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Numerous design methods are available to facilitate digital innovation processes in user interface design. Nonetheless, little guidance exists on their appropriate selection within the design process based on specific situations. Consequently, design novices with limited design knowledge face challenges when determining suitable methods. Thus, this paper aims to support design novices by guiding the situational selection of design methods.

Our research approach includes two phases: i) we adopted a taxonomy development method to identify dimensions of design methods by reviewing 292 potential design methods and interviewing 15 experts; ii) we conducted focus groups with 25 design novices and applied fuzzy-set qualitative comparative analysis to describe the relations between the taxonomy's dimensions.

We developed a novel taxonomy that presents a comprehensive overview of design conditions and their associated design methods in innovation processes. Thus, the taxonomy enables design novices to navigate the complexities of design methods needed to design digital innovation. We also identify configurations of these conditions that support the situational selections of design methods in digital innovation processes of user interface design.

The study’s contribution to the literature lies in the identification of both similarities and differences among design methods, as well as the investigation of sufficient condition configurations within the digital innovation processes of user interface design. The taxonomy helps design novices to navigate the design space by providing an overview of design conditions and the associations between methods and these conditions. By using the developed taxonomy, design novices can narrow down their options when selecting design methods for their specific situations.

While qualitative work has a long tradition in the strategy field and has recently regained popularity, we have not paused to take stock of how such work offers contributions. We address this oversight with a review of qualitative studies of strategy published in five top-tier journals over an extended period of 15 years (2003–2017). In an attempt to organize the field, we develop an empirically grounded organizing framework. We identify 12 designs that are evident in the literature, or “designs-in-use” as we call them. Acknowledging important similarities and differences between the various approaches to qualitative strategy research (QSR), we group these designs into three “families” based on their philosophical orientation. We use these designs and families to identify trends in QSR. We then engage those trends to orient the future development of qualitative methods in the strategy field.

Most buildings are hardly ever technically equipped to adapt to ever changing user demands. Adaptability of building components is known as an essential technical aid to facilitate flexible use. However, for designers and developers it is very difficult to foresee how design decisions related to flexible use effect the efficiency of the technical system, especially when adaptations have to be realized in the future. Due to the large number of variables and interrelations, a structured approach is indispensable to translate (future) user demands into technical solutions for flexible use. Therefore, the purpose of this paper is to present a novel method that can assist designers to systematically find suitable measures for flexible use. This method, named comparative selection method for adaptability measures (CSA method), is developed specifically to impartially select and compare adaptability measures.

The CSA method is principally based on a performance approach, where technical solutions are compared and matched to performance requirements. To accomplish that, specific tools and theories were transferred from industrial product development. The CSA method displays the benefits of lifespan-oriented design, since a distinction is made between initial, once occurring effects and the effects that come with each expected adaptation.

In contemporary building practice the initial phase is critical for decision making. By a number of case studies, the application of the CSA method reveals that tailor-made solutions with a high degree of adaptability are in fact the most efficient for the long term. Hereby the view is confirmed that a lifespan-oriented approach in design decisions is essential for a sustainable and future-proof building stock.

The CSA method is a newly developed and unique support tool that assists in optimizing flexible building design through the search for best fit adaptability solutions.

The high probability of the occurrence of separation bubbles or shocks and early transition to turbulence on surfaces of airfoil makes it very difficult to design high-lift and high-speed Natural-Laminar-Flow (NLF) airfoil for high-altitude long-endurance unmanned air vehicles. To resolve this issue, a framework of uncertainty-based design optimization (UBDO) is developed based on an adjusted polynomial chaos expansion (PCE) method.

The γ ̄Re-θt transition model combined with the shear stress transport k-ω turbulence model is used to predict the laminar-turbulent transition. The particle swarm optimization algorithm and PCE are integrated to search for the optimal NLF airfoil. Using proposed UBDO framework, the aforementioned problem has been regularized to achieve the optimal airfoil with a tradeoff of aerodynamic performances under fully turbulent and free transition conditions. The tradeoff is to make sure its good performance when early transition to turbulence on surfaces of NLF airfoil happens.

The results indicate that UBDO of NLF airfoil considering Mach number and lift coefficient uncertainty under free transition condition shows a significant deterioration when complicated flight conditions lead to early transition to turbulence. Meanwhile, UBDO of NLF airfoil with a tradeoff of performances under both fully turbulent and free transition conditions holds robust and reliable aerodynamic performance under complicated flight conditions.

In this work, the authors build an effective uncertainty-based design framework based on an adjusted PCE method and apply the framework to design two high-performance NLF airfoils. One of the two NLF airfoils considers Mach number and lift coefficient uncertainty under free transition condition, and the other considers uncertainties both under fully turbulent and free transition conditions. The results show that robust design of NLF airfoil should simultaneously consider Mach number, lift coefficient (angle of attack) and transition location uncertainty.

This paper aims to explore advantages and disadvantages of both traditional market research (TMR) and deep customer insight (DCI) methods to lay the platform for revealing how a relationship between these two domains could be optimised during firm-based innovation.

The paper reports on an empirical research study conducted with 13 Australian-based firms engaged in a design-led approach to innovation. Firms were facilitated through a design-led approach where the process of gathering DCIs was isolated and investigated further in comparison to TMR methods.

Results show that DCI methods are able to provide fresh, non-obvious ways of understanding customer needs, problems and behaviours that can become the foundation of new business opportunities. Findings concluded that DCI methods provide the critical layer to understand why customers do or do not engage with businesses. Revealing why was not accessible in TMR methods.

