Design Concept Generation Research Articles

A quantitative aesthetic measurement method for product appearance design

Product appearance is one of the crucial factors that influence consumers’ purchase decisions. The attractiveness of product appearance is mainly determined by the inherent aesthetics of the design composition related to the arrangement of visual design elements. Hence, it is critical to study and improve the arrangement of visual design elements for product appearance design. Strategies that apply aesthetic design principles to assist designers in effectively arranging visual design elements are widely acknowledged in both academia and industry. However, applying aesthetic design principles relies heavily on the designer’s perception and experience, while it is rather challenging for novice designers. Meanwhile, it is hard to measure and quantify design aesthetics in designing artefacts when designers refer to existing successful designs. In this regard, this study aims to introduce a method that assists designers in applying aesthetic design principles to improve the attractiveness of product appearance. Furthermore, formulas for aesthetic measurement based on aesthetic design principles are also developed, and it makes an early attempt to provide quantified aesthetic measurements of design artefacts. A case study on camera design was conducted to demonstrate the merits of the proposed method where the improved strategies for the camera appearance design offer insights for concept generation in product appearance design based on aesthetic design principles.

Generative Pre-Trained Transformer for Design Concept Generation: An Exploration

AbstractNovel concepts are essential for design innovation and can be generated with the aid of data stimuli and computers. However, current generative design algorithms focus on diagrammatic or spatial concepts that are either too abstract to understand or too detailed for early phase design exploration. This paper explores the uses of generative pre-trained transformers (GPT) for natural language design concept generation. Our experiments involve the use of GPT-2 and GPT-3 for different creative reasonings in design tasks. Both show reasonably good performance for verbal design concept generation.

Design concept generation from patent information based on novelty potential and distributional word representation model

Design concept generation from patent information based on novelty potential and distributional word representation model

A framework of design concept generation framework with operations on extensional conceptual space

A framework of design concept generation framework with operations on extensional conceptual space

Design and Analysis a Harvesting Mechanism of Swiftlets Nest

Industry swiftlets nest is not a new industry in Malaysia. It gets very high demand from China. Harvesting swiftlets nest is one of the processes to produce any products that made from swiftlets nest. Currently, they are using manual harvesting equipment to harvest swiftlets nest without using any auxiliary equipment. It is the first step in process flow and very important role before cleaning process. The objectives of this project are to design mechanism harvesting equipment to harvest swiftlets nest and to decrease the time of harvesting swiftlets nest process in a swiftlets house in a day. The methodology of research is including collect data, brainstorming, design concept generation, concept selection and simulation analysis. The design of harvesting equipment is using CAD software and analyze using FEA analysis. At the end of this project, this research will give understanding about design using CAD software and analysis that improved the harvesting equipment.

A framework for managing conceptual design process

Addressing the conceptual design stage as a significant part of design management, this article introduces a framework for concept generation and development in architectural design. Evolving throughout eleven years of experimentation, the framework is formulated as a graphical template to plot eight methods of concept generation, and multiple figurative and operative models for concept transformation and development. The framework is intended to be flexible and supportive of iterative cycling, while also offering an explicit, structured and systemized approach to broaden the solution scope and enhance creativity in the proposed alternatives. Developing language-based structures, the research addresses knowledge management in the initial stages of designing using interdisciplinary knowledge mapping. The research comprises a research-through-design methodology for framework development, and questionnaire surveys for its testing. The findings indicate that the framework helps designers initiate their designing process, guide them throughout the process, and generate a wide variety of creative concepts. Furthermore, the findings demonstrate that the analogy-based method is the most common one in shaping the final design products. Despite its contribution, the framework was criticized for generating too many alternatives that consume time and make decisions more difficult to make.

