The biological domain has the potential to offer a rich source of analogies to solve engineering design problems. However, due to the complexity embedded in biological systems, adding to the lack of structured, detailed, and searchable knowledge bases, engineering designers find it hard to access the knowledge in the biological domain, which therefore poses challenges in understanding the biological concepts in order to apply these concepts to engineering design problems. In order to assist the engineering designers in problem-solving, we report, in this paper, a web-based tool called Idea-Inspire 4.0 that supports analogical design using two broad features. First, the tool provides access to a number of biological systems using a searchable knowledge base. Second, it explains each one of these biological systems using a multi-modal representation: that is, using function decomposition model, text, function model, image, video, and audio. In this paper, we report two experiments that test how well the multi-modal representation in Idea-Inspire 4.0 supports understanding and application of biological concepts in engineering design problems. In one experiment, we use Bloom's method to test “analysis” and “synthesis” levels of understanding of a biological system. In the next experiment, we provide an engineering design problem along with a biological-analogous system and examine the novelty and requirement-satisfaction (two major indicators of creativity) of resulting design solutions. In both the experiments, the biological system (analogue) was provided using Idea-Inspire 4.0 as well as using a conventional text-image representation so that the efficacy of Idea-Inspire 4.0 is tested using a benchmark.

Since the introduction of spatial grammars 45 years ago, numerous grammars have been developed in a variety of fields from architecture to engineering design. Their benefits for solution space exploration when computationally implemented and combined with optimization have been demonstrated. However, there has been limited adoption of spatial grammars in engineering applications for various reasons. One main reason is the missing, automated, generalized link between the designs generated by the spatial grammar and their evaluation through finite-element analysis (FEA). However, the combination of spatial grammars with optimization and simulation has the advantage over continuous structural topology optimization in that explicit constraints, for example, modeling style and fabrication processes, can be included in the spatial grammar. This paper discusses the challenges in providing a generalized approach by demonstrating the implementation of a framework that combines a three-dimensional spatial grammar interpreter with automated FEA and stochastic optimization using simulated annealing (SA). Guidelines are provided for users to design spatial grammars in conjunction with FEA and integrate automatic application of boundary conditions. A simulated annealing method for use with spatial grammars is also presented including a new method to select rules through a neighborhood definition. To demonstrate the benefits of the framework, it is applied to the automated design and optimization of spokes for inline skate wheels. This example highlights the advantage of spatial grammars for modeling style and additive manufacturing (AM) constraints within the generative system combined with FEA and optimization to carry out topology and shape optimization. The results verify that the framework can generate structurally optimized designs within the style and AM constraints defined in the spatial grammar, and produce a set of topologically diverse, yet valid design solutions.

This paper proposes to contribute to our understanding of the fundamental cognitive processes essential to designing by exploring the experiences of people who have different information processing behaviors to those found in most people. In particular, we focus on people with autism spectrum conditions (ASC) because they are known to have information processing behaviors that are both maladaptive and exceptional. Central to our study is the question: what can we learn from people with ASC about cognitive processes essential to designing? The scholarship on cognitive behaviors associated with the autism spectrum and narratives on the experiences with design practice by individuals with ASC are discussed in relation to cognitive processes associated with designing. In turn, the individuals commented upon the analysis of cognitive processes associated with designing in light of their personal experiences with design practice. We conclude that the weak central coherence theory of autism provides a useful prediction of the cognitive processes necessary for expertise in design, and that both the framework for expertise in design and the way it is studied may require updating.

System architecture is important for the design of complex mechatronic systems because it acts as an intermediator between conceptual design and detail design. An explicit and exact system modeling language is imperative for successful architecture design. However, some deficiencies remain, such as the lack of geometry elements, hybrid behavior description, and specific association semantics for existing architecture modeling languages. In this study, a Systems Modeling Language extension for mechatronic system architecture modeling called ArchME is proposed. The requirements for the mechatronic System Modeling Language are analyzed, and the metamodels are defined. Then, the modeling elements are determined. Finally, the profiles based on the systems modeling language are defined to support the modeling of function, behavior, structure, and their association. This enables system designers to model the system architecture and facilitates communication between different stakeholders. A case study is provided to demonstrate the modeling capability of ArchME.

