1月22日晚间，瑞晟智能(688215)发布2025年度业绩预告，公司预计全年归属于上市公司股东的净利润 为3392.07万元至3840.07万元，比上年同期增长112.00%至139.99%。 对于2025年业绩实现大幅增长的原因，公告称，报告期内，公司依托核心竞争优势，积极把握行业发展 趋势及市场需求变化，智能工厂装备业务保持稳步增长，同时，公司发展了算力服务器业务，驱动主营 业务收入规模与效益稳步提升，整体经营实现快速增长。此外，公司对外长期股权投资收益贡献增加有 效增强了公司整体盈利水平，为业绩增长提供了重要支持。 此前，瑞晟智能曾在路演活动中介绍公司在AI领域的布局情况：公司正重点推进智能制造协同平台 （IMS）、AI数字孪生管理平台、智能排产系统等一系列人工智能软件产品的市场推广与落地应用，面 向细分行业的AI应用软件产品也将成为公司业务拓展与盈利能力提升的重要方向。 瑞晟智能表示，公司智能工厂装备业务预计将保持稳健发展，仍是公司业务的重要组成部分和增长点之 一。该系统是运用MES所积累的历史与实时数据，训练出的智能化动态排产模型系统，实现比依靠传 统人工排产、排单更均衡、高效的方案，提升生产效率 ...

Core Insights - Many small and medium-sized enterprises (SMEs) face challenges in realizing the return on investment (ROI) from their digital transformation efforts, despite having implemented various systems and automation equipment [3] - Approximately 90% of manufacturing enterprise data remains "asleep," particularly in SMEs, due to a lack of unified data and business process standards, leading to data silos and inefficient business collaboration [3][4] - The digitalization of supply chains is evolving from merely moving procurement processes online to achieving end-to-end collaboration and optimization through data integration [3] Group 1: Challenges in Digital Transformation - Enterprises often have multiple systems (e.g., SAP, PLM, MES) but struggle with data integration, resulting in data silos that hinder effective decision-making [4] - The absence of standardized business and data processes is a fundamental issue, as many companies jump into system implementation without proper design [4] - The "sleeping data" problem is exacerbated by the lack of a centralized data management system and effective edge data processing capabilities [5] Group 2: Solutions and Innovations - Companies are leveraging AI technologies to break down data barriers and enhance data sharing and value realization [4][5] - AI is being applied to improve supply chain transparency, responsiveness, and risk management, with successful case studies demonstrating proactive measures against price increases and stock shortages [6] - The development of platforms like "Procurement Butler" aims to streamline non-standard procurement processes, making them as simple and controllable as online shopping [6] Group 3: Future of AI in Manufacturing - 2025 is anticipated to be a pivotal year for AI applications, particularly in generative AI and large model technologies, although the manufacturing sector's approach differs from that of the internet industry [7] - The focus in manufacturing AI is on "small data" and "scenario closure," rather than the pursuit of large models, emphasizing practical applications over theoretical advancements [7] - Ultimately, the effectiveness of systems and AI in manufacturing will be measured by improvements in supply chain stability, speed, and intelligence [7]

Group 1 - The core viewpoint emphasizes the importance of entrepreneurial spirit in Wuhan's private enterprises, characterized by resilience, innovation, and collaboration [1] - The success of Sifang Optoelectronics in breaking international monopolies with its PM2.5 sensors and high-sensitivity methane sensors highlights the significance of self-reliance in high-end manufacturing [1] - High-performance chip development by Gaode Infrared showcases how core technologies can enhance competitive advantages and contribute to national security [1] Group 2 - The entrepreneurial spirit is described as being rooted in listening to community needs rather than chasing trends, as illustrated by Lichu Business Service's focus on essential services [1] - Wuhan Yimo Technology's significant growth, with a 300% increase in order volume and a projected 50% revenue growth, reflects the long-term commitment to industrial software development [1] - By the end of 2024, the number of private enterprises in Wuhan is expected to exceed one million, with over 90% of high-tech companies being privately owned, indicating a strong trend towards innovation and economic development [2]