Characterization of concept generation for engineering design through temporal brain network analysis

This research explores the effect of the structuredness of design concept generation techniques on temporal network neurocognition. Engineering graduate students ( n = 30) completed three concept generation tasks using techniques with different levels of structuredness: brainstorming, morphological analysis, and TRIZ. Students’ brain activation in their prefrontal cortex (PFC) was measured using functional near-infrared spectroscopy (fNIRS). The temporal dynamic of central regions in brain networks were compared between tasks. Central regions facilitate functional interaction and imply information flow through the brain. A consistent central region appears in the medial PFC. Consistent network connections occurred across both hemispheres suggesting a concurrent dual processing of divergent and convergent thinking. This study offers novel insights into the underlying neurophysiological mechanism when using these concept generation techniques. • The medial PFC was a consistently activated central brain region during concept generation. • Similar patterns of co-activation in left and right PFC were observed. • Bilateral co-activation patterns might indicate dual processing between divergent and convergent thinking. • Temporal variations occurred based on the concept generation technique.

Using an Immersive Virtual Reality Design Tool to Support Cognitive Action and Creativity: Educational Insights from Fashion Designers

This study explores how a virtual reality (VR) design tool can enhance designers' cognitive action and creativity in the design process. Ten fashion designers participated in cognitive protocol research and in-depth interviews. Regarding the idea generation process's cognitive action, we limited the experiment to the sketch phase early in the design process and selected a 2D digital design tool for comparison. Expert reviews were also conducted to evaluate the creativity of design outcomes. As a result, we found that the immersive VR design tool activated physical and perceptual action in design cognition and enhanced flexible cognitive action amongst different cognitive action levels compared to the 2D digital design tool. Consequently, we found that the enhanced flexibility in the cognitive process in VR reinforced divergent design thinking in design concept generation and was connected with creative design outcomes.

A Framework of Design Concept Generation Framework with Operations on Extensional Concept Space

A concept space is a graphical tool to map keywords and images of design visually onto a metric space. While it stimulates designers’ability of problem finding and ideation, there are open issues toward design concept generation. This paper proposes a framework of design concept generation with an extensional concept space (ECS). ECS is a metric space of the characteristics, i.e., function and physical attribute, each of which is a set of entities that fall under its definition. The concept distant measurement method based on word2vec with Wikipedia corpus is adopted to extract concepts from documents of design cases and to build a concept space. The framework facilitates a designer to explore a concept space that contains the text and image information with iterative operations, such as function development, and create a new design. This paper demonstrates a case study of chair design to verify the effectiveness of the proposed framework.

Design Concept Generation from Patent Information based on Novelty Potential and Distributional Word Representation Model

Design Concept Generation from Patent Information based on Novelty Potential and Distributional Word Representation Model

Attribute-Aware Generative Design With Generative Adversarial Networks

The designers' tendency to adhere to a specific mental set and heavy emotional investment in their initial ideas often limit their ability to innovate during the design ideation process. The shrinking time-to-market and the growing diversity of users' needs further exacerbate this gap. Recent advances in deep generative models have created new possibilities to overcome the cognitive obstacles of designers through automated generation or editing of design concepts. This article explores the capabilities of generative adversarial networks (GAN) for automated, attribute-aware generative design of the visual attributes of a product. Specifically, a design attribute GAN (DA-GAN) model is developed for automated generation of fashion product images with the desired visual attributes. Experiments on a large fashion dataset signify the potentials of GAN for attribute-aware generative design, verify the ability of editing attributes with relatively higher accuracy and uncover several key challenges and research questions for future work.

Concept generation techniques change patterns of brain activation during engineering design

AbstractThis paper presents the results of studying the brain activations of 30 engineering students when using three different design concept generation techniques: brainstorming, morphological analysis, and TRIZ. Changes in students’ brain activation in the prefrontal cortex were measured using functional near-infrared spectroscopy. The results are based on the area under the curve analysis of oxygenated hemodynamic response as well as an assessment of functional connectivity using Pearson’s correlation to compare students’ cognitive brain activations using these three different ideation techniques. The results indicate that brainstorming and morphological analysis demand more cognitive activation across the prefrontal cortex (PFC) compared to TRIZ. The highest cognitive activation when brainstorming and using morphological analysis is in the right dorsolateral PFC (DLPFC) and ventrolateral PFC. These regions are associated with divergent thinking and ill-defined problem-solving. TRIZ produces more cognitive activation in the left DLPFC. This region is associated with convergent thinking and making judgments. Morphological analysis and TRIZ also enable greater coordination (i.e., synchronized activation) between brain regions. These findings offer new evidence that structured techniques like TRIZ reduce cognitive activation, change patterns of activation and increase coordination between regions in the brain.