Biologically inspired design can be used to aid in conceptual design. Sketching is an important ideation process in conceptual design for recording and evaluating flashing moments of inspiration. The present study aims to provide a framework for exploring the effects of biological examples on the sketching contours of products, as well as the perceptual matching degree between design ideas generated via sketching and the desired functions. Elliptic Fourier descriptors with principal component analysis and perceptual matching were used to evaluate and compare the effects of biological examples, no examples, and human-engineered examples from different product categories and within one product category on the sketches in an experiment that involved 28 participants. The application of elliptic Fourier descriptors with principal component analysis shows that there are significant differences in the third and seventh principal components. It is also found that exposure to biological examples can produce more sketches with high perceptual matching degree than the other three conditions, but there are no significant effects of the example exposure on the Pearson correlation coefficients of semantic differential evaluation value vectors between design problems and sketches. These results demonstrate that exposure to biological examples will correlate with Elliptic Fourier descriptors of sketches and will not significantly increase the perceptual matching degree between sketches and the desired function.

I present an implementation of shape grammars that is aimed at supporting designers. It has two parts: a grammar editor and a stand-alone interpreter. The editor is the modeling application Rhinoceros3d using Python scripts. The interpreter is general, is three-dimensional, and supports subshape detection. A grammar is a Rhinoceros3d model; thus users can manipulate all its parts directly and immediately. That is, they can modify any shape without selecting or invoking an editor, and they can lay out the parts of the grammar in any way they find meaningful. Using this approach, which I call a whole-grammar approach, users are shielded from most subdomain tasks, like typing text files or specifying transformations. Informal observations suggest that users of this implementation can work effectively.

An important task in the initial stages of most architectural design processes is the design of planar floor plans, that are composed of non-overlapping rooms divided from each other by walls while satisfying given topological and dimensional constraints. The work described in this paper is part of a larger research aimed at developing the mathematical theory for examining the feasibility of given topological constraints and providing a generic floor plan solution for all possible design briefs.

In this paper, we mathematically describe universal (or generic) rectangular floor plans with n rooms, that is, the floor plans that topologically contain all possible rectangular floor plans with n rooms. Then, we present a graph-theoretical approach for enumerating generic rectangular floor plans upto nine rooms. At the end, we demonstrate the transformation of generic floor plans into a floor plan corresponding to a given graph.

Traditionally, design opportunities and directions are conceived based on expertise, intuition, or time-consuming user studies and marketing research at the fuzzy front end of the design process. Herein, we propose the use of the total technology space map (TSM) as a visual ideation aid for rapidly conceiving high-level design opportunities. The map is comprised of various technology domains positioned according to knowledge proximity, which is measured based on a large quantity of patent data. It provides a systematic picture of the total technology space to enable stimulated ideation beyond the designer's knowledge. Designers can browse the map and navigate various technologies to conceive new design opportunities that relate different technologies across the space. We demonstrate the process of using TSM as a rapid ideation aid and then analyze its applications in two experiments to show its effectiveness and limitations. Furthermore, we have developed a cloud-based system for computer-aided ideation, that is, InnoGPS, to integrate interactive map browsing for conceiving high-level design opportunities with domain-specific patent retrieval for stimulating concrete technical concepts, and to potentially embed machine-learning and artificial intelligence in the map-aided ideation process.

Little research has considered fuzzy scheduling and sequencing problem in operating rooms. Multiple-period fuzzy scheduling and sequencing of patients in operating rooms optimization models are proposed in this research taking into consideration patient‘s preference. The objective of the scheduling optimization model is obtaining minimal undertime and overtime and maximum patients' satisfaction about the assigned date. The objective of sequencing the optimization model is both to minimize overtime and to maximize patients' satisfaction about the assigned time. A real-life case study from a hospital that offers comprehensive surgical procedures for all surgical specialties is considered for illustration. Research results showed that the proposed models efficiently scheduled and sequenced patients while considering their preferences and hospitals operating costs. In conclusion, the proposed optimization models may result in improving patient satisfaction, utilizing hospital's resources efficiently, and providing assistance to decision makers and planners in solving effectively fuzzy scheduling and sequencing problems of operating rooms.

The shape grammar formalism has been discussed theoretically extensively. Recently there has been increased activity in implementing shape grammar interpreters, yet there is a lack of implementations that support parametric rules and emergence. Here the structure of a general parametric shape grammar interpreter is discussed in detail. The interpreter is based on graph grammars. It supports emergence, parametric rules, and numerous types of geometric objects. The shape grammar engine, an agent-based rule selection system and several implementations based on the engine are discussed.

