Key Takeaways & Executive Findings
- •• Proposes a human-centric product conceptual design model that integrates user feedback in real-time to overcome the hysteresis of traditional linear design processes. • The model employs a feedback-based co-evolution method, enabling iterative convergence of design solutions through problem-driven cycles. • Demonstrated effectiveness via a case study on a natural gas well foaming agent automatic filling device, showing improved iterative efficiency and solution quality. • Aligns with Industry 5.0 principles, emphasizing human-centricity and collaborative designer-user interaction in smart manufacturing.
Abstract
In the context of Industry 5.0, more emphasis is placed on human-centric smart manufacturing patterns. Product design is a vital phase of smart manufacturing, involving user engagement is an essential factor in enhancing design quality and fostering innovation. With user involvement in-depth, dynamically changing user requirements and feedback bring new problems to the design process, and the traditional linear solving process cannot perceive such variations timely, which causes hysteresis in the solution. The design solution’s hysteresis affects the consensus achievement process between the designer and user, further prolonging the iteration cycle. To address this issue, a human-centric product conceptual design model is proposed for the timely translation of such variations into design solutions. In this model, design problems are formed by centering on user requirements, designer and user collaboratively solve the problems to form design solutions. Through a cycle of problem-driven, knowledge-supported, and solution evaluation, new problems are solved promptly to achieve progressive solution convergence, which clarifies the iterative evolution process and improves iterative efficiency. To verify the effectiveness of the model, a natural gas well foaming agent automatic filling device design is presented.
1. Introduction
With the rapid development of new-generation information technology and its deep integration with industry, Industry 5.0 has been introduced to achieve objectives centred on human-centric, sustainability, and resilience [1]. Industry 5.0 emphasizes a human-centric approach to intelligent manufacturing, reinforcing the pivotal of human decision-making within production and manufacturing processes. Conceptual design as the front end of manufacturing, plays an essential role in final product quality and cost. In the process of new product development, inadequate evaluation and fulfillment of user requirements are usually the main reasons for the failure of new product development (NPD) [2], involving the user in the NPD process improves product quality, reduces risk, as well as increases market acceptance [3]. Therefore, in the context of Industry 5.0, the product development process should be human-centric, with designers and users collaborating to complete the generation and iteration of design solutions.
The product development process commences with user requirements analysis, which represents the initial consensus-building phase between the designers and the users. To address the fluctuation in requirements due to user personalisation, many scholars have carried out research on big data mining [4–6] and rapid reconfiguration of manufacturing systems [7]. Big data mining primarily involves the analysis of user feedback on e-commerce platforms, extracting user preferences to enhance product design. However, both the requirements analysis model and big data mining can only obtain part of crucial user requirements. Owing to limitations in professional knowledge and cognitive discrepancies, the user’s real requirements can be fully explored through multiple rounds of interaction between the designer and the user, and the bridge of interaction is the design solution. The traditional product design process includes requirement analysis, problem analysis, concept generation, detail design, and solution evaluation, which is a linear design process, and the design solution is generated at the end of the process, which delays the interaction between designer and user, and there exist a certain degree of hysteresis between the generated design solution and the user’s real requirements. Therefore, a cyclical design process is needed to support the interaction between the designer and the user. Rapid interaction contributes to the convergence of design iterations, therefore, to improve the efficiency of interaction, researchers have carried out studies in terms of interaction cognition [8, 9], and interaction flow [10, 11]. Nevertheless, interaction with mining users’ real requirements is only one aspect of the design process in product design. Iteration is also a significant aspect.
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Bing Lai, Xin Guo, Wu Zhao, Jun Li, Hao Xue, Kai Zhang (2025). Human-centric Product Conceptual Design Model and Its Feedback-based Co-evolution Method. Chinese Journal of Mechanical Engineering. https://doi.org/10.1186/s10033-025-01239-1
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Frequently Asked Questions
What is the main contribution of this paper?
The paper proposes a human-centric product conceptual design model that integrates user feedback in real-time to overcome the hysteresis of traditional linear design processes, improving iterative efficiency and solution convergence.
How does the proposed model work?
The model centers on user requirements, with designers and users collaboratively solving problems. It operates through cycles of problem-driven, knowledge-supported, and solution evaluation, allowing progressive convergence of design solutions.
What is the significance of this research in the context of Industry 5.0?
The research aligns with Industry 5.0's emphasis on human-centricity, promoting collaborative designer-user interaction in smart manufacturing to enhance product quality and innovation.
What case study was used to verify the model?
The model was applied to the design of a natural gas well foaming agent automatic filling device, demonstrating its effectiveness in improving iterative efficiency and solution quality.
What are the key benefits of the feedback-based co-evolution method?
The method enables timely translation of dynamic user requirements into design solutions, reduces hysteresis, and clarifies the iterative evolution process, leading to faster convergence and improved design outcomes.
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