Proposal of the novelty potential for design concept generation and its assessment method with word similarity

Proposal of the novelty potential for design concept generation and its assessment method with word similarity

DESIGN, FABRICATION, AND ANALYSIS OF A SMART MOWER

This paper focusses on optimisation of vibration and sound levels of a lawnmower from process cutting with the cutting blade. Technical requirements have been defined for the project including customer requirement, cost model of the product, the checklist of product design specification, concept generation, concept selection and prototyping. These are the fundamental technical requirement to build a safe and efficient of Smart Mower. The experiment was analysed using 200 to 900 wedge angles of cutting blade to cutting grass field simulation for the test of levels of vibration and sound. From the results, it is observed that the analysis of changing wedge angle will provide changes on levels of vibration and sound. The obtained results indicate that the smaller wedge angle gives smaller levels of vibration and sound. The results can also significantly meet all customer requirement according to product development. Therefore, the wedge angle is promising the reduction of vibration level and sound level. At last, this result can reduce the cost, time to market and improve product reliability and customer confidence.

Design for Crashworthiness of Categorical Multimaterial Structures Using Cluster Analysis and Bayesian Optimization

Abstract This work introduces a cluster-based structural optimization (CBSO) method for the design of categorical multimaterial structures subjected to crushing, dynamic loading. The proposed method consists of three steps: conceptual design generation, design clustering, and Bayesian optimization. In the first step, a conceptual design is generated using the hybrid cellular automaton (HCA) algorithm. In the second step, threshold-based cluster analysis yields a lower-dimensional design. Here, a cluster validity index for structural optimization is introduced in order to qualitatively evaluate the clustered design. In the third step, the optimal design is obtained through Bayesian optimization, minimizing a constrained expected improvement function. This function allows to impose soft constraints by properly redefining the expected improvement based on the maximum constraint violation. The Bayesian optimization algorithm implemented in this work has the ability to search over (i) a real design space for sizing optimization, (ii) a categorical design space for material selection, or (iii) a mixed design space for concurrent sizing optimization and material selection. With the proposed method, materials are optimally selected based on multiple attributes and multiple objectives without the need for material ranking. The effectiveness of this approach is demonstrated with the design for crashworthiness of multimaterial plates and thin-walled structures.

A novel data-driven graph-based requirement elicitation framework in the smart product-service system context

Nowadays, industrial companies are facing ever-increasing challenges to generate new value-in-use and maintain their high competitiveness in the market. With the rapid development of Information and Communication Technology (ICT), IT is embedded in the products themselves, i.e. smart, connected products (SCPs) to generate values. Hence, an emerging value proposition paradigm, smart product-service system (Smart PSS) was introduced, by leveraging both SCPs and its generated services as a solution bundle to meet individual customer needs. Unlike other types of PSS, in Smart PSS, massive user-generated data and product-sensed data are collected during the usage phase, where potential requirements can be elicited readily in a value co-creation manner with context-awareness. Nevertheless, only few scholars discuss any systematic manner to support requirement elicitation in such context. To fill the gaps, this research proposes a novel data-driven graph-based requirement elicitation framework in the Smart PSS, so as to assist engineering/designers make better design improvement or new design concept generation in a closed-loop manner. It underlines the informatics-based approach by integrating heterogeneous data sources into a holistic consideration. Moreover, by leveraging graph-based approach, context-product-service information can be linked by the edges and nodes in-between them to derive reliable requirements. To validate its feasibility and advantages, an illustrative example of smart bicycle design improvement is further adopted. As an explorative study, it is hoped that this work provides useful insights for the requirement elicitation process in today’s smart connected environment.

Assessing Concept Novelty Potential with Lexical and Distributional Word Similarity for Innovative Design

AbstractGenerating novel design concepts is a cornerstone for producing innovative products. Although many methods have been proposed for supporting the task, their performance depends on human ability. The goal of this research is to build a method supporting designers to generate novel design concepts with the knowledge of what factors have positive effects on the novelty. Toward the goal, this research assumes that the more distant two function concepts chosen, the more novel idea would come up with by the combination of the two concepts. Based on the assumption, this paper introduces a notion of novelty potential of the combination of two function concepts, and proposes a method to assess it by the function similarity. It is calculated with the integration of a lexical database for natural language called WordNet and a distributional semantics method called word2vec. The proposed method is adapted to case studies in which students perform design concept generation for given design tasks. The correlation analysis is performed to verify the assessment performance of the proposed method. This paper discusses its possibility based on the results of the case studies.