The theoretical outcome of this study is a complementary methods matrix, providing guidance on appropriate implementation of research methods in accordance with a project’s timeline to optimise the complementation of TMR methods with design-led customer engagement methods.

DCI methods provide fresh, non-obvious ways of understanding customer needs, problems and behaviours that can become the foundation of new business opportunities. It is hoped that those in a position of data collection are encouraged to experiment and use DCI methods to connect with their customers on a meaningful level and translate these insights into value.

This paper provides original value to a new understanding of how design techniques can be applied to complement and strengthen existing market research strategies. This is crucial in an era where business competition hinges on a subtle and often intimate understanding of customer needs and behaviours.

This paper aims to provide a comprehensive review of the state-of–the-art design methods for additive manufacturing (AM) technologies to improve functional performance.

In this survey, design methods for AM to improve functional performance are divided into two main groups. They are design methods for a specific objective and general design methods. Design methods in the first group primarily focus on the improvement of functional performance, while the second group also takes other important factors such as manufacturability and cost into consideration with a more general framework. Design methods in each groups are carefully reviewed with discussion and comparison.

The advantages and disadvantages of different design methods for AM are discussed in this paper. Some general issues of existing methods are summarized below: most existing design methods only focus on a single design scale with a single function; few product-level design methods are available for both products’ functionality and assembly; and some existing design methods are hard to implement for the lack of suitable computer-aided design software.

This study is a useful source for designers to select an appropriate design method to take full advantage of AM.

In this survey, a novel classification method is used to categorize existing design methods for AM. Based on this classification method, a comprehensive review is provided in this paper as an informative source for designers and researchers working in this field.

Introduces papers from this area of expertise from the ISEF 1999 Proceedings. States the goal herein is one of identifying devices or systems able to provide prescribed performance. Notes that 18 papers from the Symposium are grouped in the area of automated optimal design. Describes the main challenges that condition computational electromagnetism’s future development. Concludes by itemizing the range of applications from small activators to optimization of induction heating systems in this third chapter.

Reliability-based design optimizations (RBDOs) of engineering structures involve complex non-linear/non-differentiable performance functions, including both continuous and discrete variables. The gradient-based RBDO algorithms are less than satisfactory for these cases. The simulation-based approaches could also be computationally inefficient, especially when the double-loop strategy is used. This paper aims to present a pseudo-double loop flexible RBDO, which is efficient for solving problems, including both discrete/continuous variables.

The method is based on the hybrid improved binary bat algorithm (BBA) and weighed simulation method (WSM). According to this method, each BBA’s movement generates proper candidate solutions, and subsequently, WSM evaluates the reliability levels for design candidates to conduct swarm in a low-cost safe-region.

The accuracy of the proposed enhanced BBA and also the hybrid WSM-BBA are examined for ten benchmark deterministic optimizations and also four RBDO problems of truss structures, respectively. The solved examples reveal computational efficiency and superiority of the method to conventional RBDO approaches for solving complex problems including discrete variables.

Unlike other RBDO approaches, the proposed method is such organized that only one simulation run suffices during the optimization process. The flexibility future of the proposed RBDO framework enables a designer to present multi-level design solutions for different arrangements of the problem by using the results of the only one simulation for WSM, which is very helpful to decrease computational burden of the RBDO. In addition, a new suitable transfer function that enhanced convergence rate and search ability of the original BBA is introduced.

This paper aims to review recent research in design for additive manufacturing (DfAM), including additive manufacturing (AM) terminology, trends, methods, classification of DfAM methods and software. The focus is on the design engineer’s role in the DfAM process and includes which design methods and tools exist to aid the design process. This includes methods, guidelines and software to achieve design optimization and in further steps to increase the level of design automation for metal AM techniques. The research has a special interest in structural optimization and the coupling between topology optimization and AM.

The method used in the review consists of six rounds in which literature was sequentially collected, sorted and removed. Full presentation of the method used could be found in the paper.

Existing DfAM research has been divided into three main groups – component, part and process design – and based on the review of existing DfAM methods, a proposal for a DfAM process has been compiled. Design support suitable for use by design engineers is linked to each step in the compiled DfAM process. Finally, the review suggests a possible new DfAM process that allows a higher degree of design automation than today’s process. Furthermore, research areas that need to be further developed to achieve this framework are pointed out.

The review maps existing research in design for additive manufacturing and compiles a proposed design method. For each step in the proposed method, existing methods and software are coupled. This type of overall methodology with connecting methods and software did not exist before. The work also contributes with a discussion regarding future design process and automation.

Computational efficiency is always the major concern in aircraft design. The purpose of this research is to investigate an efficient jig-shape optimization design method. A new jig-shape optimization method is presented in the current study and its application on the high aspect ratio wing is discussed.

First, the effects of bending and torsion on aerodynamic distribution were discussed. The effect of bending deformation was equivalent to the change of attack angle through a new equivalent method. The equivalent attack angle showed a linear dependence on the quadratic function of bending. Then, a new jig-shape optimization method taking integrated structural deformation into account was proposed. The method was realized by four substeps: object decomposition, optimization design, inversion and evaluation.

After the new jig-shape optimization design, both aerodynamic distribution and structural configuration have satisfactory results. Meanwhile, the method takes both bending and torsion deformation into account.

The new jig-shape optimization method can be well used for the high aspect ratio wing.

The new method is an innovation based on the traditional single parameter design method. It is suitable for engineering application.