关键词: 大数据；重型卡车；开发问题；效率提升

Abstract: The development process of heavy-duty truck products is a systematic engineering endeavor, where the efficiency of issue management directly impacts the project development cycle. Traditional issue management and development primarily relies on manual experience and offline operations, making it difficult to achieve informatized collaborative control. Additionally, the lack of data-driven decision support results in low efficiency and insufficient scientific rigor in decisionmaking. The article proposes an information-based approach for comprehensive management of issue feedback, decomposition, and closure throughout heavy-duty truck development processes, while correlating problem resolution status with project progress. Leveraging big data visualization models, it enables categorized statistics, screening, early warnings, and delay tracking of development issues. By presenting complex datasets through intuitive graphics and visualizations,this methodology streamlines data analysis processes, enhances issue control efficiency, and provides robust support for research and development decision-making, project development productivity, and valve review processes.

Key words: big data; heavy-duty truck; development problem; efficiency improvement