study that views the design space from both a user-centered lens, explaining how drip might be successful in the future, and from an engineering lens. With a first-order model, we compare estimated capital costs of drip and sprinkler systems for various farm profiles and show that drip has the potential to be a viable technology for many farms in SSA.

Platform design has been firmly established in the automotive industry as a strategy to provide wider product variety while maintaining cost effective production. But this strategy can struggle to keep up with the pace and nature of emerging technologies. This paper reviews the existing approaches to modelling product platforms, and showcases the challenges at OEMs introducing new technological innovations in their platforms. A gap is identified in the methods to assess the ability of existing platforms to integrate new technologies whenever they become available.

Design & Manufacture Knowledge Mapping is a critical activity in medium-to-large organisations supporting many organisational activities. However, techniques for effective mapping of knowledge often employ interviews, consultations and appraisals. Although invaluable in providing expert insight, the application of such methods is inherently intrusive and resource intensive. This paper presents word co-occurrence graphs as a means to automatically generate knowledge maps from technical documents and validates against expert generated knowledge maps.

This paper proposes an analytical framework for estimating the domain where a type of technology can be used in a system. In order to achieve this aim, we have elaborated on the concepts of technology critical, technology sensitive, and the technology comfort zone, to analytically assess the impact of a new technology in the early phases of system design. The result is a general method to indicate the range of requirements that can result in valid designs. This tool can assist in the decision-making processes for technology portfolio selection based on sustainable principles.

Crucial in the design process, Technology Readiness Levels are a common form of technology maturity assessment. Studies suggest that the TRL scale can be subjective and biased. Automating the assessment can reduce human bias. This paper highlights important challenges of automation by presenting data collected on 15 technologies from the nanotechnology sector. Our findings show that, contrary to claims from the literature, patent data exists for low maturity technologies and may be useful for automation. We also found that there exists unexpected trends in data publications at TRL 2, 3 and 4.

Function and constraints modelling are implemented to design two gridded ion thrusters for additive manufacturing (AM). One concept takes advantage of AM design freedom, disregarding AM limitations and is not feasible. The other concept considers AM limitations and is manufacturable and feasible. Constraints modelling highlights AM capabilities that can be improved, showing where future investment is needed. Constraints representation can also support the creation of technology development roadmaps able to identify areas of AM technologies that must be improved.

As digitalisation progresses, the demands placed on companies are increasing at all stages of the product generation process. In order to address these requirements and maintain economic strength, companies must implement innovative and intelligent technologies. Small and medium-sized enterprises in particular are confronted with various obstacles, the overcoming of which is addressed by the “Potential Model” presented in this publication.

We propose a data-driven network-based approach to understand the interactions among technologies, products, and customers. Specifically, the approach enables both a qualitative understanding and a quantitative assessment of the impact of technological changes on customers’ co-consideration behaviors (decision of cross-shopping) and as a consequence the product competitions. The uniqueness of the proposed approach is its capability of predicting complex co-consideration relations of products as a network where both descriptive analyses (e.g., network statistics and joint correspondence analysis) and predictive models (e.g., multiple regressions quadratic assignment procedure) are employed. The integrated network analysis approach features three advantages: (1) It provides an effective visual representation of the underlying market structures; (2) It facilitates the evaluation of the correlation between customers’ consideration preferences and product attributes as well as customer demographics; (3) It enables the prediction of market competitions in response to potential technological changes. This paper demonstrates the proposed network-based approach in a vehicle design context. We investigate the impacts of the fuel economy-boosting technologies and the turbocharged engine technology on individual automakers as well as the entire auto industry. The case study provides vehicle engineers with insights into the change of market competitions brought by technological developments and thereby supports attribute decision-making in vehicle design.