In the design process, different problem statements result in different problem-solving strategies. A proper problem statement is the key to effective problem-solving. Based on the characteristics of the product design process, we divided design problem statements into open-ended (OE), decision-making (DM), and constrained (CO) statements and attempted to investigate the influences of different problem statements on designers’ cognitive behaviors from three perspectives, namely divergent thinking, convergent thinking, and mental workload. Then we provided quantification description to these influences based on electroencephalography (EEG) technology. We conducted experiments on 19 participants and used the BrainProduct™ actiChamp-32 to record the EEG data. Results are as follows: (1) The higher task-related α power was found in the temporal and occipital regions in the OE task compared with that in the DM and CO tasks. The OE statement also would help designers get novel ideas by strengthening their divergent thinking. (2) In the DM and CO tasks, there was no significant difference in the impact of the brain region on convergent thinking, but activities in the left hemisphere were stronger than that in the right hemisphere. The DM and CO tasks have better performance in convergent thinking than the OE task. (3) In the CO task, the designer's mental workload is the highest and mainly related to the activation of the centroparietal and occipital regions. These findings help designers understand the design problem-solving process from the perspective of cognitive science and monitor their thinking modes in the design process so as to improve their design performance.

Analogy is a core cognition process used to produce inferences as well as new ideas using previous knowledge and experience. Ontology is a formal representation of a set of domain concepts and their relationships. The use of analogy and ontology in design activities to support design creativity have previously been explored. This paper explores an approach to construct ontologies with sufficient richness and coverage to support reasoning over real-world datasets for prompting creative idea generation. This approach has been implemented into a computational tool for assisting designers in generating creative ideas during the early stages of design. The tool, called “the Retriever”, has been developed based on ontology by embracing the aspects of analogical reasoning. A case study has indicated that the tool can be effective and useful for idea generation. The results have indicated that the tool, in its current formulation, can significantly improve the fluency and flexibility of idea generation and the usefulness of ideas, as well as slightly increase the originality of ideas, for the case study concerned.

Shape grammars have been developed to codify a specific type of artifact – Queen Anne houses, Buffalo bungalows – or the style of a particular designer – Andrea Palladio, Frank Lloyd Wright, or Álvaro Siza Vieira. However, these specific grammars fail to encode recurrent design moves or features that are above the particularities of a specific design style or the idiosyncrasies of a specific designer and, therefore, are common to a larger category of designs and maybe reutilized and incorporated in the definition of new, specific design languages. To overcome these limitations, the notion of generic grammars for defining design domains is introduced. Its application to the urban design domain is illustrated by showing a generic grammar implementation resulting in a City Information Modeling platform composed of a parametric design interface connected to a geographic database.

Erection planning in shipbuilding is a highly complex process. When a process change happens for some reason, it is often difficult to identify how many factors are affected and estimate how sensitive these factors can be. To optimize the planning and replanning of the shipbuilding plan for the best production performance, a data-driven approach for shipbuilding erection planning is proposed, which is composed of an erection plan model, identification of major factors related to the erection plan, and a data-driven algorithm to apply shipbuilding operation data for creating plans and forecasting, for plan adjustment, future availabilities of shipyard resources including machines, equipment, and man power. Through data clustering, the relevant factors are identified as a result of plan change, and critical equipment health management is carried out through data-driven anomaly detection. A case study is implemented, and the result shows that the proposed data-driven method is able to reschedule the shipbuilding plans smoothly.

This paper presents a multipurpose chair grammar and its implementation in the design tool ChairDNA. This tool is oriented for the exploration of design alternatives in the early concept phase of the chair design process. This work addresses two shortcomings within the research area of shape grammars (SGs), namely, the lack of implementation of SGs applied to design domains, and the lack of practical applications in real-life design scenarios. To address these problems, a methodology is proposed for the implementation of a SG (more specifically, a set grammar) into a tool, comprising the translation of the grammar into user-interface elements oriented for design practitioners. By using the proposed tool, the user can add/delete chair components and edit shape parameters, while visualizing the effects on a three-dimensional digital model presented in a variety of CAD applications. Compared with other SG implementations, ChairDNA uses an approach that keeps under control the combinatorial explosion of rule applications, which simplifies the use of the tool by designers that do not have experience in SGs. The generative potential of the tool is demonstrated by generating chairs of different types, and its usability and utility in aiding the designer are evaluated by design students and design practitioners.