卓郎智能2024年营收40.3亿元 扎实推进纺纱机械领域智能化转型

Group 1 - The company reported a revenue of 4.03 billion and a net profit attributable to shareholders of -127 million for the year 2024, indicating challenges in the textile industry due to complex global economic conditions and weak international demand [1] - The textile machinery industry is currently in a phase of low demand, with a decrease in orders due to insufficient domestic market demand, excessive price competition, and rising production costs [2] - Despite the current downturn, positive factors are emerging, such as a shift towards equipment upgrades in the domestic textile machinery market and supportive macroeconomic policies aimed at boosting fixed asset investment [2][3] Group 2 - The government has proposed measures to stimulate effective demand and support consumption, including a 15.7% growth target for equipment investment and a 300 billion special bond issuance for consumption upgrades [3] - The textile machinery industry is experiencing a strong demand for intelligent transformation, with 70% of large-scale textile enterprises achieving digitalization, which will accelerate the demand for intelligent upgrades in textile machinery [3][4] - The company is focusing on technological innovation and product optimization in the natural fiber textile machinery sector, enhancing product performance and reliability to meet diverse global customer needs [5][6] Group 3 - The company is actively advancing digitalization and automation initiatives, introducing advanced digital technologies and automated logistics to improve production efficiency and product quality [6][7] - The company has made significant progress in research and development, launching new models such as the latest 51-type ring spinning machine and achieving energy consumption reductions of over 10% in new automatic spinning machines [6][7] - The intelligent transformation of the textile machinery sector is deepening, with AI technologies being widely applied to equipment control, quality inspection, and production optimization, leading to energy savings of 15%-20% and efficiency improvements of over 30% [7]