Special Issue: Emerging Technologies and Methods for Early-Stage Product Design and Development

摘要

The early-stage product design and development (PDD) process fundamentally involves the processing, synthesis, and communication of a large amount of information to make a series of key decisions on design exploration and specification, concept generation and evaluation, and prototyping. Although most current PDD practices depend heavily on human intuition, advances in computing, communication, and human–computer interaction technologies can transform PDD processes by combining the creativity and ingenuity of human designers with the speed and precision of computers. Emerging technologies like artificial intelligence (AI), cloud computing, and extended reality (XR) stand to substantially change the way designers process information and make decisions in the early stages of PDD by enabling new methods such as natural language processing, generative modeling, cloud-based virtual collaboration, and immersive design and prototyping. These new technologies are unlikely to render the human designer obsolete, but rather do change the role that the human designer plays. Thus, it is essential to understand the designer's role as an individual, a team, and a group that forms an organization. The purpose of this special issue is to synthesize the state-of-the-art research on technologies and methods that augment the performance of designers in the front-end of PDD—from understanding user needs to conceptual design, prototyping, and development of systems architecture while also emphasizing the critical need to understand the designer and their role as well.The research articles that comprise this special issue focus primarily on three major early-stage PDD activities that new technologies and methods can potentially transform: (1) design problem exploration, (2) design concept generation, and (3) design concept evaluation. Articles in the first collection gravitate toward AI methods that facilitate the elicitation of user needs and product usage context, exploration and identification of design problems, and specification of design guidelines. The second collection of research articles contributes new AI methods that enable the automated generation of novel design concepts in various forms, such as textual descriptions, images, and 3D shapes, along with a thorough analysis of the resulting changes in the designer’s role. The third collection of articles investigates new methods based on AI and XR that aim at automating or facilitating design concept evaluation. While these articles break new ground in augmenting the front-end of PDD through new technologies and methods, designers remain the principal actor in this process. It is, therefore, of paramount importance to explore the evolving role of designers in the PDD process and the nature and necessity of their partnership with technology. This special issue also presents research articles that explore biases, beliefs, attitudes, and intentions, as well as the means and method to facilitate the collection, extraction, and organization of their knowledge to support design. The remainder of this Guest Editorial elaborates on the collections of research articles presented in this special issue.The research articles in this collection of early-stage PDD activities focus on various fundamental problems concerning the specification of the design problem to be solved, including design problem identification and definition, elicitation of user needs and product usage contexts, and specification of design objectives and outcomes.In the article “A Computational Approach to Identifying Engineering Design Problems,” Obieke, Milisavljevic-Syed, Silva, and Han present a method based on Markovian models and machine learning to support engineering design problem exploration, a process of identifying or coming up with a new problem or need at the early stage of design. The authors investigate the natural models and phenomena that explain this process, such as rational and garbage can models, and the emer