Digital Management Strategies and Technological Innovation in Automotive Advanced Surface Design
Open Access
Article
Conference Proceedings
Authors: Tianbao Cui, Bengang Yi, Minglong Peng, Keyi Zhou, Zhuyu Wang, Xiaoke Zhang
Abstract: The design and development of automotive Advanced Surfaces (AS), which adhere to Bezier curve definitions, are crucial in automotive design. As design management evolves, it now encompasses strategic responsibilities alongside AS model refinement. The role of design in driving corporate innovation, creating new business models, and leading organizational change has been increasingly recognized. In a world increasingly shaped by digital technologies, industries, including the automotive sector, are experiencing profound transformations driven by digitalization. Digital transformation has become a strategic priority for enterprises to maintain competitiveness.AS design projects are long-term and involve complex task allocation and coordination among multiple personnel. Traditional task management methods often fail to accurately capture changes in responsibility, leading to unclear accountability and disruptions in task flow. Additionally, new employees face a steep learning curve, increasing on boarding time and costs, and potentially delaying project timelines. These inefficiencies compromise project performance and overall success.Our digital platform offers an effective solution by centralizing issue management and enabling real-time tracking. This platform ensures that issues are promptly recorded and updated, providing clear visibility into their status and progress. It can also automatically notify relevant personnel to ensure timely follow-up, reducing the risk of omissions or duplicated efforts. This system enhances the precision, efficiency, and transparency of issue resolution, improving overall project management and workflow efficiency.To validate this digital platform we recruited 38 (20F, 18M) to participant to our experiment. NASA-TLX has been employed to measure their performance. We calculated the effect size to present the difference between control and experimental groups. For capturing quantitative data, 6 interviewees (3 professions, 3 novices) have been invited to the semi-structured interview. We used Latent Dirichlet Allocation (LDA) to uncover the latent thematic structure in the text data. This method helps us understand respondents' perspectives and supports subsequent qualitative analysis.In conclusion, we explore the introduction of digital platform management in the AS group and its remarkable results. The digital platform significantly improved data accuracy, traceability, collaboration, and decision-making speed while reducing human errors. User research revealed engineers' pressures during the transition but also highlighted positive feedback on the benefits of digital transformation. This initiative enhances AS group's efficiency and technology-centric transformation, providing a successful example for other groups in the industry.
Keywords: Design Management, Advanced Surfaces Design, Digital Technology, Human factor, Computer Aid Design, Digitalization and Automation
DOI: 10.54941/ahfe1006115
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