Investigating the Influence of Designers’ Cognitive Characteristics and Interaction Behaviors in Design Concept Generation

This paper investigates relationships among the cognitive characteristics, interaction behaviors, and ideation outcomes of 14 engineering design teams engaged in concept generation. Cognitive characteristics were measured using the Kirton Adaption-Innovation Inventory (KAI), which assesses an individual’s cognitive preference for structure in generating and working with ideas in problem solving. Team interactions were assessed using the Interaction Dynamics Notation (IDN), which allows interaction behaviors to be quantitatively analyzed, while team outcomes were measured in terms of ideation utterances (ideas and unique ideas). Our analyses revealed that cognitive style (KAI) did not correlate significantly with interaction response behaviors (IDN) or with the quantity of ideas/unique ideas produced. However, the cognitive style diversity of the teams did influence the number of topics they discussed, as well as the interconnectedness of those topics. In addition, several specific interaction responses were associated with the occurrence of ideas/unique ideas, although the sequences associated with those responses varied widely; the more adaptive teams also had greater position specificity in these sequences than the more innovative teams. Our findings highlight the importance of forming cognitively diverse design teams and suggest that specific interaction behaviors should be encouraged or taught as a means to increase the occurrence of ideas and/or unique ideas during team concept generation.

A Systematic Study on Design Initiation of Conceptual 3DPVS.

An important product in biomedical and biomimetic engineering is the 3D scaffold, which mimics the real tissue in vitro to achieve the external cultivation of cells. The difference between the 3D scaffold and other biomimetic products lies in the fact that the former mimics the internal features of tissue, while the latter generally approximates the external traits of biological beings. In the field of scaffold engineering, the 3D printed vibratory scaffold, 3DPVS, has been proposed as a present-to-future novel scaffold product, and it currently stays at the stage of conceptual development. To achieve the novel design of the conceptual 3DPVS, a conceptual design process has been established by authors in their previous work, which contain three main stages, namely the design initiation, concept generation, and concept evaluation. In terms of design initiation, it is a ‘must-accomplish’ stage which generates outputs for both the subsequent concept generation and evaluation. Work of design initiation therefore is of significant value and it consists of several tasks; that is, conducting a thorough literature review, summarizing the fundamental issues preparing the general conceptual design, studying the multi-characterization of the 3DPVS, putting forward the potential base model(s), as well as indicating the ideality of the scaffold and establishing potential ideal model(s) for the 3DPVS. In this paper, design initiation will be chiefly focused upon these essential aspects to be discussed, work of which is expected to be useful in establishing a solid ground for future innovation work of the 3DPVS.

Case studies for the application of least common multiple (LCM) algorithm for resolving multi-parameter contradiction by inversion of TRIZ contradiction matrix

A novel algorithm for design concept generation using TRIZ inventive principles for resolving multi-parameter contradiction is described in the paper. The LCM algorithm inverts TRIZ contradiction matrix from parameter versus contradiction versus inventive principles form to solution versus parameter versus contradiction form followed by its bifurcation into two complementary matrices. The concept generation using the complementary matrices has been demonstrated for three case studies—the recursive evolution of inventive principles of algorithm by solving its own TRIZ contradiction matrix; high-performance diesel engine; and development of shrink fit and autofrettage concept for very high-pressure vessel. The first case study validates the algorithm. The recursive evolution leads an algorithm to give non-trivial solution due to positive definiteness as stated by theorem of recursive evolution. The algorithm leads to focussed heuristics and problem-oriented prioritisation of parameters by the bifurcation of solution set into basic inventive solution set and novel solution set. Scientific effect that can potentially constrain the applicability of contradiction resolution is reported. The work includes the updated contradiction matrix (Jou et al. in Adv Mater Sci Eng, 2013. https://doi.org/10.1155/2013/830891 ; Mann and Dewulf in TRIZ J, 2003).