Understanding the differences between how novice and experienced designers approach design tasks

Research was undertaken to understand how to provide the most appropriate support for novice designers in engineering design. However, how designers apply their experience and knowledge is not understood and further research in this area is required. This paper describes an observational study to understand how novice and experienced designers approach design tasks. Electronic Publication     

A comprehensive tool for developing new human-centred and social inclusion-oriented design strategies and guidelines

While Human-Centred Design is by the time considered a consolidated design methodology, emerging social inclusion-oriented theories need to be more comprehended in order to understand their potential applications in the development of new design solutions. This sort of discrepancy often generates contradictory phenomena: solutions developed using such approaches cannot be considered, at the same time, fully human-centred and social inclusion-oriented. The purpose of this article is to describe a new comprehensive tool, conceived both for designers and researchers, able to develop human-centred and social inclusion-oriented design strategies and guidelines. The tool, which is called ‘HSDT’ (Human-Social Design Tool), is an easy-to-use methodological instrument useful to identify focused results oriented toward Human-Centred Design and Social Inclusion. Using logical sequences, it allows to develop new conceptual definitions for both design and non-design subjects into new human-centred and social inclusion-oriented records. Theoretical foundations, methodological approaches, development stages and applications in design and non-design areas are presented and discussed to demonstrate real benefits resulting from the introduction of a new type of interdisciplinary tool and, later, the opportunity for designers and researchers to adopt new problem-solving approaches to bridging the gaps within Design literature.     

Expert representation of design repository space: A comparison to and validation of algorithmic output

Development of design-by-analogy tools is a promising design innovation research avenue. Previously, a method for computationally structuring patent databases as a basis for an automated design-by-analogy tool was introduced. To demonstrate its strengths and weaknesses, a computationally-generated structure is compared to four expert designers' mental models of the domain. Results indicate that, compared to experts, the computationally-generated structure is sensible in clustering of patents and organization of clusters. The computationally-generated structure represents a space in which experts can find common ground/consensus – making it promising to be intuitive/accessible to broad cohorts of designers. The computational method offers a resource-efficient way of usefully conceptualizing the space that is sensible to expert designers, while maintaining an element of unexpected representation of the space.     

A methodological comparison of the structures of scientific research and engineering design: their similarities and differences

The misunderstanding that engineering is just a part of science (at the most applied science) and that engineering design is only a kind of scientific research (often considered rather trivial) is still widespread, especially among scientists. Yet it is a misunderstanding. In the present paper the structures of scientific research and of engineering design will be compared and, apart from a few very evident similarities, a large number of essential differences will be discussed. The conclusions are on the one hand that science and engineering are strongly interwoven and mutually dependent on each other, but on the other hand that there are fundamental differences between scientific research and engineering design. They consequently require specific methodologies.     

A framework for developing engineering design ontologies within the aerospace industry

This paper presents a framework for developing engineering design ontologies within the aerospace industry. The aim of this approach is to strengthen the modularity and reuse of engineering design ontologies to support knowledge management initiatives within the aerospace industry. Successful development and effective utilisation of engineering ontologies strongly depends on the method/framework used to develop them. Ensuring modularity in ontology design is essential for engineering design activities due to the complexity of knowledge that is required to be brought together to support the product design decision-making process. The proposed approach adopts best practices from previous ontology development methods, but focuses on encouraging modular architectural ontology design. The framework is comprised of three phases namely: (1) Ontology design and development; (2) Ontology validation and (3) Implementation of ontology structure. A qualitative research methodology is employed which is composed of four phases. The first phase defines the capture of knowledge required for the framework development, followed by the ontology framework development, iterative refinement of engineering ontologies and ontology validation through case studies and experts’ opinion. The ontology-based framework is applied in the combustor and casing aerospace engineering domain. The modular ontologies developed as a result of applying the framework and are used in a case study to restructure and improve the accessibility of information on a product design information-sharing platform. Additionally, domain experts within the aerospace industry validated the strengths, benefits and limitations of the framework. Due to the modular nature of the developed ontologies, they were also employed to support other project initiatives within the case study company such as role-based computing (RBC), IT modernisation activity and knowledge management implementation across the sponsoring organisation. The major benefit of this approach is in the reduction of man-hours required for maintaining engineering design ontologies. Furthermore, this approach strengthens reuse of ontology knowledge and encourages modularity in the design and development of engineering ontologies.     

Characterizing Design Learning: A Mixed‐Methods Study of Engineering Designers' Use of Language

Using multiple quantitative and qualitative methods to examine engineering design learning, we found that students taking a course in engineering design and/or studying engineering for four years acquired engineering design language that is common to a larger community of practice as well as common to their own programs and institutions of higher learning. The study also suggests that engineering design language shapes the knowledge that students have about engineering design. Finally, students did not always put their design knowledge into practice, suggesting the need for educational improvements and research to bridge this gap.     

The place of design in the training of professional engineers and managers

To be successful a commercial engineering enterprise must harmonize the different organizational functions: marketing, finance, design, procurement and manufacture.Of these, design is the least understood and often has too little influence in the corporate decision-making circle.This paper suggests that the activities of design and general management have much in common, and that realization of this would go far towards achieving proper balance of the top management team.     

A treatise on order in engineering design research

Engineering design research shows a rather fragmented, if not a chaotic, picture. But does it have a hidden order? Can we explore it, or should we impose a reasoning model? This paper looks for the answer in the purpose of engineering design. It is destined to sustain human existence and well being by virtual creation of artifacts and services for the society. To this end, the engineering design discipline should provide a proper body of knowledge. The design knowledge obtained by empirical exploration and/or rational comprehension should be transformed for practical/pragmatic deployment. It was assumed that this purposely streaming of design knowledge gives a unique rationale for engineering design research. Based on this, a framework of reasoning was constructed, including source, channel, and sink categories of knowledge and research of engineering design, respectively. Within each category, research domains, trajectories, and approaches were identified. The semantic relationships of domains, trajectories, and approaches form a hierarchical structure. The proposed framework enables a grounded argumentation about the order of engineering design research, as well as about the articulation of the engineering design knowledge.     

A cross-disciplinary technology transfer for search-based evolutionary computing: from engineering design to software engineering design

Although object-oriented conceptual software design is difficult to learn and perform, computational tool support for the conceptual software designer is limited. In conceptual engineering design, however, computational tools exploiting interactive evolutionary computation (EC) have shown significant utility. This article investigates the cross-disciplinary technology transfer of search-based EC from engineering design to software engineering design in an attempt to provide support for the conceptual software designer. Firstly, genetic operators inspired by genetic algorithms (GAs) and evolutionary programming are evaluated for their effectiveness against a conceptual software design representation using structural cohesion as an objective fitness function. Building on this evaluation, a multi-objective GA inspired by a non-dominated Pareto sorting approach is investigated for an industrial-scale conceptual design problem. Results obtained reveal a mass of interesting and useful conceptual software design solution variants of equivalent optimality—a typical characteristic of successful multi-objective evolutionary search techniques employed in conceptual engineering design. The mass of software design solution variants produced suggests that transferring search-based technology across disciplines has significant potential to provide computationally intelligent tool support for the conceptual software designer.